Multi-Level Attention Pooling for Graph Neural Networks: Unifying Graph Representations with Multiple Localities

Decision Forests vs. Deep Networks: Conceptual Similarities and Empirical Differences at Small Sample Sizes

Releasing Graph Neural Networks with Differential Privacy Guarantees

Recurrence-Aware Long-Term Cognitive Network for Explainable Pattern Classification

Understanding and Resolving Performance Degradation in Graph Convolutional Networks

Edge-augmented Graph Transformers: Global Self-attention is Enough for Graphs

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks

Generation of Synthetic Electronic Health Records Using a Federated GAN

Deep Dual Support Vector Data Description for Anomaly Detection on Attributed Networks

Learning Fair Graph Neural Networks with Limited and Private Sensitive Attribute Information

Parametric UMAP embeddings for representation and semi-supervised learning

LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis

Physics-Coupled Spatio-Temporal Active Learning for Dynamical Systems

GIPA: General Information Propagation Algorithm for Graph Learning

StrucTexT: Structured Text Understanding with Multi-Modal Transformers

LatticeNet: Fast Spatio-Temporal Point Cloud Segmentation Using Permutohedral Lattices

On the Difficulty of Generalizing Reinforcement Learning Framework for Combinatorial Optimization

Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks

Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks

DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs

Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization

Computing Graph Neural Networks: A Survey from Algorithms to Accelerators

Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning

Deep Neural Networks and End-to-End Learning for Audio Compression

Beyond Low-pass Filtering: Graph Convolutional Networks with Automatic Filtering

Domain adaptation for person re-identification on new unlabeled data using AlignedReID++

GCN-SL: Graph Convolutional Networks with Structure Learning for Graphs under Heterophily

CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals

You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks

Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models

ST-UNet: A Spatio-Temporal U-Network for Graph-structured Time Series Modeling

A Review of Graph Neural Networks and Their Applications in Power Systems

What Can Knowledge Bring to Machine Learning? -- A Survey of Low-shot Learning for Structured Data

Graph Transformer Networks: Learning Meta-path Graphs to Improve GNNs

Learning subtree pattern importance for Weisfeiler-Lehmanbased graph kernels

ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data

Expressive Power of Invariant and Equivariant Graph Neural Networks

Unit Ball Model for Embedding Hierarchical Structures in the Complex Hyperbolic Space

ImGAGN:Imbalanced Network Embedding via Generative Adversarial Graph Networks

SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks

Predicting the Solar Potential of Rooftops using Image Segmentation and Structured Data

Learning Dynamic Graph Representation of Brain Connectome with Spatio-Temporal Attention

An Explainable Probabilistic Classifier for Categorical Data Inspired to Quantum Physics

Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolution

rx-anon -- A Novel Approach on the De-Identification of Heterogeneous Data based on a Modified Mondrian Algorithm

VoxelContext-Net: An Octree based Framework for Point Cloud Compression

Ripple Walk Training: A Subgraph-based training framework for Large and Deep Graph Neural Network

Lifelong Learning of Graph Neural Networks for Open-World Node Classification

VID-WIN: Fast Video Event Matching with Query-Aware Windowing at the Edge for the Internet of Multimedia Things

Accelerating SpMM Kernel with Cache-First Edge Sampling for Graph Neural Networks

Scalable and Flexible Deep Bayesian Optimization with Auxiliary Information for Scientific Problems

Space Partitioning and Regression Mode Seeking via a Mean-Shift-Inspired Algorithm

Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning

Hierarchical Adaptive Pooling by Capturing High-order Dependency for Graph Representation Learning

Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning

SetVAE: Learning Hierarchical Composition for Generative Modeling of Set-Structured Data

Spatio-Temporal Sparsification for General Robust Graph Convolution Networks

Understanding Heart-Failure Patients EHR Clinical Features via SHAP Interpretation of Tree-Based Machine Learning Model Predictions

Recognizing Predictive Substructures with Subgraph Information Bottleneck

CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks

Graph Convolutional Neural Networks with Node Transition Probability-based Message Passing and DropNode Regularization

Degree-Quant: Quantization-Aware Training for Graph Neural Networks

Learning to Represent and Predict Sets with Deep Neural Networks

Set Representation Learning with Generalized Sliced-Wasserstein Embeddings

Unified Robust Training for Graph NeuralNetworks against Label Noise

Deep Graph Structure Learning for Robust Representations: A Survey

Wide Graph Neural Networks: Aggregation Provably Leads to Exponentially Trainability Loss

Mini-Batch Consistent Slot Set Encoder for Scalable Set Encoding

CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting

Incorporating Symbolic Domain Knowledge into Graph Neural Networks

Ego-based Entropy Measures for Structural Representations on Graphs

Integrating Floor Plans into Hedonic Models for Rent Price Appraisal

On PyTorch Implementation of Density Estimators for von Mises-Fisher and Its Mixture

Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs

Deep Autoencoders: From Understanding to Generalization Guarantees

Interpreting and Unifying Graph Neural Networks with An Optimization Framework

A Novel Genetic Algorithm with Hierarchical Evaluation Strategy for Hyperparameter Optimisation of Graph Neural Networks

GraphHop: An Enhanced Label Propagation Method for Node Classification

Graph Neural Networks Exponentially Lose Expressive Power for Node Classification

Passenger Mobility Prediction via Representation Learning for Dynamic Directed and Weighted Graph

Hierarchical Representation via Message Propagation for Robust Model Fitting

Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks

Learning Local Neighboring Structure for Robust 3D Shape Representation

An Experimental Study of the Transferability of Spectral Graph Networks

Sensitive Data Detection with High-Throughput Neural Network Models for Financial Institutions

Decimated Framelet System on Graphs and Fast G-Framelet Transforms

Multi-Output Gaussian Processes with Functional Data: A Study on Coastal Flood Hazard Assessment

Removing Class Imbalance using Polarity-GAN: An Uncertainty Sampling Approach

Mitigating the Impact of Adversarial Attacks in Very Deep Networks

Graph-Based Neural Network Models with Multiple Self-Supervised Auxiliary Tasks

Modelling the influence of data structure on learning in neural networks: the hidden manifold model

Higher-Order Explanations of Graph Neural Networks via Relevant Walks

Explaining Deep Learning Models for Structured Data using Layer-Wise Relevance Propagation

KShapeNet: Riemannian network on Kendall shape space for Skeleton based Action Recognition

Time Series Data Imputation: A Survey on Deep Learning Approaches

Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration

A low latency ASR-free end to end spoken language understanding system

$β$-Cores: Robust Large-Scale Bayesian Data Summarization in the Presence of Outliers

GraphMDN: Leveraging graph structure and deep learning to solve inverse problems

Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realization

The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems

HyperSAGE: Generalizing Inductive Representation Learning on Hypergraphs

Meta Graph Attention on Heterogeneous Graph with Node-Edge Co-evolution

Friendship is All we Need: A Multi-graph Embedding Approach for Modeling Customer Behavior

A Unified View on Graph Neural Networks as Graph Signal Denoising

Evaluating Progress on Machine Learning for Longitudinal Electronic Healthcare Data

Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks

GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks

Residual Embedding Similarity-Based Network Selection for Predicting Brain Network Evolution Trajectory from a Single Observation

Scalable Adversarial Attack on Graph Neural Networks with Alternating Direction Method of Multipliers

Learning Representations for Axis-Aligned Decision Forests through Input Perturbation

Deep Multi-View Spatiotemporal Virtual Graph Neural Network for Significant Citywide Ride-hailing Demand Prediction

Adversarial Privacy Preserving Graph Embedding against Inference Attack

Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust Losses

Inspector Gadget: A Data Programming-based Labeling System for Industrial Images

LatticeNet: Fast Point Cloud Segmentation Using Permutohedral Lattices

Tensor Decompositions in Recursive Neural Networks for Tree-Structured Data

SEAL: Semi-supervised Adversarial Active Learning on Attributed Graphs

Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition

Graph signal processing for machine learning: A review and new perspectives

Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis

Additive Tensor Decomposition Considering Structural Data Information

Graph Convolutional Networks using Heat Kernel for Semi-supervised Learning

MetAL: Active Semi-Supervised Learning on Graphs via Meta Learning

A Hierarchical Approach to Scaling Batch Active Search Over Structured Data

Few-shot link prediction via graph neural networks for Covid-19 drug-repurposing

Extracting Structured Data from Physician-Patient Conversations By Predicting Noteworthy Utterances

Knowledge Graph Driven Approach to Represent Video Streams for Spatiotemporal Event Pattern Matching in Complex Event Processing

Path Integral Based Convolution and Pooling for Graph Neural Networks

Beyond Textual Data: Predicting Drug-Drug Interactions from Molecular Structure Images using Siamese Neural Networks

Structural Landmarking and Interaction Modelling: on Resolution Dilemmas in Graph Classification

Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case

Non-Parametric Graph Learning for Bayesian Graph Neural Networks

Adaptive-Step Graph Meta-Learner for Few-Shot Graph Classification

Differentiable Graph Module (DGM) for Graph Convolutional Networks

Cryptotree: fast and accurate predictions on encrypted structured data

One-Class Graph Neural Networks for Anomaly Detection in Attributed Networks

Location, location, location: Satellite image-based real-estate appraisal

Graph Random Neural Features for Distance-Preserving Graph Representations

HighwayGraph: Modelling Long-distance Node Relations for Improving General Graph Neural Network

Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation

CPR-GCN: Conditional Partial-Residual Graph Convolutional Network in Automated Anatomical Labeling of Coronary Arteries

TensorProjection Layer: A Tensor-Based Dimensionality Reduction Method in CNN

Hierarchical Data Generator based on Tree-Structured Stick Breaking Process for Benchmarking Clustering Methods

word2vec, node2vec, graph2vec, X2vec: Towards a Theory of Vector Embeddings of Structured Data

Unified Multi-Domain Learning and Data Imputation using Adversarial Autoencoder

AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

Semantic Graph Convolutional Networks for 3D Human Pose Regression

EvoNet: A Neural Network for Predicting the Evolution of Dynamic Graphs

Permutation Invariant Graph Generation via Score-Based Generative Modeling

From Node Embedding To Community Embedding : A Hyperbolic Approach

A Framework for End-to-End Learning on Semantic Tree-Structured Data

A Machine Learning Framework for Data Ingestion in Document Images

Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias

Graph Representation Learning via Graphical Mutual Information Maximization

ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

Sharp Rate of Convergence for Deep Neural Network Classifiers under the Teacher-Student Setting

Spectral Inference Networks: Unifying Deep and Spectral Learning

Discriminative Embeddings of Latent Variable Models for Structured Data

A Measure of Similarity in Textual Data Using Spearman's Rank Correlation Coefficient

CASTER: Predicting Drug Interactions with Chemical Substructure Representation

Towards unstructured mortality prediction with free-text clinical notes

Understanding Graph Neural Networks with Asymmetric Geometric Scattering Transforms

Few-Features Attack to Fool Machine Learning Models through Mask-Based GAN

Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural Searching

Graph Representation Learning via Multi-task Knowledge Distillation

Study of Constrained Network Structures for WGANs on Numeric Data Generation

Semi-supervised Learning in Network-Structured Data via Total Variation Minimization

A Flexible Generative Framework for Graph-based Semi-supervised Learning

Metric on random dynamical systems with vector-valued reproducing kernel Hilbert spaces

Active Learning for Graph Neural Networks via Node Feature Propagation

Human Action Recognition with Multi-Laplacian Graph Convolutional Networks

Shapley Homology: Topological Analysis of Sample Influence for Neural Networks

Dilated Convolutional Neural Networks for Sequential Manifold-valued Data

Multimodal Multitask Representation Learning for Pathology Biobank Metadata Prediction

Attention-based Multi-Input Deep Learning Architecture for Biological Activity Prediction: An Application in EGFR Inhibitors

Exploring Structure-Adaptive Graph Learning for Robust Semi-Supervised Classification

A Non-Negative Factorization approach to node pooling in Graph Convolutional Neural Networks

Deep Loopy Neural Network Model for Graph Structured Data Representation Learning

A Unifying View of Explicit and Implicit Feature Maps of Graph Kernels

Deep Weisfeiler-Lehman Assignment Kernels via Multiple Kernel Learning

Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data

Tree-Transformer: A Transformer-Based Method for Correction of Tree-Structured Data

CUTIE: Learning to Understand Documents with Convolutional Universal Text Information Extractor

Novelty Detection via Network Saliency in Visual-based Deep Learning

DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification

Approximation capability of neural networks on spaces of probability measures and tree-structured domains

Bayesian Tensor Factorisation for Bottom-up Hidden Tree Markov Models

On the equivalence between graph isomorphism testing and function approximation with GNNs

GraphNVP: An Invertible Flow Model for Generating Molecular Graphs

Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks

Revisiting Graph Neural Networks: All We Have is Low-Pass Filters

Batch Virtual Adversarial Training for Graph Convolutional Networks

IPC: A Benchmark Data Set for Learning with Graph-Structured Data

Optimal Transport for structured data with application on graphs

Graph Matching Networks for Learning the Similarity of Graph Structured Objects

Hybrid Predictive Model: When an Interpretable Model Collaborates with a Black-box Model

PAN: Path Integral Based Convolution for Deep Graph Neural Networks

Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data

Optimized Skeleton-based Action Recognition via Sparsified Graph Regression

Knowledge-driven Encode, Retrieve, Paraphrase for Medical Image Report Generation

Functional Transparency for Structured Data: a Game-Theoretic Approach

Classifying Signals on Irregular Domains via Convolutional Cluster Pooling

Deep Learning on Attributed Graphs: A Journey from Graphs to Their Embeddings and Back

Convolutional Neural Networks with Transformed Input based on Robust Tensor Network Decomposition

A Tensor-based Structural Health Monitoring Approach for Aeroservoelastic Systems

Bayesian graph convolutional neural networks for semi-supervised classification

Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules

Concept-Oriented Deep Learning: Generative Concept Representations

Learning Depthwise Separable Graph Convolution from Data Manifold

Effective Learning of Probabilistic Models for Clinical Predictions from Longitudinal Data

Metric on Nonlinear Dynamical Systems with Perron-Frobenius Operators

CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters

Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification

Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams

Graph Laplacian Regularized Graph Convolutional Networks for Semi-supervised Learning

Monte Carlo Convolution for Learning on Non-Uniformly Sampled Point Clouds

Context-Dependent Diffusion Network for Visual Relationship Detection

Convolutional Graph Auto-encoder: A Deep Generative Neural Architecture for Probabilistic Spatio-temporal Solar Irradiance Forecasting

RetGK: Graph Kernels based on Return Probabilities of Random Walks

Improving the Expressiveness of Deep Learning Frameworks with Recursion

Topology and Prediction Focused Research on Graph Convolutional Neural Networks

L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data

Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels

When Work Matters: Transforming Classical Network Structures to Graph CNN

BayesGrad: Explaining Predictions of Graph Convolutional Networks

Retrofitting Distributional Embeddings to Knowledge Graphs with Functional Relations

High Dimensional Data Enrichment: Interpretable, Fast, and Data-Efficient

Hybrid Approach of Relation Network and Localized Graph Convolutional Filtering for Breast Cancer Subtype Classification

Superpixel-guided Two-view Deterministic Geometric Model Fitting

Multi Layered-Parallel Graph Convolutional Network (ML-PGCN) for Disease Prediction

A new class of metrics for learning on real-valued and structured data

FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis

Stochastic Training of Graph Convolutional Networks with Variance Reduction

Matching Convolutional Neural Networks without Priors about Data

N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification

A Spatial Mapping Algorithm with Applications in Deep Learning-Based Structure Classification

Natural data structure extracted from neighborhood-similarity graphs

Searching for Representative Modes on Hypergraphs for Robust Geometric Model Fitting

SchNet: A continuous-filter convolutional neural network for modeling quantum interactions

Hidden Tree Markov Networks: Deep and Wide Learning for Structured Data

Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs

A Novel data Pre-processing method for multi-dimensional and non-uniform data

Collaborative Filtering with Side Information: a Gaussian Process Perspective

Geometric Multi-Model Fitting with a Convex Relaxation Algorithm

Deep neural networks on graph signals for brain imaging analysis

A Generalization of Convolutional Neural Networks to Graph-Structured Data

Interactive Graphics for Visually Diagnosing Forest Classifiers in R

Semi-Supervised Classification with Graph Convolutional Networks

On Valid Optimal Assignment Kernels and Applications to Graph Classification

Geometric deep learning on graphs and manifolds using mixture model CNNs

A reliable order-statistics-based approximate nearest neighbor search algorithm

The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition

Superpixel-based Two-view Deterministic Fitting for Multiple-structure Data

Learning Laplacian Matrix in Smooth Graph Signal Representations

Parameterizing Region Covariance: An Efficient Way To Apply Sparse Codes On Second Order Statistics

Learning Kernels for Structured Prediction using Polynomial Kernel Transformations

Building a Large-scale Multimodal Knowledge Base System for Answering Visual Queries

A Deep Learning Model for Structured Outputs with High-order Interaction

Classifying sequences by the optimized dissimilarity space embedding approach: a case study on the solubility analysis of the E. coli proteome

An exact mapping between the Variational Renormalization Group and Deep Learning

Unsupervised Ranking of Multi-Attribute Objects Based on Principal Curves

A Survey on Metric Learning for Feature Vectors and Structured Data

Ensemble Relational Learning based on Selective Propositionalization

Localized Iterative Methods for Interpolation in Graph Structured Data

A Semantic Matching Energy Function for Learning with Multi-relational Data

Regularized Partial Least Squares with an Application to NMR Spectroscopy

Regularized Tensor Factorizations and Higher-Order Principal Components Analysis

Fast, Linear Time, m-Adic Hierarchical Clustering for Search and Retrieval using the Baire Metric, with linkages to Generalized Ultrametrics, Hashing, Formal Concept Analysis, and Precision of Data Measurement

Robust Low-Rank Subspace Segmentation with Semidefinite Guarantees

Self-supervised Learning on Graphs: Contrastive, Generative,or Predictive

What to Prioritize? Natural Language Processing for the Development of a Modern Bug Tracking Solution in Hardware Development

UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation

Fine-tuning Vision Transformers for the Prediction of State Variables in Ising Models

Understanding and Overcoming the Challenges of Efficient Transformer Quantization

Just Train Twice: Improving Group Robustness without Training Group Information

Online Dynamic Window (ODW) Assisted Two-stage LSTM Frameworks for Indoor Localization

Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning

Kronecker CP Decomposition with Fast Multiplication for Compressing RNNs

How to find a good image-text embedding for remote sensing visual question answering?

CPT: Colorful Prompt Tuning for Pre-trained Vision-Language Models

Fine-Grained Image Generation from Bangla Text Description using Attentional Generative Adversarial Network

TransforMesh: A Transformer Network for Longitudinal modeling of Anatomical Meshes

Small-Bench NLP: Benchmark for small single GPU trained models in Natural Language Processing

Natural Language Video Localization with Learnable Moment Proposals

A Closer Look at Temporal Sentence Grounding in Videos: Dataset and Metric

Co-occurrence of medical conditions: Exposing patterns through probabilistic topic modeling of SNOMED codes

Long-Range Modeling of Source Code Files with eWASH: Extended Window Access by Syntax Hierarchy

Primer: Searching for Efficient Transformers for Language Modeling

Self-supervised Contrastive Learning for EEG-based Sleep Staging

RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting

Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach

A Practical Adversarial Attack on Contingency Detection of Smart Energy Systems

W2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Training

On Pursuit of Designing Multi-modal Transformer for Video Grounding

Back to the Basics: A Quantitative Analysis of Statistical and Graph-Based Term Weighting Schemes for Keyword Extraction

GradTS: A Gradient-Based Automatic Auxiliary Task Selection Method Based on Transformer Networks

Compute and Energy Consumption Trends in Deep Learning Inference

Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias in Image Search

Do Transformer Modifications Transfer Across Implementations and Applications?

Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding

Reconstructing and grounding narrated instructional videos in 3D

Line as a Visual Sentence: Context-aware Line Descriptor for Visual Localization

Counterfactual Adversarial Learning with Representation Interpolation

Temporal Pyramid Transformer with Multimodal Interaction for Video Question Answering

EVOQUER: Enhancing Temporal Grounding with Video-Pivoted BackQuery Generation

A Survey on Machine Learning Techniques for Auto Labeling of Video, Audio, and Text Data

Vision Transformers For Weeds and Crops Classification Of High Resolution UAV Images

Improved RAMEN: Towards Domain Generalization for Visual Question Answering

Learning to Generate Scene Graph from Natural Language Supervision

Using Topological Framework for the Design of Activation Function and Model Pruning in Deep Neural Networks

Active Learning Under Malicious Mislabeling and Poisoning Attacks

DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks

M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysis

DKM: Differentiable K-Means Clustering Layer for Neural Network Compression

Shifted Chunk Transformer for Spatio-Temporal Representational Learning

Adaptivity without Compromise: A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization

Web Image Context Extraction with Graph Neural Networks and Sentence Embeddings on the DOM tree

SOMTimeS: Self Organizing Maps for Time Series Clustering and its Application to Serious Illness Conversations

Comprehensive Multi-Modal Interactions for Referring Image Segmentation

SERF: Towards better training of deep neural networks using log-Softplus ERror activation Function

Telling the What while Pointing to the Where: Multimodal Queries for Image Retrieval

Modeling Dynamics of Facial Behavior for Mental Health Assessment

A Multi-input Multi-output Transformer-based Hybrid Neural Network for Multi-class Privacy Disclosure Detection

Airbert: In-domain Pretraining for Vision-and-Language Navigation

Interpreting and improving deep-learning models with reality checks

e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks

Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding

Identifying and Exploiting Structures for Reliable Deep Learning

PIM-DRAM: Accelerating Machine Learning Workloads using Processing in Commodity DRAM

DeepCAD: A Deep Generative Network for Computer-Aided Design Models

A Survey on Deep Reinforcement Learning for Data Processing and Analytics

TransRefer3D: Entity-and-Relation Aware Transformer for Fine-Grained 3D Visual Grounding

Image Retrieval on Real-life Images with Pre-trained Vision-and-Language Models

Adaptive Hierarchical Graph Reasoning with Semantic Coherence for Video-and-Language Inference

Analyzing Information Leakage of Updates to Natural Language Models

Evaluating CLIP: Towards Characterization of Broader Capabilities and Downstream Implications

Transformer-Based Attention Networks for Continuous Pixel-Wise Prediction

A New State-of-the-Art Transformers-Based Load Forecaster on the Smart Grid Domain

Benchmarking machine learning models on multi-centre eICU critical care dataset

Optimizing Latency for Online Video CaptioningUsing Audio-Visual Transformers

Armour: Generalizable Compact Self-Attention for Vision Transformers

HTTP2vec: Embedding of HTTP Requests for Detection of Anomalous Traffic

Perceiver IO: A General Architecture for Structured Inputs & Outputs

StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators

Continual Learning for Recurrent Neural Networks: an Empirical Evaluation

DQ-SGD: Dynamic Quantization in SGD for Communication-Efficient Distributed Learning

Multimodal Attention Networks for Low-Level Vision-and-Language Navigation

Rethinking and Improving Relative Position Encoding for Vision Transformer

InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual Referring

Video Generation from Text Employing Latent Path Construction for Temporal Modeling

A Tale of Two Efficient and Informative Negative Sampling Distributions

A Thorough Review on Recent Deep Learning Methodologies for Image Captioning

Experimenting with Self-Supervision using Rotation Prediction for Image Captioning

Remember What You have drawn: Semantic Image Manipulation with Memory

Segmentation in Style: Unsupervised Semantic Image Segmentation with Stylegan and CLIP

Don't Sweep your Learning Rate under the Rug: A Closer Look at Cross-modal Transfer of Pretrained Transformers

Thought Flow Nets: From Single Predictions to Trains of Model Thought

H-Transformer-1D: Fast One-Dimensional Hierarchical Attention for Sequences

Adversarial Reinforced Instruction Attacker for Robust Vision-Language Navigation

Text Classification and Clustering with Annealing Soft Nearest Neighbor Loss

Integrating Deep Learning and Augmented Reality to Enhance Situational Awareness in Firefighting Environments

Estimating Predictive Uncertainty Under Program Data Distribution Shift

Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks

Toward Collaborative Reinforcement Learning Agents that Communicate Through Text-Based Natural Language

CogME: A Novel Evaluation Metric for Video Understanding Intelligence

QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries

Leveraging Clinical Context for User-Centered Explainability: A Diabetes Use Case

A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

Graphhopper: Multi-Hop Scene Graph Reasoning for Visual Question Answering

The value of text for small business default prediction: A deep learning approach

MuVAM: A Multi-View Attention-based Model for Medical Visual Question Answering

Shell Language Processing: Unix command parsing for Machine Learning

Agents that Listen: High-Throughput Reinforcement Learning with Multiple Sensory Systems

Improving a neural network model by explanation-guided training for glioma classification based on MRI data

MaxVA: Fast Adaptation of Step Sizes by Maximizing Observed Variance of Gradients

SHORING: Design Provable Conditional High-Order Interaction Network via Symbolic Testing

SparseBERT: Rethinking the Importance Analysis in Self-attention

I Want This Product but Different : Multimodal Retrieval with Synthetic Query Expansion

Improving the Efficiency of Transformers for Resource-Constrained Devices

GAttANet: Global attention agreement for convolutional neural networks

Understanding Adversarial Examples Through Deep Neural Network's Response Surface and Uncertainty Regions

Muddling Label Regularization: Deep Learning for Tabular Datasets

SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption

CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image Encoders

AI based Presentation Creator With Customized Audio Content Delivery

Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization

Fine-grained Geolocation Prediction of Tweets with Human Machine Collaboration

iReason: Multimodal Commonsense Reasoning using Videos and Natural Language with Interpretability

A Survey of Quantization Methods for Efficient Neural Network Inference

GAIA: A Transfer Learning System of Object Detection that Fits Your Needs

LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis

Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations

Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better

Improving Compositional Generalization in Classification Tasks via Structure Annotations

Leveraging Language to Learn Program Abstractions and Search Heuristics

All You Can Embed: Natural Language based Vehicle Retrieval with Spatio-Temporal Transformers

Deep reinforcement learning with automated label extraction from clinical reports accurately classifies 3D MRI brain volumes

Multi-modal fusion with gating using audio, lexical and disfluency features for Alzheimer's Dementia recognition from spontaneous speech

Learning Knowledge Graph-based World Models of Textual Environments

Do Large Scale Molecular Language Representations Capture Important Structural Information?

Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning

CMF: Cascaded Multi-model Fusion for Referring Image Segmentation

Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral

Topics to Avoid: Demoting Latent Confounds in Text Classification

Target Model Agnostic Adversarial Attacks with Query Budgets on Language Understanding Models

Contrastive Attention for Automatic Chest X-ray Report Generation

Robust Knowledge Graph Completion with Stacked Convolutions and a Student Re-Ranking Network

MST: Masked Self-Supervised Transformer for Visual Representation

COUnty aggRegation mixup AuGmEntation (COURAGE) COVID-19 Prediction

Which transformer architecture fits my data? A vocabulary bottleneck in self-attention

Energy-Based Models for Code Generation under Compilability Constraints

Conversational Fashion Image Retrieval via Multiturn Natural Language Feedback

Counterfactual Maximum Likelihood Estimation for Training Deep Networks

Generative Adversarial Networks: A Survey Towards Private and Secure Applications

A Compression-Compilation Framework for On-mobile Real-time BERT Applications

Learning Video Models from Text: Zero-Shot Anticipation for Procedural Actions

Look Wide and Interpret Twice: Improving Performance on Interactive Instruction-following Tasks

ClawCraneNet: Leveraging Object-level Relation for Text-based Video Segmentation

Graph Barlow Twins: A self-supervised representation learning framework for graphs

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Attention mechanisms and deep learning for machine vision: A survey of the state of the art

Transformers are Deep Infinite-Dimensional Non-Mercer Binary Kernel Machines

Rethinking Cross-modal Interaction from a Top-down Perspective for Referring Video Object Segmentation

Compressing Large-Scale Transformer-Based Models: A Case Study on BERT

Improving Compositionality of Neural Networks by Decoding Representations to Inputs

Wide-minima Density Hypothesis and the Explore-Exploit Learning Rate Schedule

Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems

Fine-grained Generalization Analysis of Structured Output Prediction

Connecting Language and Vision for Natural Language-Based Vehicle Retrieval

Human Interpretable AI: Enhancing Tsetlin Machine Stochasticity with Drop Clause

NAST: Non-Autoregressive Spatial-Temporal Transformer for Time Series Forecasting

Deep-learning based Tools for Automated Protocol Definition of Advanced Diagnostic Imaging Exams

Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training

Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding

VISITRON: Visual Semantics-Aligned Interactively Trained Object-Navigator

Improved OOD Generalization via Adversarial Training and Pre-training

Semantic and Geometric Modeling with Neural Message Passing in 3D Scene Graphs for Hierarchical Mechanical Search

Robust Facial Expression Recognition with Convolutional Visual Transformers

Empirical Analysis of Image Caption Generation using Deep Learning

Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism

Bidirectional LSTM-CRF Attention-based Model for Chinese Word Segmentation

I2C2W: Image-to-Character-to-Word Transformers for Accurate Scene Text Recognition

Cross-Modal Progressive Comprehension for Referring Segmentation

Information-theoretic Evolution of Model Agnostic Global Explanations

Collaborative Spatial-Temporal Modeling for Language-Queried Video Actor Segmentation

Retrieval-Augmented Generation for Code Summarization via Hybrid GNN

A Graph Neural Network Approach for Product Relationship Prediction

Exploring Explicit and Implicit Visual Relationships for Image Captioning

Interactions in information spread: quantification and interpretation using stochastic block models

Sentiment and Emotion Classification of Epidemic Related Bilingual data from Social Media

Improved and Efficient Text Adversarial Attacks using Target Information

Cross-Level Cross-Scale Cross-Attention Network for Point Cloud Representation

Balancing Constraints and Submodularity in Data Subset Selection

Ask & Explore: Grounded Question Answering for Curiosity-Driven Exploration

SBNet: Segmentation-based Network for Natural Language-based Vehicle Search

Robust Classification from Noisy Labels: Integrating Additional Knowledge for Chest Radiography Abnormality Assessment

Understanding Synonymous Referring Expressions via Contrastive Features

T2VLAD: Global-Local Sequence Alignment for Text-Video Retrieval

Data-Efficient Language-Supervised Zero-Shot Learning with Self-Distillation

Cross-Modal Retrieval Augmentation for Multi-Modal Classification

Do Time Constraints Re-Prioritize Attention to Shapes During Visual Photo Inspection?

Distilling Wikipedia mathematical knowledge into neural network models

Deep Learning for Quantile Regression under Right Censoring: DeepQuantreg

Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks

INODE: Building an End-to-End Data Exploration System in Practice [Extended Vision]

Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks

Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning

Automatic Generation of Descriptive Titles for Video Clips Using Deep Learning

UP-DETR: Unsupervised Pre-training for Object Detection with Transformers

Active$^2$ Learning: Actively reducing redundancies in Active Learning methods for Sequence Tagging and Machine Translation

CityFlow-NL: Tracking and Retrieval of Vehicles at City Scale by Natural Language Descriptions

Siamese Natural Language Tracker: Tracking by Natural Language Descriptions with Siamese Trackers

Language-based Video Editing via Multi-Modal Multi-Level Transformer

Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey

Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis

A Joint Network for Grasp Detection Conditioned on Natural Language Commands

Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark

Text-to-Image Generation Grounded by Fine-Grained User Attention

Spatiotemporal Transformer for Video-based Person Re-identification

EnergyVis: Interactively Tracking and Exploring Energy Consumption for ML Models

Locate then Segment: A Strong Pipeline for Referring Image Segmentation

Entity Context Graph: Learning Entity Representations fromSemi-Structured Textual Sources on the Web

Bridging Vision and Language from the Video-to-Text Perspective: A Comprehensive Review

Gated Transformer Networks for Multivariate Time Series Classification

Multi-source Transfer Learning with Ensemble for Financial Time Series Forecasting

Heavy-tailed Representations, Text Polarity Classification & Data Augmentation

Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking

Self-Supervised Learning of Graph Neural Networks: A Unified Review

Variable Name Recovery in Decompiled Binary Code using Constrained Masked Language Modeling

Attention-based neural re-ranking approach for next city in trip recommendations

Rethinking Relational Encoding in Language Model: Pre-Training for General Sequences

Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data

Reweighting Augmented Samples by Minimizing the Maximal Expected Loss

Boundary Proposal Network for Two-Stage Natural Language Video Localization

Show, Price and Negotiate: A Negotiator with Online Value Look-Ahead

Locality Preserving Loss: Neighbors that Live together, Align together

Symbolic integration by integrating learning models with different strengths and weaknesses

Beyond Nyströmformer -- Approximation of self-attention by Spectral Shifting

Noisy Label Learning for Large-scale Medical Image Classification

Learning Transferable Visual Models From Natural Language Supervision

Application of Transfer Learning to Sign Language Recognition using an Inflated 3D Deep Convolutional Neural Network

Theoretical Understandings of Product Embedding for E-commerce Machine Learning

V2W-BERT: A Framework for Effective Hierarchical Multiclass Classification of Software Vulnerabilities

Probing Multimodal Embeddings for Linguistic Properties: the Visual-Semantic Case

QuerYD: A video dataset with high-quality text and audio narrations

Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with $1/n$ Parameters

Improved Bengali Image Captioning via deep convolutional neural network based encoder-decoder model

Doping: A technique for efficient compression of LSTM models using sparse structured additive matrices

Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices

Quadric hypersurface intersection for manifold learning in feature space

SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Data

A Bayesian nonparametric approach to count-min sketch under power-law data streams

Lie-Sensor: A Live Emotion Verifier or a Licensor for Chat Applications using Emotional Intelligence

A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention

Referring Segmentation in Images and Videos with Cross-Modal Self-Attention Network

Large-Scale Training System for 100-Million Classification at Alibaba

Learning-augmented count-min sketches via Bayesian nonparametrics

Points2Vec: Unsupervised Object-level Feature Learning from Point Clouds

Enhance Information Propagation for Graph Neural Network by Heterogeneous Aggregations

Structured Sparsity Inducing Adaptive Optimizers for Deep Learning

Spatial-Channel Transformer Network for Trajectory Prediction on the Traffic Scenes

Robustness of on-device Models: Adversarial Attack to Deep Learning Models on Android Apps

In Nomine Function: Naming Functions in Stripped Binaries with Neural Networks

Efficient Conformal Prediction via Cascaded Inference with Expanded Admission

Structured Prediction as Translation between Augmented Natural Languages

Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings

Visual Question Answering based on Local-Scene-Aware Referring Expression Generation

Adversarially Robust and Explainable Model Compression with On-Device Personalization for Text Classification

A modular vision language navigation and manipulation framework for long horizon compositional tasks in indoor environment

Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational Autoencoders

Interpretable Policy Specification and Synthesis through Natural Language and RL

Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability

IdBench: Evaluating Semantic Representations of Identifier Names in Source Code

Exploration of Visual Features and their weighted-additive fusion for Video Captioning

Watch and Learn: Mapping Language and Noisy Real-world Videos with Self-supervision

A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

Fast Ensemble Learning Using Adversarially-Generated Restricted Boltzmann Machines

Visual Probing and Correction of Object Recognition Models with Interactive user feedback

Recomposition vs. Prediction: A Novel Anomaly Detection for Discrete Events Based On Autoencoder

Data-driven Operation of the Resilient Electric Grid: A Case of COVID-19

Learning 2D Temporal Adjacent Networks for Moment Localization with Natural Language

Image Synthesis with Adversarial Networks: a Comprehensive Survey and Case Studies

Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games

Language and Visual Entity Relationship Graph for Agent Navigation

Visual Question Answering using Deep Learning: A Survey and Performance Analysis

Image to Bengali Caption Generation Using Deep CNN and Bidirectional Gated Recurrent Unit

Video Super Resolution Based on Deep Learning: A Comprehensive Survey

Stabilizing Transformer-Based Action Sequence Generation For Q-Learning

FsNet: Feature Selection Network on High-dimensional Biological Data

Efficient CNN-LSTM based Image Captioning using Neural Network Compression

MASKER: Masked Keyword Regularization for Reliable Text Classification

Revisiting Linformer with a modified self-attention with linear complexity

Rule Extraction from Binary Neural Networks with Convolutional Rules for Model Validation

Exploring Vicinal Risk Minimization for Lightweight Out-of-Distribution Detection

*-CFQ: Analyzing the Scalability of Machine Learning on a Compositional Task

Indonesian ID Card Extractor Using Optical Character Recognition and Natural Language Post-Processing

Generation of complex database queries and API calls from natural language utterances

MSVD-Turkish: A Comprehensive Multimodal Dataset for Integrated Vision and Language Research in Turkish

Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures

Understanding Recurrent Neural Architectures by Analyzing and Synthesizing Long Distance Dependencies in Benchmark Sequential Datasets

Discovering key topics from short, real-world medical inquiries via natural language processing and unsupervised learning

Referring Expression Comprehension: A Survey of Methods and Datasets

Parallel Blockwise Knowledge Distillation for Deep Neural Network Compression

Multi-Scale 2D Temporal Adjacent Networks for Moment Localization with Natural Language

A Study on the Autoregressive and non-Autoregressive Multi-label Learning

MQTransformer: Multi-Horizon Forecasts with Context Dependent and Feedback-Aware Attention

DecisiveNets: Training Deep Associative Memories to Solve Complex Machine Learning Problems

A Framework and Dataset for Abstract Art Generation via CalligraphyGAN

Parallel Scheduling Self-attention Mechanism: Generalization and Optimization

Fast Automatic Feature Selection for Multi-Period Sliding Window Aggregate in Time Series

Automatic coding of students' writing via Contrastive Representation Learning in the Wasserstein space

Directed Graph Attention Neural Network Utilizing 3D Coordinates for Molecular Property Prediction

Multi-stage Attention ResU-Net for Semantic Segmentation of Fine-Resolution Remote Sensing Images

Profile Prediction: An Alignment-Based Pre-Training Task for Protein Sequence Models

A Comprehensive Review on Recent Methods and Challenges of Video Description

Fashion IQ: A New Dataset Towards Retrieving Images by Natural Language Feedback

Underspecification Presents Challenges for Credibility in Modern Machine Learning

Improving Federated Relational Data Modeling via Basis Alignment and Weight Penalty

DTGAN: Dual Attention Generative Adversarial Networks for Text-to-Image Generation

Parrot: Data-Driven Behavioral Priors for Reinforcement Learning

PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards

A Multi-class Approach -- Building a Visual Classifier based on Textual Descriptions using Zero-Shot Learning

Structural and Functional Decomposition for Personality Image Captioning in a Communication Game

ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language

Using GANs to Synthesise Minimum Training Data for Deepfake Generation

On Posterior Collapse and Encoder Feature Dispersion in Sequence VAEs

Detecting Early Onset of Depression from Social Media Text using Learned Confidence Scores

Drinking from a Firehose: Continual Learning with Web-scale Natural Language

Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference

Beyond the Deep Metric Learning: Enhance the Cross-Modal Matching with Adversarial Discriminative Domain Regularization

VisualHints: A Visual-Lingual Environment for Multimodal Reinforcement Learning

Differentially Private Language Models Benefit from Public Pre-training

A Comprehensive Overview and Survey of Recent Advances in Meta-Learning

An empirical study of domain-agnostic semi-supervised learning via energy-based models: joint-training and pre-training

Position and Rotation Invariant Sign Language Recognition from 3D Point Cloud Data with Recurrent Neural Networks

Lightweight Generative Adversarial Networks for Text-Guided Image Manipulation

Pólya Urn Latent Dirichlet Allocation: a doubly sparse massively parallel sampler

Measuring Systematic Generalization in Neural Proof Generation with Transformers

A Survey on Deep Learning and Explainability for Automatic Image-based Medical Report Generation

Dual Averaging is Surprisingly Effective for Deep Learning Optimization

How much progress have we made in neural network training? A New Evaluation Protocol for Benchmarking Optimizers

Predicting Chemical Properties using Self-Attention Multi-task Learning based on SMILES Representation

Learning to Stop: A Simple yet Effective Approach to Urban Vision-Language Navigation

TextMage: The Automated Bangla Caption Generator Based On Deep Learning

Fantastic Features and Where to Find Them: Detecting Cognitive Impairment with a Subsequence Classification Guided Approach

DORi: Discovering Object Relationship for Moment Localization of a Natural-Language Query in Video

Revisiting Image-Language Networks for Open-ended Phrase Detection

TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translation

Self-attention aggregation network for video face representation and recognition

A Graph Neural Network Approach for Scalable and Dynamic IP Similarity in Enterprise Networks

gundapusunil at SemEval-2020 Task 8: Multimodal Memotion Analysis

Widget Captioning: Generating Natural Language Description for Mobile User Interface Elements

Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation

Multi-label classification of promotions in digital leaflets using textual and visual information

Uncovering Hidden Challenges in Query-Based Video Moment Retrieval

PyMT5: multi-mode translation of natural language and Python code with transformers

Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs

Using Sentences as Semantic Representations in Large Scale Zero-Shot Learning

Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models

MLE-guided parameter search for task loss minimization in neural sequence modeling

Linguistic Structure Guided Context Modeling for Referring Image Segmentation

Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning

Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers

CAPTION: Correction by Analyses, POS-Tagging and Interpretation of Objects using only Nouns

Referring Image Segmentation via Cross-Modal Progressive Comprehension

A survey on natural language processing (nlp) and applications in insurance

Finding It at Another Side: A Viewpoint-Adapted Matching Encoder for Change Captioning

A Survey on Deep Learning Techniques for Video Anomaly Detection

Arabic Handwritten Character Recognition based on Convolution Neural Networks and Support Vector Machine

An Adversarial Approach for Explaining the Predictions of Deep Neural Networks

Virtual Experience to Real World Application: Sidewalk Obstacle Avoidance Using Reinforcement Learning for Visually Impaired

GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference

Deep Neural Networks with Short Circuits for Improved Gradient Learning

Comparing Natural Language Processing Techniques for Alzheimer's Dementia Prediction in Spontaneous Speech

State-of-the-Art Augmented NLP Transformer models for direct and single-step retrosynthesis

Learning Unseen Emotions from Gestures via Semantically-Conditioned Zero-Shot Perception with Adversarial Autoencoders

Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes

Faces à la Carte: Text-to-Face Generation via Attribute Disentanglement

Reinforcement Learning for Weakly Supervised Temporal Grounding of Natural Language in Untrimmed Videos

A Multimodal Memes Classification: A Survey and Open Research Issues

Deep Collective Learning: Learning Optimal Inputs and Weights Jointly in Deep Neural Networks

Towards non-toxic landscapes: Automatic toxic comment detection using DNN

Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods

LaSOT: A High-quality Large-scale Single Object Tracking Benchmark

Historical Document Processing: Historical Document Processing: A Survey of Techniques, Tools, and Trends

TRACE: Transform Aggregate and Compose Visiolinguistic Representations for Image Search with Text Feedback

All Data Inclusive, Deep Learning Models to Predict Critical Events in the Medical Information Mart for Intensive Care III Database (MIMIC III)

Robustness to Programmable String Transformations via Augmented Abstract Training

A Multisite, Report-Based, Centralized Infrastructure for Feedback and Monitoring of Radiology AI/ML Development and Clinical Deployment

CORAL: COde RepresentAtion Learning with Weakly-Supervised Transformers for Analyzing Data Analysis

PermuteAttack: Counterfactual Explanation of Machine Learning Credit Scorecards

Predicting conversions in display advertising based on URL embeddings

An Intelligent CNN-VAE Text Representation Technology Based on Text Semantics for Comprehensive Big Data

A Fast and Robust BERT-based Dialogue State Tracker for Schema-Guided Dialogue Dataset

VLANet: Video-Language Alignment Network for Weakly-Supervised Video Moment Retrieval

Describing Unseen Videos via Multi-Modal Cooperative Dialog Agents

NukeBERT: A Pre-trained language model for Low Resource Nuclear Domain

Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval

Finding Fast Transformers: One-Shot Neural Architecture Search by Component Composition

Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery

We Have So Much In Common: Modeling Semantic Relational Set Abstractions in Videos

A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI

Describe What to Change: A Text-guided Unsupervised Image-to-Image Translation Approach

Location-aware Graph Convolutional Networks for Video Question Answering

Rethinking Generative Zero-Shot Learning: An Ensemble Learning Perspective for Recognising Visual Patches

The End-of-End-to-End: A Video Understanding Pentathlon Challenge (2020)

Weakly supervised one-stage vision and language disease detection using large scale pneumonia and pneumothorax studies

ViTAA: Visual-Textual Attributes Alignment in Person Search by Natural Language

Adversarial Robustness for Machine Learning Cyber Defenses Using Log Data

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Understanding the temporal evolution of COVID-19 research through machine learning and natural language processing

SPARK: Spatial-aware Online Incremental Attack Against Visual Tracking

Evaluating a Simple Retraining Strategy as a Defense Against Adversarial Attacks

Learning User Preferences and Understanding Calendar Contexts for Event Scheduling

Learning to Discretely Compose Reasoning Module Networks for Video Captioning

Counterfactual Vision-and-Language Navigation via Adversarial Path Sampling

Comprehensive Facial Expression Synthesis using Human-Interpretable Language

MeDaS: An open-source platform as service to help break the walls between medicine and informatics

A Novel Attention-based Aggregation Function to Combine Vision and Language

Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation

Diverse and Styled Image Captioning Using SVD-Based Mixture of Recurrent Experts

Deep Contextual Embeddings for Address Classification in E-commerce

GateNet: Gating-Enhanced Deep Network for Click-Through Rate Prediction

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

Modality-Agnostic Attention Fusion for visual search with text feedback

Learning to cooperate: Emergent communication in multi-agent navigation

SACT: Self-Aware Multi-Space Feature Composition Transformer for Multinomial Attention for Video Captioning

Measuring Compositional Generalization: A Comprehensive Method on Realistic Data

Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformers

I-BERT: Inductive Generalization of Transformer to Arbitrary Context Lengths

Transfer Learning or Self-supervised Learning? A Tale of Two Pretraining Paradigms

Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network

VATEX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research

Fast Maximum Likelihood Estimation and Supervised Classification for the Beta-Liouville Multinomial

NAS-Bench-NLP: Neural Architecture Search Benchmark for Natural Language Processing

Language-Conditioned Goal Generation: a New Approach to Language Grounding for RL

RTEX: A novel methodology for Ranking, Tagging, and Explanatory diagnostic captioning of radiography exams

Shaping Visual Representations with Language for Few-shot Classification

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Translating Natural Language Instructions for Behavioral Robot Navigation with a Multi-Head Attention Mechanism

Improving Disentangled Text Representation Learning with Information-Theoretic Guidance

MAGNet: Multi-Region Attention-Assisted Grounding of Natural Language Queries at Phrase Level

Auxiliary Signal-Guided Knowledge Encoder-Decoder for Medical Report Generation

Permutation Matters: Anisotropic Convolutional Layer for Learning on Point Clouds

2D Image Features Detector And Descriptor Selection Expert System

Template-Based Automatic Search of Compact Semantic Segmentation Architectures

Hidden Markov Chains, Entropic Forward-Backward, and Part-Of-Speech Tagging

The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models

Touchdown: Natural Language Navigation and Spatial Reasoning in Visual Street Environments

Copy mechanism and tailored training for character-based data-to-text generation

A Survey of the Recent Architectures of Deep Convolutional Neural Networks

Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces

A detailed comparative study of open source deep learning frameworks

Neural-Symbolic Relational Reasoning on Graph Models: Effective Link Inference and Computation from Knowledge Bases

AdaX: Adaptive Gradient Descent with Exponential Long Term Memory

Applying Recent Innovations from NLP to MOOC Student Course Trajectory Modeling

An Information-theoretic Visual Analysis Framework for Convolutional Neural Networks

Beyond the Nav-Graph: Vision-and-Language Navigation in Continuous Environments

Packet2Vec: Utilizing Word2Vec for Feature Extraction in Packet Data

Emerging Relation Network and Task Embedding for Multi-Task Regression Problems

Deep Conversational Recommender Systems: A New Frontier for Goal-Oriented Dialogue Systems

Inferring Temporal Compositions of Actions Using Probabilistic Automata

A Real-Time Cross-modality Correlation Filtering Method for Referring Expression Comprehension

Sequential Interpretability: Methods, Applications, and Future Direction for Understanding Deep Learning Models in the Context of Sequential Data

HCM: Hardware-Aware Complexity Metric for Neural Network Architectures

Hierarchical Image Classification using Entailment Cone Embeddings

Computation on Sparse Neural Networks: an Inspiration for Future Hardware

Learning What Makes a Difference from Counterfactual Examples and Gradient Supervision

A Novel Method of Extracting Topological Features from Word Embeddings

Relationship-Embedded Representation Learning for Grounding Referring Expressions

SECRET: Semantically Enhanced Classification of Real-world Tasks

YouMakeup VQA Challenge: Towards Fine-grained Action Understanding in Domain-Specific Videos

A Neuro-AI Interface for Evaluating Generative Adversarial Networks

Towards Learning a Generic Agent for Vision-and-Language Navigation via Pre-training

Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization

A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects

Vision-Language Navigation with Self-Supervised Auxiliary Reasoning Tasks

DeepSumm -- Deep Code Summaries using Neural Transformer Architecture

Take the Scenic Route: Improving Generalization in Vision-and-Language Navigation

ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks

LoGAN: Latent Graph Co-Attention Network for Weakly-Supervised Video Moment Retrieval

Video Object Grounding using Semantic Roles in Language Description

Data-driven models and computational tools for neurolinguistics: a language technology perspective

MUTATT: Visual-Textual Mutual Guidance for Referring Expression Comprehension

Multi-task Collaborative Network for Joint Referring Expression Comprehension and Segmentation

Proposal-free Temporal Moment Localization of a Natural-Language Query in Video using Guided Attention

SMArT: Training Shallow Memory-aware Transformers for Robotic Explainability

word2ket: Space-efficient Word Embeddings inspired by Quantum Entanglement

Video Description: A Survey of Methods, Datasets and Evaluation Metrics

Cops-Ref: A new Dataset and Task on Compositional Referring Expression Comprehension

Intelligent Home 3D: Automatic 3D-House Design from Linguistic Descriptions Only

Device Heterogeneity in Federated Learning: A Superquantile Approach

Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP

AI-based Prediction of Independent Construction Safety Outcomes from Universal Attributes

A Convolutional Baseline for Person Re-Identification Using Vision and Language Descriptions

How To Avoid Being Eaten By a Grue: Exploration Strategies for Text-Adventure Agents

WaLDORf: Wasteless Language-model Distillation On Reading-comprehension

Use What You Have: Video Retrieval Using Representations From Collaborative Experts

GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing

Fast And Efficient Boolean Matrix Factorization By Geometric Segmentation

Evaluating Sequence-to-Sequence Learning Models for If-Then Program Synthesis

A Generalized Framework of Sequence Generation with Application to Undirected Sequence Models

Synthetic-Neuroscore: Using A Neuro-AI Interface for Evaluating Generative Adversarial Networks

Dual Convolutional LSTM Network for Referring Image Segmentation

Urban2Vec: Incorporating Street View Imagery and POIs for Multi-Modal Urban Neighborhood Embedding

Controlling generative models with continuous factors of variations

Graph Constrained Reinforcement Learning for Natural Language Action Spaces

Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models

A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications

FlexiBO: Cost-Aware Multi-Objective Optimization of Deep Neural Networks

Weakly-Supervised Video Moment Retrieval via Semantic Completion Network

PoPS: Policy Pruning and Shrinking for Deep Reinforcement Learning

REVERIE: Remote Embodied Visual Referring Expression in Real Indoor Environments

Dirichlet uncertainty wrappers for actionable algorithm accuracy accountability and auditability

Biology and Compositionality: Empirical Considerations for Emergent-Communication Protocols

An Analysis of the Expressiveness of Deep Neural Network Architectures Based on Their Lipschitz Constants

TextNAS: A Neural Architecture Search Space tailored for Text Representation

Reweighted Proximal Pruning for Large-Scale Language Representation

Differentiable Reasoning on Large Knowledge Bases and Natural Language

Image Manipulation with Natural Language using Two-sidedAttentive Conditional Generative Adversarial Network

Attending Form and Context to Generate Specialized Out-of-VocabularyWords Representations

Visual-Textual Association with Hardest and Semi-Hard Negative Pairs Mining for Person Search

Compositional Temporal Visual Grounding of Natural Language Event Descriptions

Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics

On the Possibility of Rewarding Structure Learning Agents: Mutual Information on Linguistic Random Sets

Real-time Visual Object Tracking with Natural Language Description

TreeGen: A Tree-Based Transformer Architecture for Code Generation

Learning Universal Graph Neural Network Embeddings With Aid Of Transfer Learning

An Optimized and Energy-Efficient Parallel Implementation of Non-Iteratively Trained Recurrent Neural Networks

Skeleton based Zero Shot Action Recognition in Joint Pose-Language Semantic Space

Unsupervised Visual Representation Learning with Increasing Object Shape Bias

A Transfer Learning Method for Goal Recognition Exploiting Cross-Domain Spatial Features

Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding

Learning to Control Latent Representations for Few-Shot Learning of Named Entities

MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs

Semi-Supervised Natural Language Approach for Fine-Grained Classification of Medical Reports

Relationship-Aware Spatial Perception Fusion for Realistic Scene Layout Generation

Avoiding hashing and encouraging visual semantics in referential emergent language games

The Deep Learning Revolution and Its Implications for Computer Architecture and Chip Design

SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery

Drill-down: Interactive Retrieval of Complex Scenes using Natural Language Queries

Language Grounding through Social Interactions and Curiosity-Driven Multi-Goal Learning

Video Captioning with Text-based Dynamic Attention and Step-by-Step Learning

Improve variational autoEncoder with auxiliary softmax multiclassifier

You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle

Finding the most similar textual documents using Case-Based Reasoning

Modeling Feature Representations for Affective Speech using Generative Adversarial Networks

A Flexible and Adaptive Framework for Abstention Under Class Imbalance

TreeCaps: Tree-Structured Capsule Networks for Program Source Code Processing

A memory enhanced LSTM for modeling complex temporal dependencies

Gene Expression based Survival Prediction for Cancer Patients: A Topic Modeling Approach

Assisting human experts in the interpretation of their visual process: A case study on assessing copper surface adhesive potency

An Empirical Study on Post-processing Methods for Word Embeddings

Learning to Assemble Neural Module Tree Networks for Visual Grounding

Adaptive Transfer Learning of Multi-View Time Series Classification

Tell-the-difference: Fine-grained Visual Descriptor via a Discriminating Referee

Visual Natural Language Query Auto-Completion for Estimating Instance Probabilities

Referring Expression Object Segmentation with Caption-Aware Consistency

Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods

JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation

Early Prediction of 30-day ICU Re-admissions Using Natural Language Processing and Machine Learning

Developmentally motivated emergence of compositional communication via template transfer

IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification

A Hierarchical Approach for Visual Storytelling Using Image Description

SentiMATE: Learning to play Chess through Natural Language Processing

Embodied Vision-and-Language Navigation with Dynamic Convolutional Filters

Jointly Learning to Detect Emotions and Predict Facebook Reactions

Transfer Learning Robustness in Multi-Class Categorization by Fine-Tuning Pre-Trained Contextualized Language Models

CANZSL: Cycle-Consistent Adversarial Networks for Zero-Shot Learning from Natural Language

Global Autoregressive Models for Data-Efficient Sequence Learning

Large-scale representation learning from visually grounded untranscribed speech

Leveraging User Engagement Signals For Entity Labeling in a Virtual Assistant

Generating Black-Box Adversarial Examples for Text Classifiers Using a Deep Reinforced Model

Attending to Future Tokens For Bidirectional Sequence Generation

Dynamic survival prediction in intensive care units from heterogeneous time series without the need for variable selection or pre-processing

Learning to Generate Questions with Adaptive Copying Neural Networks

NeMo: a toolkit for building AI applications using Neural Modules

Computing Optimal Assignments in Linear Time for Approximate Graph Matching

Sunny and Dark Outside?! Improving Answer Consistency in VQA through Entailed Question Generation

Nearly-Unsupervised Hashcode Representations for Relation Extraction

Transformer to CNN: Label-scarce distillation for efficient text classification

LeDeepChef: Deep Reinforcement Learning Agent for Families of Text-Based Games

Model Asset eXchange: Path to Ubiquitous Deep Learning Deployment

CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text

Nemesyst: A Hybrid Parallelism Deep Learning-Based Framework Applied for Internet of Things Enabled Food Retailing Refrigeration Systems

Transfer Learning Between Related Tasks Using Expected Label Proportions

Unsupervised Construction of Knowledge Graphs From Text and Code

Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective

Transferable Representation Learning in Vision-and-Language Navigation

A Survey on Data Collection for Machine Learning: a Big Data -- AI Integration Perspective

ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks

HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips

Temporal Localization of Moments in Video Collections with Natural Language

Airbnb Price Prediction Using Machine Learning and Sentiment Analysis

Curriculum Learning in Deep Neural Networks for Financial Forecasting

EnSyth: A Pruning Approach to Synthesis of Deep Learning Ensembles

Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with Double Power-law Behavior

Graph Representation Learning via Hard and Channel-Wise Attention Networks

Creating A Neural Pedagogical Agent by Jointly Learning to Review and Assess

Open-Ended Long-Form Video Question Answering via Hierarchical Convolutional Self-Attention Networks

Encoding Database Schemas with Relation-Aware Self-Attention for Text-to-SQL Parsers

Using Intuition from Empirical Properties to Simplify Adversarial Training Defense

A Deep Decoder Structure Based on WordEmbedding Regression for An Encoder-Decoder Based Model for Image Captioning

Deep Learning in the Automotive Industry: Recent Advances and Application Examples

Neural Sign Language Translation based on Human Keypoint Estimation

One-vs-All Models for Asynchronous Training: An Empirical Analysis

A simple and effective postprocessing method for image classification

Lessons from Contextual Bandit Learning in a Customer Support Bot

Unsupervised machine learning to analyse city logistics through Twitter

A Temporal Sequence Learning for Action Recognition and Prediction

Generating Diverse and Informative Natural Language Fashion Feedback

Object-aware Aggregation with Bidirectional Temporal Graph for Video Captioning

Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing

A cost-reducing partial labeling estimator in text classification problem

Strong Black-box Adversarial Attacks on Unsupervised Machine Learning Models

Text2Scene: Generating Compositional Scenes from Textual Descriptions

Deep Learning Acceleration Techniques for Real Time Mobile Vision Applications

Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View

Context-Aware Visual Policy Network for Fine-Grained Image Captioning

Learning to Compose and Reason with Language Tree Structures for Visual Grounding

CoDraw: Collaborative Drawing as a Testbed for Grounded Goal-driven Communication

Relational Reasoning using Prior Knowledge for Visual Captioning

Transfer Learning in the Field of Renewable Energies -- A Transfer Learning Framework Providing Power Forecasts Throughout the Lifecycle of Wind Farms After Initial Connection to the Electrical Grid

Reconstruct and Represent Video Contents for Captioning via Reinforcement Learning

Perceptual Evaluation of Adversarial Attacks for CNN-based Image Classification

Using Natural Language for Reward Shaping in Reinforcement Learning

Vision-to-Language Tasks Based on Attributes and Attention Mechanism

Compositional generalization in a deep seq2seq model by separating syntax and semantics

Learning Optimal Data Augmentation Policies via Bayesian Optimization for Image Classification Tasks

Lightweight Network Architecture for Real-Time Action Recognition

Jointly Measuring Diversity and Quality in Text Generation Models

Less Memory, Faster Speed: Refining Self-Attention Module for Image Reconstruction

Multimodal Transformer with Multi-View Visual Representation for Image Captioning

Open Vocabulary Learning on Source Code with a Graph-Structured Cache

MAN: Moment Alignment Network for Natural Language Moment Retrieval via Iterative Graph Adjustment

TSXplain: Demystification of DNN Decisions for Time-Series using Natural Language and Statistical Features

FAT-DeepFFM: Field Attentive Deep Field-aware Factorization Machine

BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning

Quantifying and Alleviating the Language Prior Problem in Visual Question Answering

Mutual Information Scaling and Expressive Power of Sequence Models

Deep Closest Point: Learning Representations for Point Cloud Registration

MetaPred: Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records

Continuous Learning for Large-scale Personalized Domain Classification

Soft edit distance for differentiable comparison of symbolic sequences

Learning Semantic Vector Representations of Source Code via a Siamese Neural Network

Adversarial Attacks on Deep Neural Networks for Time Series Classification

How You Act Tells a Lot: Privacy-Leakage Attack on Deep Reinforcement Learning

Generating Token-Level Explanations for Natural Language Inference

Continual Learning for Sentence Representations Using Conceptors

Casting Light on Invisible Cities: Computationally Engaging with Literary Criticism

Interpreting and Understanding Graph Convolutional Neural Network using Gradient-based Attribution Method

Low-Rank Deep Convolutional Neural Network for Multi-Task Learning

Cross-Modal Self-Attention Network for Referring Image Segmentation

CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions

A Compendium on Network and Host based Intrusion Detection Systems

Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation

White-to-Black: Efficient Distillation of Black-Box Adversarial Attacks

Universal Rules for Fooling Deep Neural Networks based Text Classification

LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking

Cross-Modal Data Programming Enables Rapid Medical Machine Learning

Scene Understanding for Autonomous Manipulation with Deep Learning

Learning to Caption Images through a Lifetime by Asking Questions

A Weighted Multi-Criteria Decision Making Approach for Image Captioning

You Only Look & Listen Once: Towards Fast and Accurate Visual Grounding

Visual Query Answering by Entity-Attribute Graph Matching and Reasoning

GanDef: A GAN based Adversarial Training Defense for Neural Network Classifier

code2seq: Generating Sequences from Structured Representations of Code

From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following

Ain't Nobody Got Time For Coding: Structure-Aware Program Synthesis From Natural Language

ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning

Energy-Efficient Inference Accelerator for Memory-Augmented Neural Networks on an FPGA

A sequential guiding network with attention for image captioning

Understanding Composition of Word Embeddings via Tensor Decomposition

Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise

Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos

Visual Entailment: A Novel Task for Fine-Grained Image Understanding

A Noise-Sensitivity-Analysis-Based Test Prioritization Technique for Deep Neural Networks

Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing

Image Captioning Based on a Hierarchical Attention Mechanism and Policy Gradient Optimization

Hierarchical LSTMs with Adaptive Attention for Visual Captioning

A Review of Meta-Reinforcement Learning for Deep Neural Networks Architecture Search

Feature Fusion Effects of Tensor Product Representation on (De)Compositional Network for Caption Generation for Images

Deep Reader: Information extraction from Document images via relation extraction and Natural Language

Neighbourhood Watch: Referring Expression Comprehension via Language-guided Graph Attention Networks

PIRC Net : Using Proposal Indexing, Relationships and Context for Phrase Grounding

Parameter Re-Initialization through Cyclical Batch Size Schedules

Multi-modal Capsule Routing for Actor and Action Video Segmentation Conditioned on Natural Language Queries

Study and Observation of the Variations of Accuracies for Handwritten Digits Recognition with Various Hidden Layers and Epochs using Convolutional Neural Network

Neural Code Comprehension: A Learnable Representation of Code Semantics

Automatic Rendering of Building Floor Plan Images from Textual Descriptions in English

Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language

Efficient non-uniform quantizer for quantized neural network targeting reconfigurable hardware

Describe and Attend to Track: Learning Natural Language guided Structural Representation and Visual Attention for Object Tracking

Measuring Depression Symptom Severity from Spoken Language and 3D Facial Expressions

Word2Vec is a special case of Kernel Correspondence Analysis and Kernels for Natural Language Processing

Towards Easier and Faster Sequence Labeling for Natural Language Processing: A Search-based Probabilistic Online Learning Framework (SAPO)

An Introduction to Image Synthesis with Generative Adversarial Nets

Learning Unsupervised Visual Grounding Through Semantic Self-Supervision

Deep Neural Networks based Modrec: Some Results with Inter-Symbol Interference and Adversarial Examples

Unsupervised Features Extraction for Binary Similarity Using Graph Embedding Neural Networks

An Orchestrated Empirical Study on Deep Learning Frameworks and Platforms

ReSet: Learning Recurrent Dynamic Routing in ResNet-like Neural Networks

Early Prediction of Acute Kidney Injury in Critical Care Setting Using Clinical Notes

Benchmarking Deep Sequential Models on Volatility Predictions for Financial Time Series

Combining Similarity Features and Deep Representation Learning for Stance Detection in the Context of Checking Fake News

Online Embedding Compression for Text Classification using Low Rank Matrix Factorization

Learning Conditioned Graph Structures for Interpretable Visual Question Answering

Compositional Attention Networks for Interpretability in Natural Language Question Answering

Visual Re-ranking with Natural Language Understanding for Text Spotting

To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded Inference

Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality

Persistence pays off: Paying Attention to What the LSTM Gating Mechanism Persists

Beyond Narrative Description: Generating Poetry from Images by Multi-Adversarial Training

DualGAN: Unsupervised Dual Learning for Image-to-Image Translation

NICE: Noise Injection and Clamping Estimation for Neural Network Quantization

Learning to Localize and Align Fine-Grained Actions to Sparse Instructions

Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders

Mining for meaning: from vision to language through multiple networks consensus

Deep CNN Frame Interpolation with Lessons Learned from Natural Language Processing

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

Multimodal Deep Neural Networks using Both Engineered and Learned Representations for Biodegradability Prediction

IL-Net: Using Expert Knowledge to Guide the Design of Furcated Neural Networks

Improving Reinforcement Learning Based Image Captioning with Natural Language Prior

The History Began from AlexNet: A Comprehensive Survey on Deep Learning Approaches

The Wisdom of MaSSeS: Majority, Subjectivity, and Semantic Similarity in the Evaluation of VQA

SPASS: Scientific Prominence Active Search System with Deep Image Captioning Network

Natural Language Person Search Using Deep Reinforcement Learning

Seeing Colors: Learning Semantic Text Encoding for Classification

Attentive Sequence to Sequence Translation for Localizing Clips of Interest by Natural Language Descriptions

Adversarially Regularising Neural NLI Models to Integrate Logical Background Knowledge

DreamNLP: Novel NLP System for Clinical Report Metadata Extraction using Count Sketch Data Streaming Algorithm: Preliminary Results

Dynamic Self-Attention : Computing Attention over Words Dynamically for Sentence Embedding

Context-Aware Visual Policy Network for Sequence-Level Image Captioning

Grassmannian Learning: Embedding Geometry Awareness in Shallow and Deep Learning

Language Guided Fashion Image Manipulation with Feature-wise Transformations

Large Scale Language Modeling: Converging on 40GB of Text in Four Hours

Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance

Importance of the Mathematical Foundations of Machine Learning Methods for Scientific and Engineering Applications

Improving Deep Visual Representation for Person Re-identification by Global and Local Image-language Association

Learning a bidirectional mapping between human whole-body motion and natural language using deep recurrent neural networks

DeepSPINE: Automated Lumbar Vertebral Segmentation, Disc-level Designation, and Spinal Stenosis Grading Using Deep Learning

On the Flip Side: Identifying Counterexamples in Visual Question Answering

Dynamic Multimodal Instance Segmentation guided by natural language queries

What is not where: the challenge of integrating spatial representations into deep learning architectures

Time-Dependent Representation for Neural Event Sequence Prediction

The Bottleneck Simulator: A Model-based Deep Reinforcement Learning Approach

Learning The Sequential Temporal Information with Recurrent Neural Networks

YouTube for Patient Education: A Deep Learning Approach for Understanding Medical Knowledge from User-Generated Videos

Program Language Translation Using a Grammar-Driven Tree-to-Tree Model

COTA: Improving the Speed and Accuracy of Customer Support through Ranking and Deep Networks

GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations

Make (Nearly) Every Neural Network Better: Generating Neural Network Ensembles by Weight Parameter Resampling

Visualizing and Understanding Deep Neural Networks in CTR Prediction

Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations

Sparsity-based Defense against Adversarial Attacks on Linear Classifiers

Learning Distributed Representations from Reviews for Collaborative Filtering

Teaching Machines to Code: Neural Markup Generation with Visual Attention

Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval with Generative Models

Learning Visual Knowledge Memory Networks for Visual Question Answering

CS-VQA: Visual Question Answering with Compressively Sensed Images

On the Importance of Attention in Meta-Learning for Few-Shot Text Classification

Tile2Vec: Unsupervised representation learning for spatially distributed data

Unsupervised Alignment of Embeddings with Wasserstein Procrustes

Multimodal Sentiment Analysis To Explore the Structure of Emotions

Understand Functionality and Dimensionality of Vector Embeddings: the Distributional Hypothesis, the Pairwise Inner Product Loss and Its Bias-Variance Trade-off

Tree Edit Distance Learning via Adaptive Symbol Embeddings: Supplementary Materials and Results

SemStyle: Learning to Generate Stylised Image Captions using Unaligned Text

Interpretable Adversarial Perturbation in Input Embedding Space for Text

Weakly Supervised Attention Learning for Textual Phrases Grounding

Prototypical Priors: From Improving Classification to Zero-Shot Learning

Jointly Localizing and Describing Events for Dense Video Captioning

Learning Convolutional Text Representations for Visual Question Answering

Emergent Communication in a Multi-Modal, Multi-Step Referential Game

Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments

Multimodal Visual Concept Learning with Weakly Supervised Techniques

MAttNet: Modular Attention Network for Referring Expression Comprehension

Explicit Reasoning over End-to-End Neural Architectures for Visual Question Answering

Text2Shape: Generating Shapes from Natural Language by Learning Joint Embeddings

From Shannon's Channel to Semantic Channel via New Bayes' Formulas for Machine Learning

Attention-based Temporal Weighted Convolutional Neural Network for Action Recognition

Knowledge Aided Consistency for Weakly Supervised Phrase Grounding

Construction of neural networks for realization of localized deep learning

A Non-Technical Survey on Deep Convolutional Neural Network Architectures

One Single Deep Bidirectional LSTM Network for Word Sense Disambiguation of Text Data

Interactive Image Manipulation with Natural Language Instruction Commands

Node Centralities and Classification Performance for Characterizing Node Embedding Algorithms

Image Captioning at Will: A Versatile Scheme for Effectively Injecting Sentiments into Image Descriptions

A Generative Model For Zero Shot Learning Using Conditional Variational Autoencoders

Tell-and-Answer: Towards Explainable Visual Question Answering using Attributes and Captions

Describing Semantic Representations of Brain Activity Evoked by Visual Stimuli

Brenier approach for optimal transportation between a quasi-discrete measure and a discrete measure

Gated-Attention Architectures for Task-Oriented Language Grounding

Use of Deep Learning in Modern Recommendation System: A Summary of Recent Works

DarkRank: Accelerating Deep Metric Learning via Cross Sample Similarities Transfer

ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases

Counterfactual Learning from Bandit Feedback under Deterministic Logging: A Case Study in Statistical Machine Translation

Fine-Grained Object Recognition and Zero-Shot Learning in Remote Sensing Imagery

An innovative solution for breast cancer textual big data analysis

Incorporating External Knowledge to Answer Open-Domain Visual Questions with Dynamic Memory Networks

TGIF-QA: Toward Spatio-Temporal Reasoning in Visual Question Answering

AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks

Complex Structure Leads to Overfitting: A Structure Regularization Decoding Method for Natural Language Processing

Reversible Architectures for Arbitrarily Deep Residual Neural Networks

Parallel Attention: A Unified Framework for Visual Object Discovery through Dialogs and Queries

Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols

Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets

Deep learning for source camera identification on mobile devices

Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm

A Comprehensive Survey of Deep Learning in Remote Sensing: Theories, Tools and Challenges for the Community

Learning to Reason: End-to-End Module Networks for Visual Question Answering

Hierarchical Multi-scale Attention Networks for Action Recognition

One-Shot Concept Learning by Simulating Evolutionary Instinct Development

Learning to Perform Physics Experiments via Deep Reinforcement Learning

e-QRAQ: A Multi-turn Reasoning Dataset and Simulator with Explanations

Recurrent Multimodal Interaction for Referring Image Segmentation

TensorLayer: A Versatile Library for Efficient Deep Learning Development

Attentive Explanations: Justifying Decisions and Pointing to the Evidence

Health Analytics: a systematic review of approaches to detect phenotype cohorts using electronic health records

Fast Amortized Inference and Learning in Log-linear Models with Randomly Perturbed Nearest Neighbor Search

Where to Play: Retrieval of Video Segments using Natural-Language Queries

Using Artificial Tokens to Control Languages for Multilingual Image Caption Generation

Coupling Distributed and Symbolic Execution for Natural Language Queries

The "something something" video database for learning and evaluating visual common sense

Visual Question Answering: Datasets, Algorithms, and Future Challenges

A Deep Causal Inference Approach to Measuring the Effects of Forming Group Loans in Online Non-profit Microfinance Platform

Hierarchical LSTM with Adjusted Temporal Attention for Video Captioning

I2T2I: Learning Text to Image Synthesis with Textual Data Augmentation

Order embeddings and character-level convolutions for multimodal alignment

Fine-graind Image Classification via Combining Vision and Language

A Joint Speaker-Listener-Reinforcer Model for Referring Expressions

Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries

Bag-of-Words Method Applied to Accelerometer Measurements for the Purpose of Classification and Energy Estimation

Deep Reinforcement Learning-based Image Captioning with Embedding Reward

Show, Ask, Attend, and Answer: A Strong Baseline For Visual Question Answering

NIPS 2016 Workshop on Representation Learning in Artificial and Biological Neural Networks (MLINI 2016)

A Hierarchical Approach for Generating Descriptive Image Paragraphs

Learning to Predict: A Fast Re-constructive Method to Generate Multimodal Embeddings

An End-to-End Approach to Natural Language Object Retrieval via Context-Aware Deep Reinforcement Learning

Learning Cooperative Visual Dialog Agents with Deep Reinforcement Learning

Auxiliary Multimodal LSTM for Audio-visual Speech Recognition and Lipreading

Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes

Learning Deep Visual Object Models From Noisy Web Data: How to Make it Work

Visual Translation Embedding Network for Visual Relation Detection

Batch Policy Gradient Methods for Improving Neural Conversation Models

Structured Sequence Modeling with Graph Convolutional Recurrent Networks

Modeling Relationships in Referential Expressions with Compositional Modular Networks

Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation

Ask Your Neurons: A Deep Learning Approach to Visual Question Answering

Multiple Instance Learning Convolutional Neural Networks for Object Recognition

Learning Language-Visual Embedding for Movie Understanding with Natural-Language

Question Relevance in VQA: Identifying Non-Visual And False-Premise Questions

Resolving Language and Vision Ambiguities Together: Joint Segmentation & Prepositional Attachment Resolution in Captioned Scenes

The Color of the Cat is Gray: 1 Million Full-Sentences Visual Question Answering (FSVQA)

Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge

Automatic Visual Theme Discovery from Joint Image and Text Corpora

Stochastic Learning of Multi-Instance Dictionary for Earth Mover's Distance based Histogram Comparison

Learning to generalize to new compositions in image understanding

Syntactically Informed Text Compression with Recurrent Neural Networks

Learning Joint Representations of Videos and Sentences with Web Image Search

LightNet: A Versatile, Standalone Matlab-based Environment for Deep Learning

Annotation Methodologies for Vision and Language Dataset Creation

Structured Prediction: From Gaussian Perturbations to Linear-Time Principled Algorithms

Long-term Recurrent Convolutional Networks for Visual Recognition and Description

Beyond Caption To Narrative: Video Captioning With Multiple Sentences

Learning Deep Representations of Fine-grained Visual Descriptions

HARRISON: A Benchmark on HAshtag Recommendation for Real-world Images in Social Networks

Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation

Monotone Retargeting for Unsupervised Rank Aggregation with Object Features

Train and Test Tightness of LP Relaxations in Structured Prediction

Subjects and Their Objects: Localizing Interactees for a Person-Centric View of Importance

Ask Me Anything: Free-form Visual Question Answering Based on Knowledge from External Sources

Attributes as Semantic Units between Natural Language and Visual Recognition

A Subpath Kernel for Learning Hierarchical Image Representations

ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering

Do You See What I Mean? Visual Resolution of Linguistic Ambiguities

Bi-directional LSTM Recurrent Neural Network for Chinese Word Segmentation

Generate Image Descriptions based on Deep RNN and Memory Cells for Images Features

A Restricted Visual Turing Test for Deep Scene and Event Understanding

Deep Learning Algorithms with Applications to Video Analytics for A Smart City: A Survey

Explaining NonLinear Classification Decisions with Deep Taylor Decomposition

Convolutional Neural Networks over Tree Structures for Programming Language Processing

DenseCap: Fully Convolutional Localization Networks for Dense Captioning

Stories in the Eye: Contextual Visual Interactions for Efficient Video to Language Translation

Explicit Knowledge-based Reasoning for Visual Question Answering

From Images to Sentences through Scene Description Graphs using Commonsense Reasoning and Knowledge

A Critical Review of Recurrent Neural Networks for Sequence Learning

Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width

Ask Your Neurons: A Neural-based Approach to Answering Questions about Images

Segment-Phrase Table for Semantic Segmentation, Visual Entailment and Paraphrasing

Unsupervised Cross-Domain Recognition by Identifying Compact Joint Subspaces

Jointly Modeling Embedding and Translation to Bridge Video and Language

Visual Madlibs: Fill in the blank Image Generation and Question Answering

Interleaved Text/Image Deep Mining on a Large-Scale Radiology Database for Automated Image Interpretation

Translating Videos to Natural Language Using Deep Recurrent Neural Networks

Joint Learning of Distributed Representations for Images and Texts

Analysis of Stopping Active Learning based on Stabilizing Predictions

Deep Visual-Semantic Alignments for Generating Image Descriptions

Infinite Author Topic Model based on Mixed Gamma-Negative Binomial Process

Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research

Mathematical Language Processing: Automatic Grading and Feedback for Open Response Mathematical Questions

Score Function Features for Discriminative Learning: Matrix and Tensor Framework

Submodular meets Structured: Finding Diverse Subsets in Exponentially-Large Structured Item Sets

A Method for Stopping Active Learning Based on Stabilizing Predictions and the Need for User-Adjustable Stopping

Bypassing Captcha By Machine A Proof For Passing The Turing Test

Deep Fragment Embeddings for Bidirectional Image Sentence Mapping

Automatic Construction and Natural-Language Description of Nonparametric Regression Models

Exploring the power of GPU's for training Polyglot language models

Coherent Multi-Sentence Video Description with Variable Level of Detail

Factorial Hidden Markov Models for Learning Representations of Natural Language

Towards Unsupervised Learning of Temporal Relations between Events

Bidirectional Recursive Neural Networks for Token-Level Labeling with Structure

A multi-stream hmm approach to offline handwritten arabic word recognition

ClusterCluster: Parallel Markov Chain Monte Carlo for Dirichlet Process Mixtures

Object Recognition with Imperfect Perception and Redundant Description

Toric grammars: a new statistical approach to natural language modeling

Optimal Weighting of Multi-View Data with Low Dimensional Hidden States

Induction of High-level Behaviors from Problem-solving Traces using Machine Learning Tools

Combining Independent Modules in Lexical Multiple-Choice Problems

Prosody Based Co-analysis for Continuous Recognition of Coverbal Gestures

Bootstrapping Syntax and Recursion using Alignment-Based Learning

A Winnow-Based Approach to Context-Sensitive Spelling Correction

(Machine) Learning to Improve the Empirical Performance of Discrete Algorithms

Improved prediction rule ensembling through model-based data generation

Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values

Development of patients triage algorithm from nationwide COVID-19 registry data based on machine learning

Interpretable Additive Recurrent Neural Networks For Multivariate Clinical Time Series

Supervised machine learning techniques for data matching based on similarity metrics

Application of Machine Learning in Early Recommendation of Cardiac Resynchronization Therapy

Feature Importance in Gradient Boosting Trees with Cross-Validation Feature Selection

Robust Optimal Classification Trees Against Adversarial Examples

Scalable Feature Selection for (Multitask) Gradient Boosted Trees

Smart Data driven Decision Trees Ensemble Methodology for Imbalanced Big Data

Decision Tree-Based Predictive Models for Academic Achievement Using College Students' Support Networks

Learning to Synthesize Programs as Interpretable and Generalizable Policies

Survival Prediction of Heart Failure Patients using Stacked Ensemble Machine Learning Algorithm

Explainable AI for engineering design: A unified approach of systems engineering and component-based deep learning

Towards Optimally Efficient Search with Deep Learning for Large-Scale MIMO Systems

Using Graph Neural Networks to model the performance of Deep Neural Networks

Identification of the Resting Position Based on EGG, ECG, Respiration Rate and SpO2 Using Stacked Ensemble Learning

MOFit: A Framework to reduce Obesity using Machine learning and IoT

Simple is better: Making Decision Trees faster using random sampling

XtracTree: a Simple and Effective Method for Regulator Validation of Bagging Methods Used in Retail Banking

Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction

Neural-to-Tree Policy Distillation with Policy Improvement Criterion

Process parameter optimization of Friction Stir Welding on 6061AA using Supervised Machine Learning Regression-based Algorithms

On automatic extraction of on-street parking spaces using park-out events data

To Boost or not to Boost: On the Limits of Boosted Neural Networks

The Reasonable Crowd: Towards evidence-based and interpretable models of driving behavior

Fed-EINI: An Efficient and Interpretable Inference Framework for Decision Tree Ensembles in Federated Learning

Decision-forest voting scheme for classification of rare classes in network intrusion detection

GPUTreeShap: Massively Parallel Exact Calculation of SHAP Scores for Tree Ensembles

Machine Learning for Real-World Evidence Analysis of COVID-19 Pharmacotherapy

Accuracy Prediction with Non-neural Model for Neural Architecture Search

Towards a Multimodal System for Precision Agriculture using IoT and Machine Learning

Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges

Transformer-Based Behavioral Representation Learning Enables Transfer Learning for Mobile Sensing in Small Datasets

Discovering Interpretable Machine Learning Models in Parallel Coordinates

Short-term probabilistic photovoltaic power forecast based on deep convolutional long short-term memory network and kernel density estimation

Learning Gradual Argumentation Frameworks using Genetic Algorithms

Learning Linear Temporal Properties from Noisy Data: A MaxSAT Approach

Multi-Class Classification of Blood Cells -- End to End Computer Vision based diagnosis case study

Regularization is all you Need: Simple Neural Nets can Excel on Tabular Data

Model-agnostic Feature Importance and Effects with Dependent Features -- A Conditional Subgroup Approach

Designing Interpretable Approximations to Deep Reinforcement Learning

Performance Evaluation of Classification Models for Household Income, Consumption and Expenditure Data Set

Mining Interpretable Spatio-temporal Logic Properties for Spatially Distributed Systems

Improving the compromise between accuracy, interpretability and personalization of rule-based machine learning in medical problems

Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression

Making CNNs Interpretable by Building Dynamic Sequential Decision Forests with Top-down Hierarchy Learning

Automated Grading of Anatomical Objective Structured Practical Exams Using Decision Trees

MoET: Mixture of Expert Trees and its Application to Verifiable Reinforcement Learning

Analysis and classification of main risk factors causing stroke in Shanxi Province

Adaptive Threshold for Online Object Recognition and Re-identification Tasks

Symbolic regression outperforms other models for small data sets

A causal learning framework for the analysis and interpretation of COVID-19 clinical data

Performance Comparison of Different Machine Learning Algorithms on the Prediction of Wind Turbine Power Generation

MurTree: Optimal Classification Trees via Dynamic Programming and Search

Interpretable Machine Learning for COVID-19: An Empirical Study on Severity Prediction Task

The Backbone Method for Ultra-High Dimensional Sparse Machine Learning

Morphological classification of astronomical images with limited labelling

Evaluating the performance of personal, social, health-related, biomarker and genetic data for predicting an individuals future health using machine learning: A longitudinal analysis

Feature Inference Attack on Model Predictions in Vertical Federated Learning

Fuzzy Expert Systems for Prediction of ICU Admission in Patients with COVID-19

Neural Prototype Trees for Interpretable Fine-grained Image Recognition

A Vision-based System for Traffic Anomaly Detection using Deep Learning and Decision Trees

Deep imagination is a close to optimal policy for planning in large decision trees under limited resources

Sparse Oblique Decision Trees: A Tool to Understand and Manipulate Neural Net Features

Towards Interpretable-AI Policies Induction using Evolutionary Nonlinear Decision Trees for Discrete Action Systems

Multi-Atlas Based Pathological Stratification of d-TGA Congenital Heart Disease

Explainability-aided Domain Generalization for Image Classification

The Use of Binary Choice Forests to Model and Estimate Discrete Choices

Robust Neural Routing Through Space Partitions for Camera Relocalization in Dynamic Indoor Environments

Uncovering Feature Interdependencies in High-Noise Environments with Stepwise Lookahead Decision Forests

Boost then Convolve: Gradient Boosting Meets Graph Neural Networks

Human Activity Analysis and Recognition from Smartphones using Machine Learning Techniques

Leveraging a Joint of Phenotypic and Genetic Features on Cancer Patient Subgrouping

A Dynamic Battery State-of-Health Forecasting Model for Electric Trucks: Li-Ion Batteries Case-Study

CDT: Cascading Decision Trees for Explainable Reinforcement Learning

One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks

Spatio-temporal Sequence Prediction with Point Processes and Self-organizing Decision Trees

Towards Interpretable Neural Networks: An Exact Transformation to Multi-Class Multivariate Decision Trees

Boosted Genetic Algorithm using Machine Learning for traffic control optimization

Inapproximability of Minimizing a Pair of DNFs or Binary Decision Trees Defining a Partial Boolean Function

Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms

An exploration of the influence of path choice in game-theoretic attribution algorithms

Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods

Data Preprocessing to Mitigate Bias with Boosted Fair Mollifiers

Scalable and Provably Accurate Algorithms for Differentially Private Distributed Decision Tree Learning

Artificial Intelligence Enhanced Rapid and Efficient Diagnosis of Mycoplasma Pneumoniae Pneumonia in Children Patients

NuCLS: A scalable crowdsourcing, deep learning approach and dataset for nucleus classification, localization and segmentation

BEDS: Bagging ensemble deep segmentation for nucleus segmentation with testing stage stain augmentation

Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent

Connecting Interpretability and Robustness in Decision Trees through Separation

A Compositional Atlas of Tractable Circuit Operations: From Simple Transformations to Complex Information-Theoretic Queries

Machine Learning-based Classification of Active Walking Tasks in Older Adults using fNIRS

Predicting student performance using data from an auto-grading system

DoubleEnsemble: A New Ensemble Method Based on Sample Reweighting and Feature Selection for Financial Data Analysis

Decision Machines: Interpreting Decision Tree as a Model Combination Method

Automatic image annotation base on Naive Bayes and Decision Tree classifiers using MPEG-7

Convolutional Ordinal Regression Forest for Image Ordinal Estimation

Learning Temporal Causal Sequence Relationships from Real-Time Time-Series

Yet Another Representation of Binary Decision Trees: A Mathematical Demonstration

Dive into Decision Trees and Forests: A Theoretical Demonstration

Challenges in the application of a mortality prediction model for COVID-19 patients on an Indian cohort

Comparisons of Graph Neural Networks on Cancer Classification Leveraging a Joint of Phenotypic and Genetic Features

Teach me to play, gamer! Imitative learning in computer games via linguistic description of complex phenomena and decision tree

Brain Tumor Detection and Classification based on Hybrid Ensemble Classifier

Automatic Historical Feature Generation through Tree-based Method in Ads Prediction

Growing Deep Forests Efficiently with Soft Routing and Learned Connectivity

Efficient Training of Robust Decision Trees Against Adversarial Examples

Application of computer simulation results and machine learning in analysis of microwave radiothermometry data

Investigating ADR mechanisms with knowledge graph mining and explainable AI

Scientific intuition inspired by machine learning generated hypotheses

Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning

Hard-ODT: Hardware-Friendly Online Decision Tree Learning Algorithm and System

Hard and Soft EM in Bayesian Network Learning from Incomplete Data

Meta Ordinal Regression Forest For Learning with Unsure Lung Nodules

Using dynamical quantization to perform split attempts in online tree regressors

Monte Carlo Tree Search for a single target search game on a 2-D lattice

Fairness-guided SMT-based Rectification of Decision Trees and Random Forests

Explaining Conditions for Reinforcement Learning Behaviors from Real and Imagined Data

TrimTuner: Efficient Optimization of Machine Learning Jobs in the Cloud via Sub-Sampling

A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees

Estimating decision tree learnability with polylogarithmic sample complexity

An Empirical Analysis of Feature Engineering for Predictive Modeling

Learning Global Transparent Models Consistent with Local Contrastive Explanations

An Approach to Evaluating Learning Algorithms for Decision Trees

Continuous-Time Birth-Death MCMC for Bayesian Regression Tree Models

A Tensor Compiler for Unified Machine Learning Prediction Serving

Learning Patterns in Imaginary Vowels for an Intelligent Brain Computer Interface (BCI) Design

Universal guarantees for decision tree induction via a higher-order splitting criterion

Interpretable Machine Learning with an Ensemble of Gradient Boosting Machines

Decision trees as partitioning machines to characterize their generalization properties

Adaptive Deep Forest for Online Learning from Drifting Data Streams

Rare-Event Simulation for Neural Network and Random Forest Predictors

Identifying Risk of Opioid Use Disorder for Patients Taking Opioid Medications with Deep Learning

Prognosis Prediction in Covid-19 Patients from Lab Tests and X-ray Data through Randomized Decision Trees

Adversarial Attacks to Machine Learning-Based Smart Healthcare Systems

Interactive Reinforcement Learning for Feature Selection with Decision Tree in the Loop

Transparency, Auditability and eXplainability of Machine Learning Models in Credit Scoring

Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement Learning

Kaggle forecasting competitions: An overlooked learning opportunity

AutoFS: Automated Feature Selection via Diversity-aware Interactive Reinforcement Learning

An Extensive Experimental Evaluation of Automated Machine Learning Methods for Recommending Classification Algorithms (Extended Version)

Developing and Improving Risk Models using Machine-learning Based Algorithms

Enhancing the Interpretability of Deep Models in Heathcare Through Attention: Application to Glucose Forecasting for Diabetic People

A Study of the Learnability of Relational Properties: Model Counting Meets Machine Learning (MCML)

Towards Efficient and Scalable Acceleration of Online Decision Tree Learning on FPGA

An in-depth comparison of methods handling mixed-attribute data for general fuzzy min-max neural network

Automatic Radish Wilt Detection Using Image Processing Based Techniques and Machine Learning Algorithm

A Novel Multiple Ensemble Learning Models Based on Different Datasets for Software Defect Prediction

Surrogate Assisted Methods for the Parameterisation of Agent-Based Models

Tree Space Prototypes: Another Look at Making Tree Ensembles Interpretable

Evaluating Nonlinear Decision Trees for Binary Classification Tasks with Other Existing Methods

Rectified Decision Trees: Towards Interpretability, Compression and Empirical Soundness

Rectified Decision Trees: Exploring the Landscape of Interpretable and Effective Machine Learning

Evaluating Machine Learning Models for the Fast Identification of Contingency Cases

Estimating the time-lapse between medical insurance reimbursement with non-parametric regression models

A review of machine learning applications in wildfire science and management

Revisiting the Application of Feature Selection Methods to Speech Imagery BCI Datasets

Sparse Coding Driven Deep Decision Tree Ensembles for Nuclear Segmentation in Digital Pathology Images

A Decision-Theoretic Approach for Model Interpretability in Bayesian Framework

Interpretable Rule Discovery Through Bilevel Optimization of Split-Rules of Nonlinear Decision Trees for Classification Problems

Palm Vein Identification based on hybrid features selection model

Fruit classification using deep feature maps in the presence of deceptive similar classes

The Tree Ensemble Layer: Differentiability meets Conditional Computation

StructureBoost: Efficient Gradient Boosting for Structured Categorical Variables

Certifying Decision Trees Against Evasion Attacks by Program Analysis

Prediction with Spatio-temporal Point Processes with Self Organizing Decision Trees

Data-Driven Method for Enhanced Corrosion Assessment of Reinforced Concrete Structures

Handling Missing Data in Decision Trees: A Probabilistic Approach

Optimization Methods for Interpretable Differentiable Decision Trees in Reinforcement Learning

The Max-Cut Decision Tree: Improving on the Accuracy and Running Time of Decision Trees

ForestDSH: A Universal Hash Design for Discrete Probability Distributions

How fair can we go in machine learning? Assessing the boundaries of fairness in decision trees

Model family selection for classification using Neural Decision Trees

Gradient boosting machine with partially randomized decision trees

Decision Trees for Decision-Making under the Predict-then-Optimize Framework

ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification

Decision Forest: A Nonparametric Approach to Modeling Irrational Choice

Detecting and Understanding Real-World Differential Performance Bugs in Machine Learning Libraries

DETECT: A Hierarchical Clustering Algorithm for Behavioural Trends in Temporal Educational Data

Neural Additive Models: Interpretable Machine Learning with Neural Nets

A Comparative Study on Machine Learning Algorithms for the Control of a Wall Following Robot

The Best Defense Is a Good Offense: Adversarial Attacks to Avoid Modulation Detection

Feature Partitioning for Robust Tree Ensembles and their Certification in Adversarial Scenarios

Medical-based Deep Curriculum Learning for Improved Fracture Classification

A One-Class Classification Decision Tree Based on Kernel Density Estimation

An Experimental Comparison of Old and New Decision Tree Algorithms

A Numerical Transform of Random Forest Regressors corrects Systematically-Biased Predictions

Regional Tree Regularization for Interpretability in Black Box Models

Model-Agnostic Counterfactual Explanations for Consequential Decisions

Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers

Robustness for Non-Parametric Classification: A Generic Attack and Defense

A Comparative Study of Machine Learning Models for Predicting the State of Reactive Mixing

Transparent Classification with Multilayer Logical Perceptrons and Random Binarization

Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization

dtControl: Decision Tree Learning Algorithms for Controller Representation

Neural Rule Ensembles: Encoding Sparse Feature Interactions into Neural Networks

Collaborative Training of Balanced Random Forests for Open Set Domain Adaptation

Explaining the Predictions of Any Image Classifier via Decision Trees

Towards Deep Machine Reasoning: a Prototype-based Deep Neural Network with Decision Tree Inference

Black Box Explanation by Learning Image Exemplars in the Latent Feature Space

LiteMORT: A memory efficient gradient boosting tree system on adaptive compact distributions

A meta-algorithm for classification using random recursive tree ensembles: A high energy physics application

Generalization of Change-Point Detection in Time Series Data Based on Direct Density Ratio Estimation

Extracting more from boosted decision trees: A high energy physics case study

RADE: Resource-Efficient Supervised Anomaly Detection Using Decision Tree-Based Ensemble Methods

A Comparative Study on Crime in Denver City Based on Machine Learning and Data Mining

Gradient Boosting on Decision Trees for Mortality Prediction in Transcatheter Aortic Valve Implantation

Explainable outlier detection through decision tree conditioning

Customers Churn Prediction in Financial Institution Using Artificial Neural Network

Care2Vec: A Deep learning approach for the classification of self-care problems in physically disabled children

Prediction of Physical Load Level by Machine Learning Analysis of Heart Activity after Exercises

BehavDT: A Behavioral Decision Tree Learning to Build User-Centric Context-Aware Predictive Model

An AI model for Rapid and Accurate Identification of Chemical Agents in Mass Casualty Incidents

RoNGBa: A Robustly Optimized Natural Gradient Boosting Training Approach with Leaf Number Clipping

A Dynamic Modelling Framework for Human Hand Gesture Task Recognition

A Self-Adaptive Synthetic Over-Sampling Technique for Imbalanced Classification

WOTBoost: Weighted Oversampling Technique in Boosting for imbalanced learning

Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks

Distilling Black-Box Travel Mode Choice Model for Behavioral Interpretation

Predicting Louisiana Public High School Dropout through Imbalanced Learning Techniques

SLEEPER: interpretable Sleep staging via Prototypes from Expert Rules

Enhancing Decision Tree based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization

Silas: High Performance, Explainable and Verifiable Machine Learning

Scheduling optimization of parallel linear algebra algorithms using Supervised Learning

Optimal Decision Trees for the Algorithm Selection Problem: Integer Programming Based Approaches

Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data

Towards Automatic Screening of Typical and Atypical Behaviors in Children With Autism

Detecting floodwater on roadways from image data with handcrafted features and deep transfer learning

Investigation of wind pressures on tall building under interference effects using machine learning techniques

Optimizing for Interpretability in Deep Neural Networks with Tree Regularization

A real-time iterative machine learning approach for temperature profile prediction in additive manufacturing processes

Prediction of Highway Lane Changes Based on Prototype Trajectories

A discriminative approach for finding and characterizing positivity violations using decision trees

Asynch-SGBDT: Asynchronous Parallel Stochastic Gradient Boosting Decision Tree based on Parameters Server

Online Local Boosting: improving performance in online decision trees

The Quantum Version Of Classification Decision Tree Constructing Algorithm C5.0

Automatic Mass Detection in Breast Using Deep Convolutional Neural Network and SVM Classifier

Subsampling Bias and The Best-Discrepancy Systematic Cross Validation

Conservative Q-Improvement: Reinforcement Learning for an Interpretable Decision-Tree Policy

A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks

A meta-learning recommender system for hyperparameter tuning: predicting when tuning improves SVM classifiers

What is Interpretable? Using Machine Learning to Design Interpretable Decision-Support Systems

Concept Tree: High-Level Representation of Variables for More Interpretable Surrogate Decision Trees

A Novel Hyperparameter-free Approach to Decision Tree Construction that Avoids Overfitting by Design

Arterial incident duration prediction using a bi-level framework of extreme gradient-tree boosting

Integrated Neural Network and Machine Vision Approach For Leather Defect Classification

Explainable AI for Trees: From Local Explanations to Global Understanding

Wearable Sensor Data Based Human Activity Recognition using Machine Learning: A new approach

Development of a Forecasting and Warning System on the Ecological Life-Cycle of Sunn Pest

Asymmetric Impurity Functions, Class Weighting, and Optimal Splits for Binary Classification Trees

A Comparison Study of Credit Card Fraud Detection: Supervised versus Unsupervised

Visualizing the decision-making process in deep neural decision forest

Forecasting Weakly Correlated Time Series in Tasks of Electronic Commerce

Determining input variable ranges in Industry 4.0: A heuristic for estimating the domain of a real-valued function or trained regression model given an output range

STYLE-ANALYZER: fixing code style inconsistencies with interpretable unsupervised algorithms

Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making

A Novel Pixel-Averaging Technique for Extracting Training Data from a Single Image, Used in ML-Based Image Enlargement

Predicting class-imbalanced business risk using resampling, regularization, and model ensembling algorithms

A cooperative game for automated learning of elasto-plasticity knowledge graphs and models with AI-guided experimentation

On the usage of the probability integral transform to reduce the complexity of multi-way fuzzy decision trees in Big Data classification problems

Beyond the Low-Degree Algorithm: Mixtures of Subcubes and Their Applications

Hybrid Forest: A Concept Drift Aware Data Stream Mining Algorithm

Efficient Toxicity Prediction via Simple Features Using Shallow Neural Networks and Decision Trees

Adaptive Exact Learning of Decision Trees from Membership Queries

Predicting wind pressures around circular cylinders using machine learning techniques

Benchmarking and Optimization of Gradient Boosting Decision Tree Algorithms

Performance Analysis of Machine Learning Techniques to Predict Diabetes Mellitus

The Random Forest Classifier in WEKA: Discussion and New Developments for Imbalanced Data

An Automatic Interaction Detection Hybrid Model for Bankcard Response Classification

Improving the Interpretability of Deep Neural Networks with Knowledge Distillation

Image Embedding of PMU Data for Deep Learning towards Transient Disturbance Classification

Efficient logic architecture in training gradient boosting decision tree for high-performance and edge computing

Proximity Forest: An effective and scalable distance-based classifier for time series

Code Failure Prediction and Pattern Extraction using LSTM Networks

Deep Hierarchical Machine: a Flexible Divide-and-Conquer Architecture

Intersectionality: Multiple Group Fairness in Expectation Constraints

PSICA: decision trees for probabilistic subgroup identification with categorical treatments

Offline Multi-Action Policy Learning: Generalization and Optimization

Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System

Contextual Care Protocol using Neural Networks and Decision Trees

Benchmarking datasets for Anomaly-based Network Intrusion Detection: KDD CUP 99 alternatives

YASENN: Explaining Neural Networks via Partitioning Activation Sequences

Random Forests, Decision Trees, and Categorical Predictors: The "Absent Levels" Problem

Superensemble Classifier for Improving Predictions in Imbalanced Datasets

A Practical Method for Solving Contextual Bandit Problems Using Decision Trees

Grand Challenge: Real-time Destination and ETA Prediction for Maritime Traffic

Human activity recognition based on time series analysis using U-Net

Learning Neural Parsers with Deterministic Differentiable Imitation Learning

Memory-Efficient Global Refinement of Decision-Tree Ensembles and its Application to Face Alignment

Undersampling and Bagging of Decision Trees in the Analysis of Cardiorespiratory Behavior for the Prediction of Extubation Readiness in Extremely Preterm Infants

Approximation Trees: Statistical Stability in Model Distillation

Mapping Auto-context Decision Forests to Deep ConvNets for Semantic Segmentation

Determining the best classifier for predicting the value of a boolean field on a blood donor database using genetic algorithms

Disease Classification within Dermascopic Images Using features extracted by ResNet50 and classification through Deep Forest

Query-Efficient Hard-label Black-box Attack:An Optimization-based Approach

Considerations for a PAP Smear Image Analysis System with CNN Features

Generative Adversarial Image Synthesis with Decision Tree Latent Controller

Deep Decision Trees for Discriminative Dictionary Learning with Adversarial Multi-Agent Trajectories

Evaluating Hospital Case Cost Prediction Models Using Azure Machine Learning Studio

Modeling Dengue Vector Population Using Remotely Sensed Data and Machine Learning

Decision Tree Design for Classification in Crowdsourcing Systems

A Dynamic Boosted Ensemble Learning Method Based on Random Forest

A real-time warning system for rear-end collision based on random forest classifier

A Decision Tree Approach to Predicting Recidivism in Domestic Violence

EEG machine learning with Higuchi fractal dimension and Sample Entropy as features for successful detection of depression

Finding Influential Training Samples for Gradient Boosted Decision Trees

Influence of the Event Rate on Discrimination Abilities of Bankruptcy Prediction Models

Sequential Outlier Detection based on Incremental Decision Trees

A Bayesian and Machine Learning approach to estimating Influence Model parameters for IM-RO

Bridge type classification: supervised learning on a modified NBI dataset

Enhancing Multi-Class Classification of Random Forest using Random Vector Functional Neural Network and Oblique Decision Surfaces

Machine learning modeling for time series problem: Predicting flight ticket prices

Information gain ratio correction: Improving prediction with more balanced decision tree splits

Iterative Random Forests to detect predictive and stable high-order interactions

An Improved Naive Bayes Classifier-based Noise Detection Technique for Classifying User Phone Call Behavior

A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series

Real-Time Capable Micro-Doppler Signature Decomposition of Walking Human Limbs

Tree-Structured Boosting: Connections Between Gradient Boosted Stumps and Full Decision Trees

Beyond Sparsity: Tree Regularization of Deep Models for Interpretability

Fault Detection of Broken Rotor Bar in LS-PMSM Using Random Forests

The Heterogeneous Ensembles of Standard Classification Algorithms (HESCA): the Whole is Greater than the Sum of its Parts

Joint Maximum Purity Forest with Application to Image Super-Resolution

Efficient Decision Trees for Multi-class Support Vector Machines Using Entropy and Generalization Error Estimation

Reviving Threshold-Moving: a Simple Plug-in Bagging Ensemble for Binary and Multiclass Imbalanced Data

Forward Thinking: Building and Training Neural Networks One Layer at a Time

Semi-supervised Classification: Cluster and Label Approach using Particle Swarm Optimization

Explaining the Success of AdaBoost and Random Forests as Interpolating Classifiers

Identifying Similarities in Epileptic Patients for Drug Resistance Prediction

Exploiting random projections and sparsity with random forests and gradient boosting methods -- Application to multi-label and multi-output learning, random forest model compression and leveraging input sparsity

Automatic Viseme Vocabulary Construction to Enhance Continuous Lip-reading

Transition Forests: Learning Discriminative Temporal Transitions for Action Recognition and Detection

Structured Learning of Tree Potentials in CRF for Image Segmentation

An investigation into machine learning approaches for forecasting spatio-temporal demand in ride-hailing service

metboost: Exploratory regression analysis with hierarchically clustered data

Effective and Extensible Feature Extraction Method Using Genetic Algorithm-Based Frequency-Domain Feature Search for Epileptic EEG Multi-classification

Highly Efficient Hierarchical Online Nonlinear Regression Using Second Order Methods

What Can I Do Now? Guiding Users in a World of Automated Decisions

Stage 4 validation of the Satellite Image Automatic Mapper lightweight computer program for Earth observation Level 2 product generation, Part 1 Theory

To Boost or Not to Boost? On the Limits of Boosted Trees for Object Detection

Distributed Real-Time Sentiment Analysis for Big Data Social Streams

Improved Multi-Class Cost-Sensitive Boosting via Estimation of the Minimum-Risk Class

Splitting matters: how monotone transformation of predictor variables may improve the predictions of decision tree models

hi-RF: Incremental Learning Random Forest for large-scale multi-class Data Classification

FastBDT: A speed-optimized and cache-friendly implementation of stochastic gradient-boosted decision trees for multivariate classification

Predicting the future relevance of research institutions - The winning solution of the KDD Cup 2016

Performance Based Evaluation of Various Machine Learning Classification Techniques for Chronic Kidney Disease Diagnosis

Bagged Boosted Trees for Classification of Ecological Momentary Assessment Data

How is a data-driven approach better than random choice in label space division for multi-label classification?

On the boosting ability of top-down decision tree learning algorithm for multiclass classification

An evaluation of randomized machine learning methods for redundant data: Predicting short and medium-term suicide risk from administrative records and risk assessments

Predicting the direction of stock market prices using random forest

Confidence Decision Trees via Online and Active Learning for Streaming (BIG) Data

Classification of Large-Scale Fundus Image Data Sets: A Cloud-Computing Framework

Feature Selection via Binary Simultaneous Perturbation Stochastic Approximation

Decision Forests, Convolutional Networks and the Models in-Between

L1 logistic regression as a feature selection step for training stable classification trees for the prediction of severity criteria in imported malaria

X-TREPAN: a multi class regression and adapted extraction of comprehensible decision tree in artificial neural networks

Fault Diagnosis of Helical Gear Box using Large Margin K-Nearest Neighbors Classifier using Sound Signals

Turnover Prediction Of Shares using Data Mining techniques : A Case Study

A Reinforcement Learning Approach to Online Learning of Decision Trees

CO2 Forest: Improved Random Forest by Continuous Optimization of Oblique Splits

Random Forest for the Contextual Bandit Problem - extended version

A Bayesian Approach to Learning Bayesian Networks with Local Structure

A General Framework for Multi-focal Image Classification and Authentication: Application to Microscope Pollen Images

On Extreme Pruning of Random Forest Ensembles for Real-time Predictive Applications

Differentially- and non-differentially-private random decision trees

A New Intelligence Based Approach for Computer-Aided Diagnosis of Dengue Fever

Deep Distributed Random Samplings for Supervised Learning: An Alternative to Random Forests?

Evaluation of Predictive Data Mining Algorithms in Erythemato-Squamous Disease Diagnosis

Predicting Nearly As Well As the Optimal Twice Differentiable Regressor

Object Detection with Pixel Intensity Comparisons Organized in Decision Trees

Exponentially Increasing the Capacity-to-Computation Ratio for Conditional Computation in Deep Learning

Mining Recurrent Concepts in Data Streams using the Discrete Fourier Transform

Layered Logic Classifiers: Exploring the `And' and `Or' Relations

Fast Supervised Hashing with Decision Trees for High-Dimensional Data

Effects of Sampling Methods on Prediction Quality. The Case of Classifying Land Cover Using Decision Trees

Power System Parameters Forecasting Using Hilbert-Huang Transform and Machine Learning

A Hybrid Feature Selection Method to Improve Performance of a Group of Classification Algorithms

Improving Performance of a Group of Classification Algorithms Using Resampling and Feature Selection

Prediction with Missing Data via Bayesian Additive Regression Trees

A Latent Source Model for Nonparametric Time Series Classification

Knowledge Matters: Importance of Prior Information for Optimization

Predicting the Severity of Breast Masses with Data Mining Methods

Supervised Feature Selection for Diagnosis of Coronary Artery Disease Based on Genetic Algorithm

Representation, Approximation and Learning of Submodular Functions Using Low-rank Decision Trees

Extracting useful rules through improved decision tree induction using information entropy

Evaluation of a Supervised Learning Approach for Stock Market Operations

Estimating Well-Performing Bayesian Networks using Bernoulli Mixtures

A fair comparison of many max-tree computation algorithms (Extended version of the paper submitted to ISMM 2013

An Approach of Improving Students Academic Performance by using k means clustering algorithm and Decision tree

Performance Evaluation of Predictive Classifiers For Knowledge Discovery From Engineering Materials Data Sets

Isoelastic Agents and Wealth Updates in Machine Learning Markets

Performance Tuning Of J48 Algorithm For Prediction Of Soil Fertility

Chi-square Tests Driven Method for Learning the Structure of Factored MDPs

From Exact Learning to Computing Boolean Functions and Back Again

Free Energy and the Generalized Optimality Equations for Sequential Decision Making

Data Mining: A Prediction for Performance Improvement of Engineering Students using Classification

Fast approximations to structured sparse coding and applications to object classification

COMET: A Recipe for Learning and Using Large Ensembles on Massive Data

Dimension Reduction Using Rule Ensemble Machine Learning Methods: A Numerical Study of Three Ensemble Methods

IBSEAD: - A Self-Evolving Self-Obsessed Learning Algorithm for Machine Learning

Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images

Ontology-supported processing of clinical text using medical knowledge integration for multi-label classification of diagnosis coding

Hybrid Medical Image Classification Using Association Rule Mining with Decision Tree Algorithm

Fish recognition based on the combination between robust feature selection, image segmentation and geometrical parameter techniques using Artificial Neural Network and Decision Tree

Decision trees are PAC-learnable from most product distributions: a smoothed analysis

A Theory of Probabilistic Boosting, Decision Trees and Matryoshki

Data Engineering for the Analysis of Semiconductor Manufacturing Data

Scaling Up Inductive Logic Programming by Learning from Interpretations

Variational Inference for Continuous-Time Switching Dynamical Systems

Sequential Deep Learning Architectures for Anomaly Detection in Virtual Network Function Chains

Online Metro Origin-Destination Prediction via Heterogeneous Information Aggregation

TSAMT: Time-Series-Analysis-based Motion Transfer among Multiple Cameras

Graphical modelling in continuous-time: consistency guarantees and algorithms using Neural ODEs

Anomaly Detection for High-Dimensional Data Using Large Deviations Principle

Improving Time Series Classification Algorithms Using Octave-Convolutional Layers

Convolutional Shapelet Transform: A new approach for time series shapelets

Lithium-ion Battery State of Health Estimation based on Cycle Synchronization using Dynamic Time Warping

MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification

Improving the Thermal Infrared Monitoring of Volcanoes: A Deep Learning Approach for Intermittent Image Series

Vision-Guided Forecasting -- Visual Context for Multi-Horizon Time Series Forecasting

GPRInvNet: Deep Learning-Based Ground Penetrating Radar Data Inversion for Tunnel Lining

Dynamic Adaptive Spatio-temporal Graph Convolution for fMRI Modelling

Contributions to Large Scale Bayesian Inference and Adversarial Machine Learning

Well Googled is Half Done: Multimodal Forecasting of New Fashion Product Sales with Image-based Google Trends

Deep Learning with Kernel Flow Regularization for Time Series Forecasting

An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series

Causal Inference in Non-linear Time-series using Deep Networks and Knockoff Counterfactuals

Learning Predictive and Interpretable Timeseries Summaries from ICU Data

S&P 500 Stock Price Prediction Using Technical, Fundamental and Text Data

Domain-guided Machine Learning for Remotely Sensed In-Season Crop Growth Estimation

From Known to Unknown: Knowledge-guided Transformer for Time-Series Sales Forecasting in Alibaba

Online Multi-horizon Transaction Metric Estimation with Multi-modal Learning in Payment Networks

Deep Directed Information-Based Learning for Privacy-Preserving Smart Meter Data Release

DeepTimeAnomalyViz: A Tool for Visualizing and Post-processing Deep Learning Anomaly Detection Results for Industrial Time-Series

Signal Classification using Smooth Coefficients of Multiple wavelets

SFFDD: Deep Neural Network with Enriched Features for Failure Prediction with Its Application to Computer Disk Driver

Change of human mobility during COVID-19: A United States case study

Hydroelectric Generation Forecasting with Long Short Term Memory (LSTM) Based Deep Learning Model for Turkey

RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks

A Deep-Learning Based Optimization Approach to Address Stop-Skipping Strategy in Urban Rail Transit Lines

An empirical evaluation of attention-based multi-head models for improved turbofan engine remaining useful life prediction

TS-MULE: Local Interpretable Model-Agnostic Explanations for Time Series Forecast Models

Classification of multivariate weakly-labelled time-series with attention

Online learning of windmill time series using Long Short-term Cognitive Networks

Machine learning methods for modelling and analysis of time series signals in geoinformatics

Highly Scalable and Provably Accurate Classification in Poincare Balls

CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting

Periodic Freight Demand Estimation for Large-scale Tactical Planning

Anomaly Attribution of Multivariate Time Series using Counterfactual Reasoning

Instance-wise Graph-based Framework for Multivariate Time Series Forecasting

Predicting the outcome of team movements -- Player time series analysis using fuzzy and deep methods for representation learning

Variational Conditional Dependence Hidden Markov Models for Skeleton-Based Action Recognition

Modeling Systems with Machine Learning based Differential Equations

NTS-NOTEARS: Learning Nonparametric Temporal DAGs With Time-Series Data and Prior Knowledge

DAE : Discriminatory Auto-Encoder for multivariate time-series anomaly detection in air transportation

Predicting Intraoperative Hypoxemia with Joint Sequence Autoencoder Networks

Deep Personalized Glucose Level Forecasting Using Attention-based Recurrent Neural Networks

Anomaly Detection on IT Operation Series via Online Matrix Profile

Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series

Nonparametric Extrema Analysis in Time Series for Envelope Extraction, Peak Detection and Clustering

A method for estimating the entropy of time series using artificial neural network

Transformer Networks for Data Augmentation of Human Physical Activity Recognition

Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting

Anomaly Detection in Predictive Maintenance: A New Evaluation Framework for Temporal Unsupervised Anomaly Detection Algorithms

MrSQM: Fast Time Series Classification with Symbolic Representations

Accurate shape and phase averaging of time series through Dynamic Time Warping

VIbCReg: Variance-Invariance-better-Covariance Regularization for Self-Supervised Learning on Time Series

A Multi-view Multi-task Learning Framework for Multi-variate Time Series Forecasting

Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection

Time Series Prediction using Deep Learning Methods in Healthcare

Deep Particulate Matter Forecasting Model Using Correntropy-Induced Loss

TCCT: Tightly-Coupled Convolutional Transformer on Time Series Forecasting

Variational voxelwise rs-fMRI representation learning: Evaluation of sex, age, and neuropsychiatric signatures

Federated Variational Learning for Anomaly Detection in Multivariate Time Series

Feature-weighted Stacking for Nonseasonal Time Series Forecasts: A Case Study of the COVID-19 Epidemic Curves

Anonymizing Sensor Data on the Edge: A Representation Learning and Transformation Approach

Parallel Machine Learning for Forecasting the Dynamics of Complex Networks

Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress

A spatio-temporal LSTM model to forecast across multiple temporal and spatial scales

Efficient Out-of-Distribution Detection Using Latent Space of $β$-VAE for Cyber-Physical Systems

FastDTW is approximate and Generally Slower than the Algorithm it Approximates

Attention-based Neural Load Forecasting: A Dynamic Feature Selection Approach

Energy time series forecasting-Analytical and empirical assessment of conventional and machine learning models

DTWSSE: Data Augmentation with a Siamese Encoder for Time Series

DTW-Merge: A Novel Data Augmentation Technique for Time Series Classification

DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction

Deep Sequence Modeling: Development and Applications in Asset Pricing

Transformers predicting the future. Applying attention in next-frame and time series forecasting

XAI Methods for Neural Time Series Classification: A Brief Review

Construction Cost Index Forecasting: A Multi-feature Fusion Approach

Long-term series forecasting with Query Selector -- efficient model of sparse attention

Crop mapping from image time series: deep learning with multi-scale label hierarchies

Homological Time Series Analysis of Sensor Signals from Power Plants

Comparing Prophet and Deep Learning to ARIMA in Forecasting Wholesale Food Prices

Crop Classification under Varying Cloud Cover with Neural Ordinary Differential Equations

Event2Graph: Event-driven Bipartite Graph for Multivariate Time-series Anomaly Detection

Hierarchical forecasting with a top-down alignment of independent level forecasts

Time Delay Estimation of Traffic Congestion Propagation based on Transfer Entropy

Identification of Abnormal States in Videos of Ants Undergoing Social Phase Change

Charts and atlases for nonlinear data-driven models of dynamics on manifolds

IT2CFNN: An Interval Type-2 Correlation-Aware Fuzzy Neural Network to Construct Non-Separable Fuzzy Rules with Uncertain and Adaptive Shapes for Nonlinear Function Approximation

Empirical Risk Minimization for Time Series: Nonparametric Performance Bounds for Prediction

GalaxAI: Machine learning toolbox for interpretable analysis of spacecraft telemetry data

Time Series Forecasting of New Cases and New Deaths Rate for COVID-19 using Deep Learning Methods

Ensemble neuroevolution based approach for multivariate time series anomaly detection

Ensemble Augmentation for Deep Neural Networks Using 1-D Time Series Vibration Data

Model-free inference of unseen attractors: Reconstructing phase space features from a single noisy trajectory using reservoir computing

A volumetric change detection framework using UAV oblique photogrammetry - A case study of ultra-high-resolution monitoring of progressive building collapse

Local Exceptionality Detection in Time Series Using Subgroup Discovery

Layer-wise training convolutional neural networks with smaller filters for human activity recognition using wearable sensors

High dimensional Bayesian Optimization Algorithm for Complex System in Time Series

Reconstructing a dynamical system and forecasting time series by self-consistent deep learning

Recent Ice Trends in Swiss Mountain Lakes: 20-year Analysis of MODIS Imagery

PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series

An Applied Deep Learning Approach for Estimating Soybean Relative Maturity from UAV Imagery to Aid Plant Breeding Decisions

Learning who is in the market from time series: market participant discovery through adversarial calibration of multi-agent simulators

Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections

Voice2Series: Reprogramming Acoustic Models for Time Series Classification

Generative Adversarial Networks for Spatio-temporal Data: A Survey

Random vector functional link neural network based ensemble deep learning for short-term load forecasting

Otimizacao de pesos e funcoes de ativacao de redes neurais aplicadas na previsao de series temporais

Temporal Dependencies in Feature Importance for Time Series Predictions

Self-supervised Transformer for Multivariate Clinical Time-Series with Missing Values

RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting

TELESTO: A Graph Neural Network Model for Anomaly Classification in Cloud Services

Spatio-temporal graph neural networks for multi-site PV power forecasting

Snippet Policy Network for Multi-class Varied-length ECG Early Classification

Process Model Forecasting Using Time Series Analysis of Event Sequence Data

Spatio-Temporal SAR-Optical Data Fusion for Cloud Removal via a Deep Hierarchical Model

AutoML Meets Time Series Regression Design and Analysis of the AutoSeries Challenge

Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks

Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Adaptive Refined Labeling

Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series

Generative adversarial networks in time series: A survey and taxonomy

Learning Graph Structures with Transformer for Multivariate Time Series Anomaly Detection in IoT

Neural Ordinary Differential Equation Model for Evolutionary Subspace Clustering and Its Applications

Tsformer: Time series Transformer for tourism demand forecasting

Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies

High-dimensional Multivariate Time Series Forecasting in IoT Applications using Embedding Non-stationary Fuzzy Time Series

Automated data-driven approach for gap filling in the time series using evolutionary learning

Approximation Theory of Convolutional Architectures for Time Series Modelling

CLeaR: An Adaptive Continual Learning Framework for Regression Tasks

Innovations Autoencoder and its Application in One-class Anomalous Sequence Detection

An Investigation of Traffic Density Changes inside Wuhan during the COVID-19 Epidemic with GF-2 Time-Series Images

Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests

Model-free prediction of emergence of extreme events in a parametrically driven nonlinear dynamical system by Deep Learning

MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification

Learning interaction rules from multi-animal trajectories via augmented behavioral models

Smoothed Bernstein Online Aggregation for Day-Ahead Electricity Demand Forecasting

Neural Transformation Learning for Deep Anomaly Detection Beyond Images

Wasserstein GAN: Deep Generation applied on Bitcoins financial time series

Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows

Automated Label Generation for Time Series Classification with Representation Learning: Reduction of Label Cost for Training

Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Out-of-Distribution Dynamics Detection: RL-Relevant Benchmarks and Results

STR-GODEs: Spatial-Temporal-Ridership Graph ODEs for Metro Ridership Prediction

Multi-modal Affect Analysis using standardized data within subjects in the Wild

SITHCon: A neural network robust to variations in input scaling on the time dimension

Ensembles of Randomized NNs for Pattern-based Time Series Forecasting

Short-term Renewable Energy Forecasting in Greece using Prophet Decomposition and Tree-based Ensembles

Probabilistic Time Series Forecasting with Implicit Quantile Networks

Physics-informed generative neural network: an application to troposphere temperature prediction

CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation

On the Use of Time Series Kernel and Dimensionality Reduction to Identify the Acquisition of Antimicrobial Multidrug Resistance in the Intensive Care Unit

A Comparative Study of Using Spatial-Temporal Graph Convolutional Networks for Predicting Availability in Bike Sharing Schemes

MissFormer: (In-)attention-based handling of missing observations for trajectory filtering and prediction

Comparing seven methods for state-of-health time series prediction for the lithium-ion battery packs of forklifts

EVARS-GPR: EVent-triggered Augmented Refitting of Gaussian Process Regression for Seasonal Data

Early Recognition of Ball Catching Success in Clinical Trials with RNN-Based Predictive Classification

Detecting Faults during Automatic Screwdriving: A Dataset and Use Case of Anomaly Detection for Automatic Screwdriving

Low-Rank Temporal Attention-Augmented Bilinear Network for financial time-series forecasting

Randomized Neural Networks for Forecasting Time Series with Multiple Seasonality

Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface

Spatiotemporal convolutional network for time-series prediction and causal inference

Clustering of Time Series Data with Prior Geographical Information

Estimating the electrical power output of industrial devices with end-to-end time-series classification in the presence of label noise

Comparison of end-to-end neural network architectures and data augmentation methods for automatic infant motility assessment using wearable sensors

An Empirical Survey of Data Augmentation for Time Series Classification with Neural Networks

As easy as APC: Leveraging self-supervised learning in the context of time series classification with varying levels of sparsity and severe class imbalance

Temporal Cluster Matching for Change Detection of Structures from Satellite Imagery

Spatio-Temporal Graph Convolution for Resting-State fMRI Analysis

Improved Prediction and Network Estimation Using the Monotone Single Index Multi-variate Autoregressive Model

FallDeF5: A Fall Detection Framework Using 5G-based Deep Gated Recurrent Unit Networks

False Negative Reduction in Video Instance Segmentation using Uncertainty Estimates

On a novel training algorithm for sequence-to-sequence predictive recurrent networks

Time-Series Representation Learning via Temporal and Contextual Contrasting

Automated Evolutionary Approach for the Design of Composite Machine Learning Pipelines

Accelerating Recurrent Neural Networks for Gravitational Wave Experiments

Functional Classwise Principal Component Analysis: A Novel Classification Framework

Stochastic Recurrent Neural Network for Multistep Time Series Forecasting

Bayesian Inference in High-Dimensional Time-Serieswith the Orthogonal Stochastic Linear Mixing Model

An Empirical Study of Graph-Based Approaches for Semi-Supervised Time Series Classification

Instance-based Counterfactual Explanations for Time Series Classification

Beyond Predictions in Neural ODEs: Identification and Interventions

Residual Networks as Flows of Velocity Fields for Diffeomorphic Time Series Alignment

Including Sparse Production Knowledge into Variational Autoencoders to Increase Anomaly Detection Reliability

Serial-EMD: Fast Empirical Mode Decomposition Method for Multi-dimensional Signals Based on Serialization

Attention-based Neural Network for Driving Environment Complexity Perception

Fast and Robust Online Inference with Stochastic Gradient Descent via Random Scaling

Neural Controlled Differential Equations for Online Prediction Tasks

Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time Series

Attention to Warp: Deep Metric Learning for Multivariate Time Series

A Multilayered Block Network Model to Forecast Large Dynamic Transportation Graphs: an Application to US Air Transport

On the benefits of maximum likelihood estimation for Regression and Forecasting

Combining Pseudo-Point and State Space Approximations for Sum-Separable Gaussian Processes

GAN for time series prediction, data assimilation and uncertainty quantification

FinGAT: Financial Graph Attention Networks for Recommending Top-K Profitable Stocks

Concurrent Neural Network : A model of competition between times series

ScoreGrad: Multivariate Probabilistic Time Series Forecasting with Continuous Energy-based Generative Models

Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection

Multi-Modal Prototype Learning for Interpretable Multivariable Time Series Classification

Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA

Time Series is a Special Sequence: Forecasting with Sample Convolution and Interaction

Time Series Domain Adaptation via Sparse Associative Structure Alignment

Adaptive Visibility Graph Neural Network and its Application in Modulation Classification

Adversarial Attacks on Deep Models for Financial Transaction Records

Time Series Anomaly Detection for Cyber-physical Systems via Neural System Identification and Bayesian Filtering

How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time series

Domain Adaptation for Time Series Forecasting via Attention Sharing

A Self-Supervised Framework for Function Learning and Extrapolation

Graph Neural Network-Based Anomaly Detection in Multivariate Time Series

Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps

BRAIN2DEPTH: Lightweight CNN Model for Classification of Cognitive States from EEG Recordings

Signal Transformer: Complex-valued Attention and Meta-Learning for Signal Recognition

WAX-ML: A Python library for machine learning and feedback loops on streaming data

GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data

A Knowledge Distillation Ensemble Framework for Predicting Short and Long-term Hospitalisation Outcomes from Electronic Health Records Data

Conditional and Adversarial Euler-based Generators For Time Series

HIFI: Anomaly Detection for Multivariate Time Series with High-order Feature Interactions

Variance Reduced Training with Stratified Sampling for Forecasting Models

Hierarchical Probabilistic Model for Blind Source Separation via Legendre Transformation

Distributed Learning and its Application for Time-Series Prediction

RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting

Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties

Machine Learning Framework for Sensing and Modeling Interference in IoT Frequency Bands

Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features

Neighborhood Contrastive Learning Applied to Online Patient Monitoring

Generating Reliable Process Event Streams and Time Series Data based on Neural Networks

Multistep Electric Vehicle Charging Station Occupancy Prediction using Mixed LSTM Neural Networks

Towards Deep Industrial Transfer Learning for Anomaly Detection on Time Series Data

Uncovering Closed-form Governing Equations of Nonlinear Dynamics from Videos

Time-series Imputation of Temporally-occluded Multiagent Trajectories

Manifold Topology Divergence: a Framework for Comparing Data Manifolds

DMIDAS: Deep Mixed Data Sampling Regression for Long Multi-Horizon Time Series Forecasting

When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting

Multi-Time Attention Networks for Irregularly Sampled Time Series

Evaluation of deep learning models for multi-step ahead time series prediction

Inferring Granger Causality from Irregularly Sampled Time Series

Streaming Linear System Identification with Reverse Experience Replay

High-Performance FPGA-based Accelerator for Bayesian Recurrent Neural Networks

Deep Switching State Space Model (DS$^3$M) for Nonlinear Time Series Forecasting with Regime Switching

Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems

Early Abandoning and Pruning for Elastic Distances including Dynamic Time Warping

Warming-up recurrent neural networks to maximize reachable multi-stability greatly improves learning

Leveraging Pre-Images to Discover Nonlinear Relationships in Multivariate Environments

Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding

MTHetGNN: A Heterogeneous Graph Embedding Framework for Multivariate Time Series Forecasting

Fast, Accurate and Interpretable Time Series Classification Through Randomization

The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization

Rethinking the constraints of multimodal fusion: case study in Weakly-Supervised Audio-Visual Video Parsing

A Renormalization Group Approach to Connect Discrete- and Continuous-Time Descriptions of Gaussian Processes

Recovery of Future Data via Convolution Nuclear Norm Minimization

Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network

Targeted stochastic gradient Markov chain Monte Carlo for hidden Markov models with rare latent states

Semantics-aware Adaptive Knowledge Distillation for Sensor-to-Vision Action Recognition

Pay Attention to Evolution: Time Series Forecasting with Deep Graph-Evolution Learning

Operator Autoencoders: Learning Physical Operations on Encoded Molecular Graphs

Non-Compression Auto-Encoder for Detecting Road Surface Abnormality via Vehicle Driving Noise

Joint learning of multiple Granger causal networks via non-convex regularizations: Inference of group-level brain connectivity

Monte Carlo Filtering Objectives: A New Family of Variational Objectives to Learn Generative Model and Neural Adaptive Proposal for Time Series

Benchmarking Energy-Conserving Neural Networks for Learning Dynamics from Data

The Neural Moving Average Model for Scalable Variational Inference of State Space Models

ASM2TV: An Adaptive Semi-Supervised Multi-Task Multi-View Learning Framework

Historical Inertia: A Neglected but Powerful Baseline for Long Sequence Time-series Forecasting

Stacking VAE with Graph Neural Networks for Effective and Interpretable Time Series Anomaly Detection

Temporal Prediction and Evaluation of Brassica Growth in the Field using Conditional Generative Adversarial Networks

Towards an Automatic Analysis of CHO-K1 Suspension Growth in Microfluidic Single-cell Cultivation

Towards Synthetic Multivariate Time Series Generation for Flare Forecasting

Explainable Machine Learning-driven Strategy for Automated Trading Pattern Extraction

A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting

Leveraging Multiple Relations for Fashion Trend Forecasting Based on Social Media

PSEUDo: Interactive Pattern Search in Multivariate Time Series with Locality-Sensitive Hashing and Relevance Feedback

Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting

The effects of regularisation on RNN models for time series forecasting: Covid-19 as an example

The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification

Learn to Predict Vertical Track Irregularity with Extremely Imbalanced Data

Using Spatio-temporal Deep Learning for Forecasting Demand and Supply-demand Gap in Ride-hailing System with Anonymized Spatial Adjacency Information

Apply Artificial Neural Network to Solving Manpower Scheduling Problem

Conditional Mutual information-based Contrastive Loss for Financial Time Series Forecasting

Deep-Learning Estimation of Band Gap with the Reading-Periodic-Table Method and Periodic Convolution Layer

Improving Neural Networks for Time Series Forecasting using Data Augmentation and AutoML

Identifying Latent Stochastic Differential Equations with Variational Auto-Encoders

Learning Representative Temporal Features for Action Recognition

Parameter Estimation with Dense and Convolutional Neural Networks Applied to the FitzHugh-Nagumo ODE

SALAD: Self-Adaptive Lightweight Anomaly Detection for Real-time Recurrent Time Series

Lossless compression with state space models using bits back coding

Out-of-distribution Detection and Generation using Soft Brownian Offset Sampling and Autoencoders

All-Clear Flare Prediction Using Interval-based Time Series Classifiers

Context-aware demand prediction in bike sharing systems: incorporating spatial, meteorological and calendrical context

Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series

A machine learning approach for forecasting hierarchical time series

TE-ESN: Time Encoding Echo State Network for Prediction Based on Irregularly Sampled Time Series Data

Dynamic Slate Recommendation with Gated Recurrent Units and Thompson Sampling

Low-Rank Autoregressive Tensor Completion for Spatiotemporal Traffic Data Imputation

Learning in Feedforward Neural Networks Accelerated by Transfer Entropy

Learning Continuous-Time Dynamics by Stochastic Differential Networks

Dynamical prediction of two meteorological factors using the deep neural network and the long short-term memory $(2)$

Phenotyping OSA: a time series analysis using fuzzy clustering and persistent homology

Predicting traffic signals on transportation networks using spatio-temporal correlations on graphs

tsrobprep -- an R package for robust preprocessing of time series data

Generative modeling of spatio-temporal weather patterns with extreme event conditioning

Stochastic Online Convex Optimization; Application to probabilistic time series forecasting

Tracking agitation in people living with dementia in a care environment

Inductive Predictions of Extreme Hydrologic Events in The Wabash River Watershed

Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx

Developing an Unsupervised Real-time Anomaly Detection Scheme for Time Series with Multi-seasonality

Time Series Forecasting via Learning Convolutionally Low-Rank Models

A study on Ensemble Learning for Time Series Forecasting and the need for Meta-Learning

Sequential convolutional network for behavioral pattern extraction in gait recognition

Bayesian Neural Architecture Search using A Training-Free Performance Metric

Survey on Modeling Intensity Function of Hawkes Process Using Neural Models

Enhancing predictive skills in physically-consistent way: Physics Informed Machine Learning for Hydrological Processes

A Joint Model for IT Operation Series Prediction and Anomaly Detection

Principal Component Density Estimation for Scenario Generation Using Normalizing Flows

"Train one, Classify one, Teach one" -- Cross-surgery transfer learning for surgical step recognition

Discrete Graph Structure Learning for Forecasting Multiple Time Series

A windowed correlation based feature selection method to improve time series prediction of dengue fever cases

Forecasting The JSE Top 40 Using Long Short-Term Memory Networks

Deep Transformer Networks for Time Series Classification: The NPP Safety Case

Soft and subspace robust multivariate rank tests based on entropy regularized optimal transport

Recursive input and state estimation: A general framework for learning from time series with missing data

Exploring grid topology reconfiguration using a simple deep reinforcement learning approach

Adversarial autoencoders and adversarial LSTM for improved forecasts of urban air pollution simulations

Integrating Domain Knowledge in Data-driven Earth Observation with Process Convolutions

Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering

Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Data

Probabilistic water demand forecasting using quantile regression algorithms

Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity

HIVE-COTE 2.0: a new meta ensemble for time series classification

An Empirical Framework for Domain Generalization in Clinical Settings

VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance

Forecasting COVID-19 Counts At A Single Hospital: A Hierarchical Bayesian Approach

Meaningful Adversarial Stickers for Face Recognition in Physical World

LioNets: A Neural-Specific Local Interpretation Technique Exploiting Penultimate Layer Information

Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation

Self-supervised pre-training enhances change detection in Sentinel-2 imagery

Probabilistic Time Series Forecasting with Structured Shape and Temporal Diversity

DeepSITH: Efficient Learning via Decomposition of What and When Across Time Scales

Granger Causality Based Hierarchical Time Series Clustering for State Estimation

An Experimental Review on Deep Learning Architectures for Time Series Forecasting

CARRNN: A Continuous Autoregressive Recurrent Neural Network for Deep Representation Learning from Sporadic Temporal Data

Autoencoder-based Representation Learning from Heterogeneous Multivariate Time Series Data of Mechatronic Systems

In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness

Evaluation of Time Series Forecasting Models for Estimation of PM2.5 Levels in Air

Towards a Rigorous Evaluation of Explainability for Multivariate Time Series

N-BEATS neural network for mid-term electricity load forecasting

Surfacing Estimation Uncertainty in the Decay Parameters of Hawkes Processes with Exponential Kernels

Time Series Imaging for Link Layer Anomaly Classification in Wireless Networks

Learnable Dynamic Temporal Pooling for Time Series Classification

A Survey on Semi-parametric Machine Learning Technique for Time Series Forecasting

Model Selection for Time Series Forecasting: Empirical Analysis of Different Estimators

RLAD: Time Series Anomaly Detection through Reinforcement Learning and Active Learning

A clustering approach to time series forecasting using neural networks: A comparative study on distance-based vs. feature-based clustering methods

Tensor-Train Networks for Learning Predictive Modeling of Multidimensional Data

Prediction of Landfall Intensity, Location, and Time of a Tropical Cyclone

Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting

Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation

COVID-19 mortality analysis from soft-data multivariate curve regression and machine learning

Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality

Deep EHR Spotlight: a Framework and Mechanism to Highlight Events in Electronic Health Records for Explainable Predictions

A semi-supervised autoencoder framework for joint generation and classification of breathing

Early Classification of Time Series. Cost-based Optimization Criterion and Algorithms

Reframing demand forecasting: a two-fold approach for lumpy and intermittent demand

RV-FuseNet: Range View Based Fusion of Time-Series LiDAR Data for Joint 3D Object Detection and Motion Forecasting

Super ensemble learning for daily streamflow forecasting: Large-scale demonstration and comparison with multiple machine learning algorithms

Parallel Extraction of Long-term Trends and Short-term Fluctuation Framework for Multivariate Time Series Forecasting

Handling Missing Observations with an RNN-based Prediction-Update Cycle

Graph Attention Recurrent Neural Networks for Correlated Time Series Forecasting -- Full version

Joint Parameter Discovery and Generative Modeling of Dynamic Systems

Integrating Physiological Time Series and Clinical Notes with Deep Learning for Improved ICU Mortality Prediction

Understanding the Robustness of Skeleton-based Action Recognition under Adversarial Attack

An Efficient Method for the Classification of Croplands in Scarce-Label Regions

Feature space approximation for kernel-based supervised learning

Efficient Variational Bayesian Structure Learning of Dynamic Graphical Models

Robust Optimization and Validation of Echo State Networks for learning chaotic dynamics

Interpretable Feature Construction for Time Series Extrinsic Regression

Modeling and forecasting Spread of COVID-19 epidemic in Iran until Sep 22, 2021, based on deep learning

Bayesian Temporal Factorization for Multidimensional Time Series Prediction

Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting

Spatiotemporal Tensor Completion for Improved Urban Traffic Imputation

Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies

Affect2MM: Affective Analysis of Multimedia Content Using Emotion Causality

A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping

Determinantal Point Processes Implicitly Regularize Semi-parametric Regression Problems

Classification and Feature Transformation with Fuzzy Cognitive Maps

Depth Evaluation for Metal Surface Defects by Eddy Current Testing using Deep Residual Convolutional Neural Networks

RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicity Detection

Systematic Generalization in Neural Networks-based Multivariate Time Series Forecasting Models

LSTMs and Deep Residual Networks for Carbohydrate and Bolus Recommendations in Type 1 Diabetes Management

District Wise Price Forecasting of Wheat in Pakistan using Deep Learning

Time Series Change Point Detection with Self-Supervised Contrastive Predictive Coding

Transfer Learning for Clinical Time Series Analysis using Deep Neural Networks

Data-driven Prognostics with Predictive Uncertainty Estimation using Ensemble of Deep Ordinal Regression Models

Rethinking Recurrent Neural Networks and Other Improvements for Image Classification

Contrastive learning of strong-mixing continuous-time stochastic processes

MALI: A memory efficient and reverse accurate integrator for Neural ODEs

Scalable Learning With a Structural Recurrent Neural Network for Short-Term Traffic Prediction

Deep Neural Dynamic Bayesian Networks applied to EEG sleep spindles modeling

LiDAR-based Recurrent 3D Semantic Segmentation with Temporal Memory Alignment

Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series

Adjusting for Autocorrelated Errors in Neural Networks for Time Series Regression and Forecasting

Physical Activity Recognition Based on a Parallel Approach for an Ensemble of Machine Learning and Deep Learning Classifiers

Automatic Stockpile Volume Monitoring using Multi-view Stereo from SkySat Imagery

CLPVG: Circular limited penetrable visibility graph as a new network model for time series

Beyond Convolutions: A Novel Deep Learning Approach for Raw Seismic Data Ingestion

Variational inference formulation for a model-free simulation of a dynamical system with unknown parameters by a recurrent neural network

Temporal signals to images: Monitoring the condition of industrial assets with deep learning image processing algorithms

Independent Innovation Analysis for Nonlinear Vector Autoregressive Process

A Comparative Study of Gamma Markov Chains for Temporal Non-Negative Matrix Factorization

Time-Series Imputation with Wasserstein Interpolation for Optimal Look-Ahead-Bias and Variance Tradeoff

Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series

Partially Hidden Markov Chain Linear Autoregressive model: inference and forecasting

Similarity measure for sparse time course data based on Gaussian processes

Generating Long-term Continuous Multi-type Generation Profiles using Generative Adversarial Network

Estimation of Continuous Blood Pressure from PPG via a Federated Learning Approach

Benchmarking time series classification -- Functional data vs machine learning approaches

Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior

Phase Space Reconstruction Network for Lane Intrusion Action Recognition

Delhi air quality prediction using LSTM deep learning models with a focus on COVID-19 lockdown

nTreeClus: a Tree-based Sequence Encoder for Clustering Categorical Series

Elastic Similarity Measures for Multivariate Time Series Classification

Joint Characterization of Multiscale Information in High Dimensional Data

On model selection for scalable time series forecasting in transport networks

Echo State Networks trained by Tikhonov least squares are L2(μ) approximators of ergodic dynamical systems

Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning

Unsupervised Clustering of Time Series Signals using Neuromorphic Energy-Efficient Temporal Neural Networks

Deep Learning Approaches for Forecasting Strawberry Yields and Prices Using Satellite Images and Station-Based Soil Parameters

Robust Domain-Free Domain Generalization with Class-aware Alignment

On the Post-hoc Explainability of Deep Echo State Networks for Time Series Forecasting, Image and Video Classification

Robust Factorization of Real-world Tensor Streams with Patterns, Missing Values, and Outliers

Adaptive Weighting Scheme for Automatic Time-Series Data Augmentation

Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural Networks

Proofs and additional experiments on Second order techniques for learning time-series with structural breaks

Geometric feature performance under downsampling for EEG classification tasks

How Far Should We Look Back to Achieve Effective Real-Time Time-Series Anomaly Detection?

Rethinking 1D-CNN for Time Series Classification: A Stronger Baseline

Challenges and approaches to time-series forecasting in data center telemetry: A Survey

Feature Selection for Multivariate Time Series via Network Pruning

Comparative Analysis of Machine Learning Approaches to Analyze and Predict the Covid-19 Outbreak

PatchX: Explaining Deep Models by Intelligible Pattern Patches for Time-series Classification

Causal Inference for Time series Analysis: Problems, Methods and Evaluation

Anomaly Detection through Transfer Learning in Agriculture and Manufacturing IoT Systems

Self-supervised learning for fast and scalable time series hyper-parameter tuning

Change Point Detection in Time Series Data using Autoencoders with a Time-Invariant Representation

Forecasting Nonnegative Time Series via Sliding Mask Method (SMM) and Latent Clustered Forecast (LCF)

Attentive Gaussian processes for probabilistic time-series generation

Meta-Learning for Koopman Spectral Analysis with Short Time-series

Plotting time: On the usage of CNNs for time series classification

Few-shot time series segmentation using prototype-defined infinite hidden Markov models

A Generalised Signature Method for Multivariate Time Series Feature Extraction

Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting

Anomaly Detection of Time Series with Smoothness-Inducing Sequential Variational Auto-Encoder

Online tensor factorization and CP-dictionary learning for Markovian data

Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting

Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting

AGSTN: Learning Attention-adjusted Graph Spatio-Temporal Networks for Short-term Urban Sensor Value Forecasting

Functional Time Series Forecasting: Functional Singular Spectrum Analysis Approaches

Short-term prediction of Time Series based on bounding techniques

A fast algorithm for complex discord searches in time series: HOT SAX Time

An Optimal Reduction of TV-Denoising to Adaptive Online Learning

Multi-view Integration Learning for Irregularly-sampled Clinical Time Series

Temporal Latent Auto-Encoder: A Method for Probabilistic Multivariate Time Series Forecasting

VConstruct: Filling Gaps in Chl-a Data Using a Variational Autoencoder

Optimizing Convergence for Iterative Learning of ARIMA for Stationary Time Series

Short-term daily precipitation forecasting with seasonally-integrated autoencoder

Where does the Stimulus go? Deep Generative Model for Commercial Banking Deposits

Graphical Models for Financial Time Series and Portfolio Selection

DyLoc: Dynamic Localization for Massive MIMO Using Predictive Recurrent Neural Networks

Forecasting adverse surgical events using self-supervised transfer learning for physiological signals

Indoor environment data time-series reconstruction using autoencoder neural networks

Ensemble manifold based regularized multi-modal graph convolutional network for cognitive ability prediction

TC-DTW: Accelerating Multivariate Dynamic Time Warping Through Triangle Inequality and Point Clustering

Interpretable Models for Granger Causality Using Self-explaining Neural Networks

Optimizing Hyperparameters in CNNs using Bilevel Programming in Time Series Data

Free congruence: an exploration of expanded similarity measures for time series data

Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions

A General Framework for Hypercomplex-valued Extreme Learning Machines

A Deep Learning Based Ternary Task Classification System Using Gramian Angular Summation Field in fNIRS Neuroimaging Data

Physics-aware, probabilistic model order reduction with guaranteed stability

Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows

Time series classification for predictive maintenance on event logs

Untargeted, Targeted and Universal Adversarial Attacks and Defenses on Time Series

Behavioral Model Inference of Black-box Software using Deep Neural Networks

Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data with Spatial Information

Deep Neural Networks to Recover Unknown Physical Parameters from Oscillating Time Series

Hierarchical Clustering using Auto-encoded Compact Representation for Time-series Analysis

Condition Assessment of Stay Cables through Enhanced Time Series Classification Using a Deep Learning Approach

Time-Series Regeneration with Convolutional Recurrent Generative Adversarial Network for Remaining Useful Life Estimation

NVAE-GAN Based Approach for Unsupervised Time Series Anomaly Detection

Demand Forecasting for Platelet Usage: from Univariate Time Series to Multivariate Models

Do We Really Need Deep Learning Models for Time Series Forecasting?

The data synergy effects of time-series deep learning models in hydrology

Large-Scale Extended Granger Causality for Classification of Marijuana Users From Functional MRI

A Survey on Principles, Models and Methods for Learning from Irregularly Sampled Time Series

Multi-Sample Online Learning for Probabilistic Spiking Neural Networks

RTFN: A Robust Temporal Feature Network for Time Series Classification

General Domain Adaptation Through Proportional Progressive Pseudo Labeling

Uncovering differential equations from data with hidden variables

Towards Automated Satellite Conjunction Management with Bayesian Deep Learning

Recurrent Neural Networks for Time Series Forecasting: Current Status and Future Directions

Multi-Faceted Representation Learning with Hybrid Architecture for Time Series Classification

Use Short Isometric Shapelets to Accelerate Binary Time Series Classification

A Performance-Explainability Framework to Benchmark Machine Learning Methods: Application to Multivariate Time Series Classifiers

SAFCAR: Structured Attention Fusion for Compositional Action Recognition

XEM: An Explainable Ensemble Method for Multivariate Time Series Classification

Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection

Series Saliency: Temporal Interpretation for Multivariate Time Series Forecasting

Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data

Analysing the Direction of Emotional Influence in Nonverbal Dyadic Communication: A Facial-Expression Study

Detection of Anomalies in a Time Series Data using InfluxDB and Python

Anomaly Detection and Localization based on Double Kernelized Scoring and Matrix Kernels

FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting

Meta-learning framework with applications to zero-shot time-series forecasting

Building Deep Learning Models to Predict Mortality in ICU Patients

Neural Dynamic Mode Decomposition for End-to-End Modeling of Nonlinear Dynamics

A Review of Hidden Markov Models and Recurrent Neural Networks for Event Detection and Localization in Biomedical Signals

Large Non-Stationary Noisy Covariance Matrices: A Cross-Validation Approach

XCM: An Explainable Convolutional Neural Network for Multivariate Time Series Classification

Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification

A Transformer-based Framework for Multivariate Time Series Representation Learning

An Expectation-Based Network Scan Statistic for a COVID-19 Early Warning System

Graph-based Reinforcement Learning for Active Learning in Real Time: An Application in Modeling River Networks

An Empirical Study of Explainable AI Techniques on Deep Learning Models For Time Series Tasks

An autoencoder wavelet based deep neural network with attention mechanism for multistep prediction of plant growth

Structural Forecasting for Tropical Cyclone Intensity Prediction: Providing Insight with Deep Learning

Randomized kernels for large scale Earth observation applications

Central object segmentation by deep learning for fruits and other roundish objects

LandCoverNet: A global benchmark land cover classification training dataset

Learning summary features of time series for likelihood free inference

Learning Long-Term Dependencies in Irregularly-Sampled Time Series

Mixture Density Conditional Generative Adversarial Network Models (MD-CGAN)

Efficient implementations of echo state network cross-validation

Mixed pooling of seasonality for time series forecasting: An application to pallet transport data

Time2Graph: Revisiting Time Series Modeling with Dynamic Shapelets

Self-Supervised Time Series Representation Learning by Inter-Intra Relational Reasoning

Unsupervised learning for economic risk evaluation in the context of Covid-19 pandemic

4D Human Body Capture from Egocentric Video via 3D Scene Grounding

Improving Clinical Outcome Predictions Using Convolution over Medical Entities with Multimodal Learning

Explainable Tensorized Neural Ordinary Differential Equations forArbitrary-step Time Series Prediction

Backpropagation-Free Learning Method for Correlated Fuzzy Neural Networks

A Non-linear Function-on-Function Model for Regression with Time Series Data

Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting

Remaining Useful Life Estimation Under Uncertainty with Causal GraphNets

Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns To Attend To Important Variables As Well As Informative Time Intervals

Central and Non-central Limit Theorems arising from the Scattering Transform and its Neural Activation Generalization

A Worrying Analysis of Probabilistic Time-series Models for Sales Forecasting

Correlative Channel-Aware Fusion for Multi-View Time Series Classification

Combining Deep Transfer Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification

Visual Forecasting of Time Series with Image-to-Image Regression

A Time-Frequency based Suspicious Activity Detection for Anti-Money Laundering

Phenotyping Clusters of Patient Trajectories suffering from Chronic Complex Disease

Large-scale kernelized GRANGER causality to infer topology of directed graphs with applications to brain networks

Spatiotemporal Adaptive Neural Network for Long-term Forecasting of Financial Time Series

Discovering long term dependencies in noisy time series data using deep learning

TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks

Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series

Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks

Energy consumption forecasting using a stacked nonparametric Bayesian approach

Personality-Driven Gaze Animation with Conditional Generative Adversarial Networks

Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data

Forecasting Emergency Department Capacity Constraints for COVID Isolation Beds

ConFuse: Convolutional Transform Learning Fusion Framework For Multi-Channel Data Analysis

The quantization error in a Self-Organizing Map as a contrast and colour specific indicator of single-pixel change in large random patterns

Neural Controlled Differential Equations for Irregular Time Series

A Tree-structure Convolutional Neural Network for Temporal Features Exaction on Sensor-based Multi-resident Activity Recognition

S3-Net: A Fast and Lightweight Video Scene Understanding Network by Single-shot Segmentation

Time Series Forecasting with Stacked Long Short-Term Memory Networks

A Lane-Changing Prediction Method Based on Temporal Convolution Network

Smart Anomaly Detection in Sensor Systems: A Multi-Perspective Review

Industrial Forecasting with Exponentially Smoothed Recurrent Neural Networks

Self-awareness in intelligent vehicles: Feature based dynamic Bayesian models for abnormality detection

What went wrong and when? Instance-wise Feature Importance for Time-series Models

Temporal Knowledge Graph Embedding Model based on Additive Time Series Decomposition

Collective Awareness for Abnormality Detection in Connected Autonomous Vehicles

An Adversarial Domain Separation Framework for Septic Shock Early Prediction Across EHR Systems

Benchmarking Deep Learning Interpretability in Time Series Predictions

Peak Detection On Data Independent Acquisition Mass Spectrometry Data With Semisupervised Convolutional Transformers

Spatiotemporal Attention for Multivariate Time Series Prediction and Interpretation

A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series Data

Self-attention for raw optical Satellite Time Series Classification

Change point detection for graphical models in the presence of missing values

Prediction of Rainfall in Rajasthan, India using Deep and Wide Neural Network

VLSTM: Very Long Short-Term Memory Networks for High-Frequency Trading

Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health Episodes

Predicting Human Decision Making in Psychological Tasks with Recurrent Neural Networks

Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting

COT-GAN: Generating Sequential Data via Causal Optimal Transport

Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability

Reservoir Computing meets Recurrent Kernels and Structured Transforms

A novel method of fuzzy time series forecasting based on interval index number and membership value using support vector machine

RDIS: Random Drop Imputation with Self-Training for Incomplete Time Series Data

Monash University, UEA, UCR Time Series Extrinsic Regression Archive

Neural Additive Vector Autoregression Models for Causal Discovery in Time Series Data

A Spatial-Temporal Graph Based Hybrid Infectious Disease Model with Application to COVID-19

Deep Latent Variable Model for Learning Longitudinal Multi-view Data

Neural Ordinary Differential Equations for Intervention Modeling

Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series

Approaches and Applications of Early Classification of Time Series: A Review

Predicting Parkinson's Disease with Multimodal Irregularly Collected Longitudinal Smartphone Data

CRATOS: Cognition of Reliable Algorithm for Time-series Optimal Solution

Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping

Forecasting Photovoltaic Power Production using a Deep Learning Sequence to Sequence Model with Attention

Consumer Behaviour in Retail: Next Logical Purchase using Deep Neural Network

Reconstruct Anomaly to Normal: Adversarial Learned and Latent Vector-constrained Autoencoder for Time-series Anomaly Detection

Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings

A Deep Learning Forecaster with Exogenous Variables for Day-Ahead Locational Marginal Price

Model-Based Reinforcement Learning for Type 1Diabetes Blood Glucose Control

Theory and Algorithms for Shapelet-based Multiple-Instance Learning

Multivariate Time Series Classification with Hierarchical Variational Graph Pooling

Early Abandoning PrunedDTW and its application to similarity search

A Case-Study on the Impact of Dynamic Time Warping in Time Series Regression

TOTOPO: Classifying univariate and multivariate time series with Topological Data Analysis

A Critical Overview of Privacy-Preserving Approaches for Collaborative Forecasting

MIA-Prognosis: A Deep Learning Framework to Predict Therapy Response

Recurrent convolutional neural network for the surrogate modeling of subsurface flow simulation

Multivariate Temporal Autoencoder for Predictive Reconstruction of Deep Sequences

A fast noise filtering algorithm for time series prediction using recurrent neural networks

Time-Dynamic Estimates of the Reliability of Deep Semantic Segmentation Networks

Multivariate Quantile Bayesian Structural Time Series (MQBSTS) Model

Online learning of both state and dynamics using ensemble Kalman filters

TimeAutoML: Autonomous Representation Learning for Multivariate Irregularly Sampled Time Series

Leveraging Class Hierarchies with Metric-Guided Prototype Learning

An Evaluation of Classification Methods for 3D Printing Time-Series Data

From Time Series to Euclidean Spaces: On Spatial Transformations for Temporal Clustering

Extreme-SAX: Extreme Points Based Symbolic Representation for Time Series Classification

Modifying the Symbolic Aggregate Approximation Method to Capture Segment Trend Information

Quantile Convolutional Neural Networks for Value at Risk Forecasting

AAMDRL: Augmented Asset Management with Deep Reinforcement Learning

Anomaly Detection and Sampling Cost Control via Hierarchical GANs

GTEA: Representation Learning for Temporal Interaction Graphs via Edge Aggregation

ODE guided Neural Data Augmentation Techniques for Time Series Data and its Benefits on Robustness

Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction

Enhancing Time Series Momentum Strategies Using Deep Neural Networks

Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting

Semi-Supervised Learning for In-Game Expert-Level Music-to-Dance Translation

A Context Integrated Relational Spatio-Temporal Model for Demand and Supply Forecasting

Deep Learning based Covert Attack Identification for Industrial Control Systems

TAnoGAN: Time Series Anomaly Detection with Generative Adversarial Networks

Adversarial Examples in Deep Learning for Multivariate Time Series Regression

A Linear Transportation $\mathrm{L}^p$ Distance for Pattern Recognition

An analysis of deep neural networks for predicting trends in time series data

Survey of explainable machine learning with visual and granular methods beyond quasi-explanations

Resilient In-Season Crop Type Classification in Multispectral Satellite Observations using Growth Stage Normalization

Process Knowledge Driven Change Point Detection for Automated Calibration of Discrete Event Simulation Models Using Machine Learning

Explainable boosted linear regression for time series forecasting

Evaluation of Local Explanation Methods for Multivariate Time Series Forecasting

Time-series Imputation and Prediction with Bi-Directional Generative Adversarial Networks

Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders

Automatic deep learning for trend prediction in time series data

A 1d convolutional network for leaf and time series classification

Matrix Profile XXII: Exact Discovery of Time Series Motifs under DTW

Context Model for Pedestrian Intention Prediction using Factored Latent-Dynamic Conditional Random Fields

Frequency-based Multi Task learning With Attention Mechanism for Fault Detection In Power Systems

Learning Hidden Patterns from Patient Multivariate Time Series Data Using Convolutional Neural Networks: A Case Study of Healthcare Cost Prediction

Healthcare Cost Prediction: Leveraging Fine-grain Temporal Patterns

Correlation-aware Unsupervised Change-point Detection via Graph Neural Networks

A Genetic Feature Selection Based Two-stream Neural Network for Anger Veracity Recognition

Deep Switching Auto-Regressive Factorization:Application to Time Series Forecasting

Actionable Interpretation of Machine Learning Models for Sequential Data: Dementia-related Agitation Use Case

Data-Driven Open Set Fault Classification and Fault Size Estimation Using Quantitative Fault Diagnosis Analysis

Large-scale nonlinear Granger causality: A data-driven, multivariate approach to recovering directed networks from short time-series data

tsBNgen: A Python Library to Generate Time Series Data from an Arbitrary Dynamic Bayesian Network Structure

Risk Prediction of Peer-to-Peer Lending Market by a LSTM Model with Macroeconomic Factor

Topology-based Clusterwise Regression for User Segmentation and Demand Forecasting

Multivariable times series classification through an interpretable representation

Computer Model Calibration with Time Series Data using Deep Learning and Quantile Regression

Multivariate Time-series Anomaly Detection via Graph Attention Network

Travel time prediction for congested freeways with a dynamic linear model

LAVARNET: Neural Network Modeling of Causal Variable Relationships for Multivariate Time Series Forecasting

Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values

Application of LSTM architectures for next frame forecasting in Sentinel-1 images time series

Data Anomaly Detection for Structural Health Monitoring of Bridges using Shapelet Transform

Benchmarking adversarial attacks and defenses for time-series data

DeepFolio: Convolutional Neural Networks for Portfolios with Limit Order Book Data

Deep Recurrent Model for Individualized Prediction of Alzheimer's Disease Progression

Hybrid Deep Neural Networks to Infer State Models of Black-Box Systems

Gesture Recognition from Skeleton Data for Intuitive Human-Machine Interaction

$k$-means on Positive Definite Matrices, and an Application to Clustering in Radar Image Sequences

Counterfactual Explanations for Machine Learning on Multivariate Time Series Data

ATM Cash demand forecasting in an Indian Bank with chaos and deep learning

DeepSTCL: A Deep Spatio-temporal ConvLSTM for Travel Demand Prediction

Modelling Segmented Cardiotocography Time-Series Signals Using One-Dimensional Convolutional Neural Networks for the Early Detection of Abnormal Birth Outcomes

Seasonal-adjustment Based Feature Selection Method for Large-scale Search Engine Logs

The Canonical Interval Forest (CIF) Classifier for Time Series Classification

Reinforcement Learning based dynamic weighing of Ensemble Models for Time Series Forecasting

MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III

Predicting Future Sales of Retail Products using Machine Learning

Selecting Data Adaptive Learner from Multiple Deep Learners using Bayesian Networks

Learning from Irregularly-Sampled Time Series: A Missing Data Perspective

Deep Neural Networks for automatic extraction of features in time series satellite images

A Survey on Knowledge integration techniques with Artificial Neural Networks for seq-2-seq/time series models

Airflow recovery from thoracic and abdominal movements using Synchrosqueezing Transform and Locally Stationary Gaussian Process Regression

Automatic Remaining Useful Life Estimation Framework with Embedded Convolutional LSTM as the Backbone

Comparative Analysis of the Hidden Markov Model and LSTM: A Simulative Approach

Improving the Accuracy of Global Forecasting Models using Time Series Data Augmentation

Modeling of time series using random forests: theoretical developments

A Causal-based Framework for Multimodal Multivariate Time Series Validation Enhanced by Unsupervised Deep Learning as an Enabler for Industry 4.0

Conditional Latent Block Model: a Multivariate Time Series Clustering Approach for Autonomous Driving Validation

Ubicomp Digital 2020 -- Handwriting classification using a convolutional recurrent network

Instance Explainable Temporal Network For Multivariate Timeseries

Shape-CD: Change-Point Detection in Time-Series Data with Shapes and Neurons

Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows

Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models

Prediction of hierarchical time series using structured regularization and its application to artificial neural networks

Classification with 2-D Convolutional Neural Networks for breast cancer diagnosis

Don't Forget The Past: Recurrent Depth Estimation from Monocular Video

Improving Robustness on Seasonality-Heavy Multivariate Time Series Anomaly Detection

ESPRESSO: Entropy and ShaPe awaRe timE-Series SegmentatiOn for processing heterogeneous sensor data

Fused-Lasso Regularized Cholesky Factors of Large Nonstationary Covariance Matrices of Longitudinal Data

A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data

Handling Variable-Dimensional Time Series with Graph Neural Networks

Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach

Can we Estimate Truck Accident Risk from Telemetric Data using Machine Learning?

Fast Variational Learning in State-Space Gaussian Process Models

Leveraging the Self-Transition Probability of Ordinal Pattern Transition Graph for Transportation Mode Classification

Comparison of Different Methods for Time Sequence Prediction in Autonomous Vehicles

timeXplain -- A Framework for Explaining the Predictions of Time Series Classifiers

MTS-CycleGAN: An Adversarial-based Deep Mapping Learning Network for Multivariate Time Series Domain Adaptation Applied to the Ironmaking Industry

Attention Mechanism for Multivariate Time Series Recurrent Model Interpretability Applied to the Ironmaking Industry

VAE-LIME: Deep Generative Model Based Approach for Local Data-Driven Model Interpretability Applied to the Ironmaking Industry

Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution

Towards a Near Universal Time Series Data Mining Tool: Introducing the Matrix Profile

Automatic Detection of Major Freeway Congestion Events Using Wireless Traffic Sensor Data: A Machine Learning Approach

Improving the Robustness of Trading Strategy Backtesting with Boltzmann Machines and Generative Adversarial Networks

Lightweight Temporal Self-Attention for Classifying Satellite Image Time Series

Winning with Simple Learning Models: Detecting Earthquakes in Groningen, the Netherlands

Superiority of Simplicity: A Lightweight Model for Network Device Workload Prediction

Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural Networks

Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances

Novel semi-metrics for multivariate change point analysis and anomaly detection

Accurate Characterization of Non-Uniformly Sampled Time Series using Stochastic Differential Equations

N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding

Graph Neural Networks for Leveraging Industrial Equipment Structure: An application to Remaining Useful Life Estimation

ForecastNet: A Time-Variant Deep Feed-Forward Neural Network Architecture for Multi-Step-Ahead Time-Series Forecasting

Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions

Covariance-engaged Classification of Sets via Linear Programming

Combining Ensemble Kalman Filter and Reservoir Computing to predict spatio-temporal chaotic systems from imperfect observations and models

Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning

Hidden Markov Nonlinear ICA: Unsupervised Learning from Nonstationary Time Series

Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov Model

A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting

Supporting Optimal Phase Space Reconstructions Using Neural Network Architecture for Time Series Modeling

Robust Group Subspace Recovery: A New Approach for Multi-Modality Data Fusion

Revisiting clustering as matrix factorisation on the Stiefel manifold

Low-Rank Autoregressive Tensor Completion for Multivariate Time Series Forecasting

Markovian RNN: An Adaptive Time Series Prediction Network with HMM-based Switching for Nonstationary Environments

Nonlinear Evolution via Spatially-Dependent Linear Dynamics for Electrophysiology and Calcium Data

A Multi-Phase Approach for Product Hierarchy Forecasting in Supply Chain Management: Application to MonarchFx Inc

FedGAN: Federated Generative Adversarial Networks for Distributed Data

Stanza: A Nonlinear State Space Model for Probabilistic Inference in Non-Stationary Time Series

Sparse Dynamic Distribution Decomposition: Efficient Integration of Trajectory and Snapshot Time Series Data

Model-Size Reduction for Reservoir Computing by Concatenating Internal States Through Time

Deep Learning with Attention Mechanism for Predicting Driver Intention at Intersection

Hierarchical regularization networks for sparsification based learning on noisy datasets

Cost-effective Interactive Attention Learning with Neural Attention Processes

Multivariate Time Series Forecasting with Transfer Entropy Graph

Statistical Estimation of High-Dimensional Vector Autoregressive Models

tvGP-VAE: Tensor-variate Gaussian Process Prior Variational Autoencoder

Forecasting with sktime: Designing sktime's New Forecasting API and Applying It to Replicate and Extend the M4 Study

Dynamic Time Warping as a New Evaluation for Dst Forecast with Machine Learning

Hybrid Model for Anomaly Detection on Call Detail Records by Time Series Forecasting

Path Imputation Strategies for Signature Models of Irregular Time Series

Time Series Analysis and Forecasting of COVID-19 Cases Using LSTM and ARIMA Models

Joint learning of variational representations and solvers for inverse problems with partially-observed data

Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE

ReRe: A Lightweight Real-time Ready-to-Go Anomaly Detection Approach for Time Series

Long Short-Term Memory with Gate and State Level Fusion for Light Field-Based Face Recognition

Variable-lag Granger Causality and Transfer Entropy for Time Series Analysis

Interpretable Time Series Classification using Linear Models and Multi-resolution Multi-domain Symbolic Representations

Comparison of Recurrent Neural Network Architectures for Wildfire Spread Modelling

Unsupervised Online Anomaly Detection On Irregularly Sampled Or Missing Valued Time-Series Data Using LSTM Networks

Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks

PI-Net: A Deep Learning Approach to Extract Topological Persistence Images

Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University

Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data

Riemannian geometry for Compound Gaussian distributions: application to recursive change detection

Neural Ordinary Differential Equation based Recurrent Neural Network Model

Neural ODEs for Informative Missingness in Multivariate Time Series

Anomaly Detection And Classification In Time Series With Kervolutional Neural Networks

A Composite Quantile Fourier Neural Network for Multi-Step Probabilistic Forecasting of Nonstationary Univariate Time Series

A network-based transfer learning approach to improve sales forecasting of new products

A Novel Granular-Based Bi-Clustering Method of Deep Mining the Co-Expressed Genes

Data-Space Inversion Using a Recurrent Autoencoder for Time-Series Parameterization

Joint Multi-Dimensional Model for Global and Time-Series Annotations

Improvement in Land Cover and Crop Classification based on Temporal Features Learning from Sentinel-2 Data Using Recurrent-Convolutional Neural Network (R-CNN)

TSViz: Demystification of Deep Learning Models for Time-Series Analysis

If You Like It, GAN It. Probabilistic Multivariate Times Series Forecast With GAN

SeismoGen: Seismic Waveform Synthesis Using Generative Adversarial Networks

Supervised Feature Subset Selection and Feature Ranking for Multivariate Time Series without Feature Extraction

Attentive Weakly Supervised land cover mapping for object-based satellite image time series data with spatial interpretation

Robust Lane Detection from Continuous Driving Scenes Using Deep Neural Networks

k-Nearest Neighbour Classifiers: 2nd Edition (with Python examples)

Application of Deep Interpolation Network for Clustering of Physiologic Time Series

Forecasting in Non-stationary Environments with Fuzzy Time Series

Interpretable Multi-Task Deep Neural Networks for Dynamic Predictions of Postoperative Complications

Data-Driven Construction of Data Center Graph of Things for Anomaly Detection

Ensemble Deep Learning on Time-Series Representation of Tweets for Rumor Detection in Social Media

A tale of two toolkits, report the third: on the usage and performance of HIVE-COTE v1.0

Towards Accurate Predictions and Causal 'What-if' Analyses for Planning and Policy-making: A Case Study in Emergency Medical Services Demand

Sensor selection on graphs via data-driven node sub-sampling in network time series

A New Metric for Lumpy and Intermittent Demand Forecasts: Stock-keeping-oriented Prediction Error Costs

Applications of shapelet transform to time series classification of earthquake, wind and wave data

Characters as Graphs: Recognizing Online Handwritten Chinese Characters via Spatial Graph Convolutional Network

Transfer Learning with Graph Neural Networks for Short-Term Highway Traffic Forecasting

COVID-19 Time-series Prediction by Joint Dictionary Learning and Online NMF

A Bayesian Deep Learning Framework for End-To-End Prediction of Emotion from Heartbeat

Time Series Data Augmentation for Neural Networks by Time Warping with a Discriminative Teacher

Kernels for time series with irregularly-spaced multivariate observations

Stacked Boosters Network Architecture for Short Term Load Forecasting in Buildings

Co-eye: A Multi-resolution Symbolic Representation to TimeSeries Diversified Ensemble Classification

VELC: A New Variational AutoEncoder Based Model for Time Series Anomaly Detection

Hybrid Attention Networks for Flow and Pressure Forecasting in Water Distribution Systems

Clustering Time Series Data through Autoencoder-based Deep Learning Models

Probabilistic Spatial Transformers for Bayesian Data Augmentation

Real-time Classification from Short Event-Camera Streams using Input-filtering Neural ODEs

TSInsight: A local-global attribution framework for interpretability in time-series data

Forecasting in multivariate irregularly sampled time series with missing values

An information-geometric approach to feature extraction and moment reconstruction in dynamical systems

On the performance of deep learning models for time series classification in streaming

From Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction

NEWMA: a new method for scalable model-free online change-point detection

Anomaly Detection in Univariate Time-series: A Survey on the State-of-the-Art

A Spatio-Temporal Spot-Forecasting Framework for Urban Traffic Prediction

Correlated daily time series and forecasting in the M4 competition

Difference Attention Based Error Correction LSTM Model for Time Series Prediction

Half-empty or half-full? A Hybrid Approach to Predict Recycling Behavior of Consumers to Increase Reverse Vending Machine Uptime

Topological Data Analysis in Text Classification: Extracting Features with Additive Information

Proximity-Based Active Learning on Streaming Data: A Personalized Eating Moment Recognition

Ensemble Forecasting of Monthly Electricity Demand using Pattern Similarity-based Methods

Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization

ABBA: Adaptive Brownian bridge-based symbolic aggregation of time series

New Perspectives on the Use of Online Learning for Congestion Level Prediction over Traffic Data

Zero-shot and few-shot time series forecasting with ordinal regression recurrent neural networks

Triad State Space Construction for Chaotic Signal Classification with Deep Learning

G-Net: A Deep Learning Approach to G-computation for Counterfactual Outcome Prediction Under Dynamic Treatment Regimes

Adaptive exponential power distribution with moving estimator for nonstationary time series

Analysis of Hydrological and Suspended Sediment Events from Mad River Watershed using Multivariate Time Series Clustering

Improving Irregularly Sampled Time Series Learning with Dense Descriptors of Time

Statistically Guided Divide-and-Conquer for Sparse Factorization of Large Matrix

Human Activity Recognition from Wearable Sensor Data Using Self-Attention

Dynamic transformation of prior knowledge into Bayesian models for data streams

Context-dependent self-exciting point processes: models, methods, and risk bounds in high dimensions

Drift-Adjusted And Arbitrated Ensemble Framework For Time Series Forecasting

Probabilistic Forecasting with Temporal Convolutional Neural Network

Backdoor Attacks against Transfer Learning with Pre-trained Deep Learning Models

Time Series Forecasting Using LSTM Networks: A Symbolic Approach

Ambiguity in Sequential Data: Predicting Uncertain Futures with Recurrent Models

FusionLane: Multi-Sensor Fusion for Lane Marking Semantic Segmentation Using Deep Neural Networks

Adversarial Attacks on Probabilistic Autoregressive Forecasting Models

A Single Scalable LSTM Model for Short-Term Forecasting of Disaggregated Electricity Loads

Nonlinear Time Series Classification Using Bispectrum-based Deep Convolutional Neural Networks

Complexity Measures and Features for Times Series classification

Pattern Similarity-based Machine Learning Methods for Mid-term Load Forecasting: A Comparative Study

Learn to Generate Time Series Conditioned Graphs with Generative Adversarial Nets

Mixture-based Multiple Imputation Model for Clinical Data with a Temporal Dimension

Identity Recognition in Intelligent Cars with Behavioral Data and LSTM-ResNet Classifier

An empirical study of neural networks for trend detection in time series

Prediction of adverse events in Afghanistan: regression analysis of time series data grouped not by geographic dependencies

A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs

Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting

Longitudinal Support Vector Machines for High Dimensional Time Series

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs

A New Unified Deep Learning Approach with Decomposition-Reconstruction-Ensemble Framework for Time Series Forecasting

N-BEATS: Neural basis expansion analysis for interpretable time series forecasting

SummerTime: Variable-length Time SeriesSummarization with Applications to PhysicalActivity Analysis

Network Clustering Via Kernel-ARMA Modeling and the Grassmannian The Brain-Network Case

Controlled time series generation for automotive software-in-the-loop testing using GANs

Semantic Discord: Finding Unusual Local Patterns for Time Series

Generalised learning of time-series: Ornstein-Uhlenbeck processes

TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classification

The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth Measure

Fully convolutional networks for structural health monitoring through multivariate time series classification

A Physiology-Driven Computational Model for Post-Cardiac Arrest Outcome Prediction

Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems

Model adaptation and unsupervised learning with non-stationary batch data under smooth concept drift

Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems

Autoencoder-based time series clustering with energy applications

Unsupervised non-parametric change point detection in quasi-periodic signals

Confirmatory Bayesian Online Change Point Detection in the Covariance Structure of Gaussian Processes

Error-feedback Stochastic Configuration Strategy on Convolutional Neural Networks for Time Series Forecasting

Ensemble Grammar Induction For Detecting Anomalies in Time Series

Multi-label Prediction in Time Series Data using Deep Neural Networks

Bayesian nonparametric shared multi-sequence time series segmentation

Automatic Health Problem Detection from Gait Videos Using Deep Neural Networks

Inferring Individual Level Causal Models from Graph-based Relational Time Series

Linking Bank Clients using Graph Neural Networks Powered by Rich Transactional Data

Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case

A Multi-Scale Tensor Network Architecture for Classification and Regression

Causality based Feature Fusion for Brain Neuro-Developmental Analysis

Motif Difference Field: A Simple and Effective Image Representation of Time Series for Classification

Intelligence, physics and information -- the tradeoff between accuracy and simplicity in machine learning

Inference for Network Structure and Dynamics from Time Series Data via Graph Neural Network

Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality

Relational State-Space Model for Stochastic Multi-Object Systems

Framework for Inferring Following Strategies from Time Series of Movement Data

Temporally Folded Convolutional Neural Networks for Sequence Forecasting

Bayesian Recurrent Framework for Missing Data Imputation and Prediction with Clinical Time Series

Fully Neural Network based Model for General Temporal Point Processes

GRATIS: GeneRAting TIme Series with diverse and controllable characteristics

Real Time Trajectory Prediction Using Deep Conditional Generative Models

Scalable Hybrid HMM with Gaussian Process Emission for Sequential Time-series Data Clustering

Discovering Nonlinear Relations with Minimum Predictive Information Regularization

Prediction of MRI Hardware Failures based on Image Features using Time Series Classification

Root Cause Detection Among Anomalous Time Series Using Temporal State Alignment

Temporal Tensor Transformation Network for Multivariate Time Series Prediction

Unsupervised Scalable Representation Learning for Multivariate Time Series

Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting

A Deep Structural Model for Analyzing Correlated Multivariate Time Series

Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series

Graph Message Passing with Cross-location Attentions for Long-term ILI Prediction

Crowdfunding Dynamics Tracking: A Reinforcement Learning Approach

A Distributed Neural Network Architecture for Robust Non-Linear Spatio-Temporal Prediction

Visual Evaluation of Generative Adversarial Networks for Time Series Data

The Expressivity and Training of Deep Neural Networks: toward the Edge of Chaos?

Applying Deep Learning to Detect Traffic Accidents in Real Time Using Spatiotemporal Sequential Data

Dynamic Prediction of ICU Mortality Risk Using Domain Adaptation

Time Series Classification: Lessons Learned in the (Literal) Field while Studying Chicken Behavior

Features or Shape? Tackling the False Dichotomy of Time Series Classification

On the Metrics and Adaptation Methods for Domain Divergences of sEMG-based Gesture Recognition

Training Dynamic Exponential Family Models with Causal and Lateral Dependencies for Generalized Neuromorphic Computing

Feature engineering workflow for activity recognition from synchronized inertial measurement units

Water Supply Prediction Based on Initialized Attention Residual Network

A posteriori Trading-inspired Model-free Time Series Segmentation

Application of Machine Learning to accidents detection at directional drilling

Deteção de estruturas permanentes a partir de dados de séries temporais Sentinel 1 e 2

Classification des S{é}ries Temporelles Incertaines par Transformation Shapelet

Towards Better Forecasting by Fusing Near and Distant Future Visions

InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers

Clustering Time-Series by a Novel Slope-Based Similarity Measure Considering Particle Swarm Optimization

Regression with Uncertainty Quantification in Large Scale Complex Data

Detecting Hardly Visible Roads in Low-Resolution Satellite Time Series Data

Machine learning applications in time series hierarchical forecasting

Optimal Attack against Autoregressive Models by Manipulating the Environment

Training Distributed Deep Recurrent Neural Networks with Mixed Precision on GPU Clusters

Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019

GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series

A tale of two toolkits, report the second: bake off redux. Chapter 1. dictionary based classifiers

Deep Air Quality Forecasting Using Hybrid Deep Learning Framework

Deep Mixed Effect Model using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare

Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction

Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values

Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series

Modeling emotion in complex stories: the Stanford Emotional Narratives Dataset

Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information

Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors

A Comparative Analysis of Forecasting Financial Time Series Using ARIMA, LSTM, and BiLSTM

Convolutional Mixture Density Recurrent Neural Network for Predicting User Location with WiFi Fingerprints

Simultaneous Implementation Features Extraction and Recognition Using C3D Network for WiFi-based Human Activity Recognition

Discovering Subdimensional Motifs of Different Lengths in Large-Scale Multivariate Time Series

Challenges with Extreme Class-Imbalance and Temporal Coherence: A Study on Solar Flare Data

Comparison between DeepESNs and gated RNNs on multivariate time-series prediction

The dynamics of the stomatognathic system from 4D multimodal data

Object-based multi-temporal and multi-source land cover mapping leveraging hierarchical class relationships

Learning Weighted Submanifolds with Variational Autoencoders and Riemannian Variational Autoencoders

Driver Identification Based on Vehicle Telematics Data using LSTM-Recurrent Neural Network

DeStress: Deep Learning for Unsupervised Identification of Mental Stress in Firefighters from Heart-rate Variability (HRV) Data

Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention

Efficient structure learning with automatic sparsity selection for causal graph processes

RSM-GAN: A Convolutional Recurrent GAN for Anomaly Detection in Contaminated Seasonal Multivariate Time Series

Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis

Self-supervised representation learning from electroencephalography signals

Detecting Patterns of Physiological Response to Hemodynamic Stress via Unsupervised Deep Learning

Generating an Explainable ECG Beat Space With Variational Auto-Encoders

Building Effective Large-Scale Traffic State Prediction System: Traffic4cast Challenge Solution

Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models

Towards Learning Universal, Regional, and Local Hydrological Behaviors via Machine-Learning Applied to Large-Sample Datasets

Spatio-Temporal Alignments: Optimal transport through space and time

Early Predictions for Medical Crowdfunding: A Deep Learning Approach Using Diverse Inputs

Time-Series Analysis via Low-Rank Matrix Factorization Applied to Infant-Sleep Data

Architectural Tricks for Deep Learning in Remote Photoplethysmography

Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes

Variational Bayesian inference of hidden stochastic processes with unknown parameters

Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data

Classification of Hand Movements from EEG using a Deep Attention-based LSTM Network

Quick and Easy Time Series Generation with Established Image-based GANs

ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels

Harnessing the power of Topological Data Analysis to detect change points in time series

Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks

Learning low-dimensional state embeddings and metastable clusters from time series data

Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting

Causal inference for climate change events from satellite image time series using computer vision and deep learning

High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes

U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging

ODE$^2$VAE: Deep generative second order ODEs with Bayesian neural networks

Quick, Stat!: A Statistical Analysis of the Quick, Draw! Dataset

Sequential Gaussian Processes for Online Learning of Nonstationary Functions

Evolving Gaussian Process kernels from elementary mathematical expressions

Causal Mechanism Transfer Network for Time Series Domain Adaptation in Mechanical Systems

WaveletAE: A Wavelet-enhanced Autoencoder for Wind Turbine Blade Icing Detection

Graph Spectral Embedding for Parsimonious Transmission of Multivariate Time Series

Data Smashing 2.0: Sequence Likelihood (SL) Divergence For Fast Time Series Comparison

A tale of two toolkits, report the first: benchmarking time series classification algorithms for correctness and efficiency

Demand Forecasting from Spatiotemporal Data with Graph Networks and Temporal-Guided Embedding

Forecasting, Causality, and Impulse Response with Neural Vector Autoregressions

The Sparse Reverse of Principal Component Analysis for Fast Low-Rank Matrix Completion

Unsupervised Representation for EHR Signals and Codes as Patient Status Vector

End-to-end learning of energy-based representations for irregularly-sampled signals and images

Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters

Stochastic Weight Matrix-based Regularization Methods for Deep Neural Networks

The Dynamical Gaussian Process Latent Variable Model in the Longitudinal Scenario

WATTNet: Learning to Trade FX via Hierarchical Spatio-Temporal Representation of Highly Multivariate Time Series

Temporal Pattern Attention for Multivariate Time Series Forecasting

sktime: A Unified Interface for Machine Learning with Time Series

Self-boosted Time-series Forecasting with Multi-task and Multi-view Learning

Reusing Convolutional Activations from Frame to Frame to Speed up Training and Inference

Interpolation-Prediction Networks for Irregularly Sampled Time Series

Few-Shot Deep Adversarial Learning for Video-based Person Re-identification

Estimating Granger Causality with Unobserved Confounders via Deep Latent-Variable Recurrent Neural Network

Explaining Deep Classification of Time-Series Data with Learned Prototypes

Machine Learning and the Internet of Things Enable Steam Flood Optimization for Improved Oil Production

Early Classification for Agricultural Monitoring from Satellite Time Series

Autoregressive-Model-Based Methods for Online Time Series Prediction with Missing Values: an Experimental Evaluation

Griffon: Reasoning about Job Anomalies with Unlabeled Data in Cloud-based Platforms

Inferring Global Dynamics of a Black-Box System Using Machine Learning

Time series model selection with a meta-learning approach; evidence from a pool of forecasting algorithms

Dynamic Prediction Length for Time Series with Sequence to Sequence Networks

Chaotic Time Series Prediction using Spatio-Temporal RBF Neural Networks

Variational approach for learning Markov processes from time series data

A Machine Learning Approach for Smartphone-based Sensing of Roads and Driving Style

A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification

Local Score Dependent Model Explanation for Time Dependent Covariates

MEx: Multi-modal Exercises Dataset for Human Activity Recognition

Sales Demand Forecast in E-commerce using a Long Short-Term Memory Neural Network Methodology

DeepAISE -- An End-to-End Development and Deployment of a Recurrent Neural Survival Model for Early Prediction of Sepsis

Multitask learning and benchmarking with clinical time series data

Sparse Coding of Shape Trajectories for Facial Expression and Action Recognition

NeuPDE: Neural Network Based Ordinary and Partial Differential Equations for Modeling Time-Dependent Data

Self-Organizing Maps with Variable Input Length for Motif Discovery and Word Segmentation

Model inference for Ordinary Differential Equations by parametric polynomial kernel regression

CDSA: Cross-Dimensional Self-Attention for Multivariate, Geo-tagged Time Series Imputation

Inferring linear and nonlinear Interaction networks using neighborhood support vector machines

Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models

Generalisation in fully-connected neural networks for time series forecasting

Deep Generative Quantile-Copula Models for Probabilistic Forecasting

SleepNet: Automated Sleep Analysis via Dense Convolutional Neural Network Using Physiological Time Series

Interpretable Classification of Time-Series Data using Efficient Enumerative Techniques

Detecting Regions of Maximal Divergence for Spatio-Temporal Anomaly Detection

Deep Learning for Time Series Forecasting: The Electric Load Case

An Adaptive Approach for Anomaly Detector Selection and Fine-Tuning in Time Series

Clustering Activity-Travel Behavior Time Series using Topological Data Analysis

Efficient Kernel-based Subsequence Search for User Identification from Walking Activity

Automated Real-time Anomaly Detection in Human Trajectories using Sequence to Sequence Networks

Activity2Vec: Learning ADL Embeddings from Sensor Data with a Sequence-to-Sequence Model

Time series cluster kernels to exploit informative missingness and incomplete label information

A Review of Deep Learning with Special Emphasis on Architectures, Applications and Recent Trends

Non-technical Loss Detection with Statistical Profile Images Based on Semi-supervised Learning

Streaming Adaptation of Deep Forecasting Models using Adaptive Recurrent Units

Forecasting high-dimensional dynamics exploiting suboptimal embeddings

Insights into LSTM Fully Convolutional Networks for Time Series Classification

Predicting Treatment Initiation from Clinical Time Series Data via Graph-Augmented Time-Sensitive Model

Rare Disease Detection by Sequence Modeling with Generative Adversarial Networks

Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization

Fast Convolutive Nonnegative Matrix Factorization Through Coordinate and Block Coordinate Updates

MLFriend: Interactive Prediction Task Recommendation for Event-Driven Time-Series Data

Anomaly Subsequence Detection with Dynamic Local Density for Time Series

An Improvement of PAA on Trend-Based Approximation for Time Series

RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend Filtering

Detection of small changes in medical and random-dot images comparing self-organizing map performance to human detection

A Self-supervised Approach to Hierarchical Forecasting with Applications to Groupwise Synthetic Controls

Gesture Recognition in RGB Videos UsingHuman Body Keypoints and Dynamic Time Warping

Traffic Flow Combination Forecasting Method Based on Improved LSTM and ARIMA

Enforcing constraints for interpolation and extrapolation in Generative Adversarial Networks

Topological Data Analysis of Time Series Data for B2B Customer Relationship Management

Normalizing flows for novelty detection in industrial time series data

Machine Learning of Time Series Using Time-delay Embedding and Precision Annealing

Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping

A Variational Autoencoder for Probabilistic Non-Negative Matrix Factorisation

Learning Interpretable Shapelets for Time Series Classification through Adversarial Regularization

Evaluating aleatoric and epistemic uncertainties of time series deep learning models for soil moisture predictions

Energy Predictive Models with Limited Data using Transfer Learning

Brain-Network Clustering via Kernel-ARMA Modeling and the Grassmannian

CCMI : Classifier based Conditional Mutual Information Estimation

A Fast-Optimal Guaranteed Algorithm For Learning Sub-Interval Relationships in Time Series

Characterizing and Forecasting User Engagement with In-app Action Graph: A Case Study of Snapchat

Super-resolution of Time-series Labels for Bootstrapped Event Detection

Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes

Time Series Anomaly Detection Using Convolutional Neural Networks and Transfer Learning

A novel hybrid model based on multi-objective Harris hawks optimization algorithm for daily PM2.5 and PM10 forecasting

Assessing the effect of advertising expenditures upon sales: a Bayesian structural time series model

Exploring Interpretable LSTM Neural Networks over Multi-Variable Data

Evaluating time series forecasting models: An empirical study on performance estimation methods

Identifying cross country skiing techniques using power meters in ski poles

Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data

Predicting Sparse Clients' Actions with CPOPT-Net in the Banking Environment

Population-based Global Optimisation Methods for Learning Long-term Dependencies with RNNs

Quantifying Long Range Dependence in Language and User Behavior to improve RNNs

Augmenting Physiological Time Series Data: A Case Study for Sleep Apnea Detection

Discovering Latent Covariance Structures for Multiple Time Series

Enforcing constraints for time series prediction in supervised, unsupervised and reinforcement learning

Automatic Posterior Transformation for Likelihood-Free Inference

Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces

Semantic Analysis of Traffic Camera Data: Topic Signal Extraction and Anomalous Event Detection

Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation

Biosignal Generation and Latent Variable Analysis with Recurrent Generative Adversarial Networks

Deep Learning for Multi-Scale Changepoint Detection in Multivariate Time Series

Analyzing Dynamical Brain Functional Connectivity As Trajectories on Space of Covariance Matrices

Differential Recurrent Neural Network and its Application for Human Activity Recognition

Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI

Unsupervised Learning through Temporal Smoothing and Entropy Maximization

Learning Causality: Synthesis of Large-Scale Causal Networks from High-Dimensional Time Series Data

Multivariate Time Series Classification using Dilated Convolutional Neural Network

Temporal Graph Convolutional Networks for Automatic Seizure Detection

ConvTimeNet: A Pre-trained Deep Convolutional Neural Network for Time Series Classification

Surface Type Classification for Autonomous Robot Indoor Navigation

Multi-resolution Networks For Flexible Irregular Time Series Modeling (Multi-FIT)

Sequence to sequence deep learning models for solar irradiation forecasting

Real numbers, data science and chaos: How to fit any dataset with a single parameter

Temporal-Clustering Invariance in Irregular Healthcare Time Series

Time Series Simulation by Conditional Generative Adversarial Net

Wearable-based Parkinson's Disease Severity Monitoring using Deep Learning

Predicting Student Performance in an Educational Game Using a Hidden Markov Model

Mining Novel Multivariate Relationships in Time Series Data Using Correlation Networks

Linear Multiple Low-Rank Kernel Based Stationary Gaussian Processes Regression for Time Series

Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics

Human Motion Prediction via Pattern Completion in Latent Representation Space

One-dimensional Deep Image Prior for Time Series Inverse Problems

DSTP-RNN: a dual-stage two-phase attention-based recurrent neural networks for long-term and multivariate time series prediction

On Arrhythmia Detection by Deep Learning and Multidimensional Representation

Handling temporality of clinical events with application to Adverse Drug Event detection in Electronic Health Records: A scoping review

Decomposing Temperature Time Series with Non-Negative Matrix Factorization

A Novel GAN-based Fault Diagnosis Approach for Imbalanced Industrial Time Series

Two-phase flow regime prediction using LSTM based deep recurrent neural network

Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination

Probabilistic Forecasting of Sensory Data with Generative Adversarial Networks - ForGAN

Online Estimation of Multiple Dynamic Graphs in Pattern Sequences

Medical Time Series Classification with Hierarchical Attention-based Temporal Convolutional Networks: A Case Study of Myotonic Dystrophy Diagnosis

Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flow

Improved Dynamic Time Warping (DTW) Approach for Online Signature Verification

Optimal Combination Forecasts on Retail Multi-Dimensional Sales Data

Trainable Time Warping: Aligning Time-Series in the Continuous-Time Domain

Multi-Task Time Series Analysis applied to Drug Response Modelling

Learning Disentangled Representations of Satellite Image Time Series

Multi-Stage Fault Warning for Large Electric Grids Using Anomaly Detection and Machine Learning

Multiple-Kernel Dictionary Learning for Reconstruction and Clustering of Unseen Multivariate Time-series

Graph Hierarchical Convolutional Recurrent Neural Network (GHCRNN) for Vehicle Condition Prediction

Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks

Should we Reload Time Series Classification Performance Evaluation ? (a position paper)

Deep Learning with Convolutional Neural Network for Objective Skill Evaluation in Robot-assisted Surgery

Autoregressive Convolutional Recurrent Neural Network for Univariate and Multivariate Time Series Prediction

Temporal Registration in Application to In-utero MRI Time Series

A Data-Driven Approach for Predicting Vegetation-Related Outages in Power Distribution Systems

Inferring Multidimensional Rates of Aging from Cross-Sectional Data

Data-driven Neural Architecture Learning For Financial Time-series Forecasting

Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach

Application of Deep Learning Long Short-Term Memory in Energy Demand Forecasting

3D Graph Convolutional Networks with Temporal Graphs: A Spatial Information Free Framework For Traffic Forecasting

Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs

Reducing Artificial Neural Network Complexity: A Case Study on Exoplanet Detection

Deep MR Fingerprinting with total-variation and low-rank subspace priors

Robust and Subject-Independent Driving Manoeuvre Anticipation through Domain-Adversarial Recurrent Neural Networks

Short-term Road Traffic Prediction based on Deep Cluster at Large-scale Networks

Data-driven Perception of Neuron Point Process with Unknown Unknowns

Deep Gated Recurrent and Convolutional Network Hybrid Model for Univariate Time Series Classification

Emulating dynamic non-linear simulators using Gaussian processes

Structural Recurrent Neural Network for Traffic Speed Prediction

A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection

Recurrent Deep Divergence-based Clustering for simultaneous feature learning and clustering of variable length time series

Sinkhorn Divergence of Topological Signature Estimates for Time Series Classification

Elastic bands across the path: A new framework and methods to lower bound DTW

Approximate Newton-based statistical inference using only stochastic gradients

Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning

A Spatial-Temporal Decomposition Based Deep Neural Network for Time Series Forecasting

T-CGAN: Conditional Generative Adversarial Network for Data Augmentation in Noisy Time Series with Irregular Sampling

Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series

Short-term Demand Forecasting for Online Car-hailing Services using Recurrent Neural Networks

Deep-dust: Predicting concentrations of fine dust in Seoul using LSTM

Discovery of Important Subsequences in Electrocardiogram Beats Using the Nearest Neighbour Algorithm

Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data

Exploiting statistical dependencies of time series with hierarchical correlation reconstruction

Deep learning-based electroencephalography analysis: a systematic review

Explainable Failure Predictions with RNN Classifiers based on Time Series Data

Kernel Change-point Detection with Auxiliary Deep Generative Models

Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference

Efficient Matrix Profile Computation Using Different Distance Functions

Adversarial Domain Adaptation for Stable Brain-Machine Interfaces

MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks

Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series

Impact of Data Normalization on Deep Neural Network for Time Series Forecasting

SOM-VAE: Interpretable Discrete Representation Learning on Time Series

A CNN adapted to time series for the classification of Supernovae

Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition

Using an Ancillary Neural Network to Capture Weekends and Holidays in an Adjoint Neural Network Architecture for Intelligent Building Management

Robust multivariate and functional archetypal analysis with application to financial time series analysis

A Comparison of LSTMs and Attention Mechanisms for Forecasting Financial Time Series

Video Trajectory Classification and Anomaly Detection Using Hybrid CNN-VAE

Combining Sentinel-1 and Sentinel-2 Time Series via RNN for object-based land cover classification

E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs

Semi-unsupervised Learning of Human Activity using Deep Generative Models

Multiple-Instance Learning by Boosting Infinitely Many Shapelet-based Classifiers

Closed-form Inference and Prediction in Gaussian Process State-Space Models

Financial Series Prediction: Comparison Between Precision of Time Series Models and Machine Learning Methods

seq2graph: Discovering Dynamic Dependencies from Multivariate Time Series with Multi-level Attention

Time-Discounting Convolution for Event Sequences with Ambiguous Timestamps

RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series

Learning Individualized Cardiovascular Responses from Large-scale Wearable Sensors Data

Multivariate Time-series Similarity Assessment via Unsupervised Representation Learning and Stratified Locality Sensitive Hashing: Application to Early Acute Hypotensive Episode Detection

Predicting Blood Pressure Response to Fluid Bolus Therapy Using Attention-Based Neural Networks for Clinical Interpretability

An Interpretable Machine Vision Approach to Human Activity Recognition using Photoplethysmograph Sensor Data

Examining Deep Learning Architectures for Crime Classification and Prediction

Modeling Treatment Delays for Patients using Feature Label Pairs in a Time Series

Improving Clinical Predictions through Unsupervised Time Series Representation Learning

Real-time Power System State Estimation and Forecasting via Deep Neural Networks

Deep Multimodal Learning: An Effective Method for Video Classification

Leveraging Clinical Time-Series Data for Prediction: A Cautionary Tale

Multi-step Time Series Forecasting Using Ridge Polynomial Neural Network with Error-Output Feedbacks

Deep Ensemble Tensor Factorization for Longitudinal Patient Trajectories Classification

Rapid Time Series Prediction with a Hardware-Based Reservoir Computer

Unsupervised Learning in Reservoir Computing for EEG-based Emotion Recognition

Multivariate Forecasting of Crude Oil Spot Prices using Neural Networks

InfoSSM: Interpretable Unsupervised Learning of Nonparametric State-Space Model for Multi-modal Dynamics

Black-Box Autoregressive Density Estimation for State-Space Models

Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables

A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data

Transform-Based Multilinear Dynamical System for Tensor Time Series Analysis

Spatio-temporal Stacked LSTM for Temperature Prediction in Weather Forecasting

Short-Term Wind-Speed Forecasting Using Kernel Spectral Hidden Markov Models

Adversarial Unsupervised Representation Learning for Activity Time-Series

Learning Representations of Missing Data for Predicting Patient Outcomes

Langevin-gradient parallel tempering for Bayesian neural learning

EA-LSTM: Evolutionary Attention-based LSTM for Time Series Prediction

Efficient Online Hyperparameter Optimization for Kernel Ridge Regression with Applications to Traffic Time Series Prediction

A High GOPs/Slice Time Series Classifier for Portable and Embedded Biomedical Applications

Can automated smoothing significantly improve benchmark time series classification algorithms?

PerceptionNet: A Deep Convolutional Neural Network for Late Sensor Fusion

Adaptive Extreme Learning Machine for Recurrent Beta-basis Function Neural Network Training

Causal Inference in Nonverbal Dyadic Communication with Relevant Interval Selection and Granger Causality

Time series clustering based on the characterisation of segment typologies

MOrdReD: Memory-based Ordinal Regression Deep Neural Networks for Time Series Forecasting

Autowarp: Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders

Using Deep Learning for price prediction by exploiting stationary limit order book features

A Consistent Method for Learning OOMs from Asymptotically Stationary Time Series Data Containing Missing Values

Seglearn: A Python Package for Learning Sequences and Time Series

A Periodicity-based Parallel Time Series Prediction Algorithm in Cloud Computing Environments

Real time expert system for anomaly detection of aerators based on computer vision technology and existing surveillance cameras

Deep Diabetologist: Learning to Prescribe Hyperglycemia Medications with Hierarchical Recurrent Neural Networks

Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data

Supervised Nonnegative Matrix Factorization to Predict ICU Mortality Risk

Discretizing Logged Interaction Data Biases Learning for Decision-Making

Concept-drifting Data Streams are Time Series; The Case for Continuous Adaptation

Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization

Using Autoencoders To Learn Interesting Features For Detecting Surveillance Aircraft

A Variational Time Series Feature Extractor for Action Prediction

A Capsule Network for Traffic Speed Prediction in Complex Road Networks

DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn

Time is of the Essence: Machine Learning-based Intrusion Detection in Industrial Time Series Data

Basic Filters for Convolutional Neural Networks Applied to Music: Training or Design?

From BOP to BOSS and Beyond: Time Series Classification with Dictionary Based Classifiers

Conditional Time Series Forecasting with Convolutional Neural Networks

Random Warping Series: A Random Features Method for Time-Series Embedding

A Time Series Graph Cut Image Segmentation Scheme for Liver Tumors

Explainable time series tweaking via irreversible and reversible temporal transformations

Learning Deep Mixtures of Gaussian Process Experts Using Sum-Product Networks

Forecasting Across Time Series Databases using Recurrent Neural Networks on Groups of Similar Series: A Clustering Approach

Revisiting Inaccuracies of Time Series Averaging under Dynamic Time Warping

A Memory-Network Based Solution for Multivariate Time-Series Forecasting

Deep Recurrent Electricity Theft Detection in AMI Networks with Random Tuning of Hyper-parameters

A Deep Learning Spatiotemporal Prediction Framework for Mobile Crowdsourced Services

DLBI: Deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy

Correlated Time Series Forecasting using Deep Neural Networks: A Summary of Results

Deep Chronnectome Learning via Full Bidirectional Long Short-Term Memory Networks for MCI Diagnosis

A Unified Framework for Long Range and Cold Start Forecasting of Seasonal Profiles in Time Series

NonSTOP: A NonSTationary Online Prediction Method for Time Series

Predicting Extubation Readiness in Extreme Preterm Infants based on Patterns of Breathing

Optimizing the Union of Intersections LASSO ($UoI_{LASSO}$) and Vector Autoregressive ($UoI_{VAR}$) Algorithms for Improved Statistical Estimation at Scale

Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks

Combining time-series and textual data for taxi demand prediction in event areas: a deep learning approach

Encoding Temporal Markov Dynamics in Graph for Visualizing and Mining Time Series

Interpretable Time Series Classification using All-Subsequence Learning and Symbolic Representations in Time and Frequency Domains

Data augmentation using synthetic data for time series classification with deep residual networks

Differentiable Compositional Kernel Learning for Gaussian Processes

Improving Optimization for Models With Continuous Symmetry Breaking

Approximate Collapsed Gibbs Clustering with Expectation Propagation

Scene Learning: Deep Convolutional Networks For Wind Power Prediction by Embedding Turbines into Grid Space

Assessment of electrical and infrastructure recovery in Puerto Rico following hurricane Maria using a multisource time series of satellite imagery

Exact and Robust Conformal Inference Methods for Predictive Machine Learning With Dependent Data

Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting

A Recurrent Neural Network Survival Model: Predicting Web User Return Time

Recurrent Auto-Encoder Model for Large-Scale Industrial Sensor Signal Analysis

Transfer Learning for Clinical Time Series Analysis using Recurrent Neural Networks

Accurate Uncertainties for Deep Learning Using Calibrated Regression

An Interpretable and Sparse Neural Network Model for Nonlinear Granger Causality Discovery

An Efficient ADMM Algorithm for Structural Break Detection in Multivariate Time Series

Multilevel Wavelet Decomposition Network for Interpretable Time Series Analysis

Focusing on What is Relevant: Time-Series Learning and Understanding using Attention

Sparse Multi-Output Gaussian Processes for Medical Time Series Prediction

A Review of Network Inference Techniques for Neural Activation Time Series

Prediction of Dynamical time Series Using Kernel Based Regression and Smooth Splines

Multi-variable LSTM neural network for autoregressive exogenous model

A Generative Modeling Approach to Limited Channel ECG Classification

Autoregressive Convolutional Neural Networks for Asynchronous Time Series

Direct Estimation of Pharmacokinetic Parameters from DCE-MRI using Deep CNN with Forward Physical Model Loss

Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care

Hierarchical Attention-Based Recurrent Highway Networks for Time Series Prediction

Sea surface temperature prediction and reconstruction using patch-level neural network representations

Root-cause Analysis for Time-series Anomalies via Spatiotemporal Graphical Modeling in Distributed Complex Systems

Grouped Convolutional Neural Networks for Multivariate Time Series

Generalised Structural CNNs (SCNNs) for time series data with arbitrary graph topology

Predicting County Level Corn Yields Using Deep Long Short Term Memory Models

Taxi demand forecasting: A HEDGE based tessellation strategy for improved accuracy

Currency exchange prediction using machine learning, genetic algorithms and technical analysis

Extracting Traffic Primitives Directly from Naturalistically Logged Data for Self-Driving Applications

Structure Learning from Time Series with False Discovery Control

Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification

Multi-Statistic Approximate Bayesian Computation with Multi-Armed Bandits

SAFE: Spectral Evolution Analysis Feature Extraction for Non-Stationary Time Series Prediction

Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions

Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data

A Tempt to Unify Heterogeneous Driving Databases using Traffic Primitives

An Unsupervised Clustering-Based Short-Term Solar Forecasting Methodology Using Multi-Model Machine Learning Blending

A Deep Learning Approach for Forecasting Air Pollution in South Korea Using LSTM

Invariants of multidimensional time series based on their iterated-integral signature

Multi-shot Pedestrian Re-identification via Sequential Decision Making

Real-time regression analysis with deep convolutional neural networks

30m resolution Global Annual Burned Area Mapping based on Landsat images and Google Earth Engine

Estimating Gradual-Emotional Behavior in One-Minute Videos with ESNs

An Evaluation of Classification and Outlier Detection Algorithms

COBRAS-TS: A new approach to Semi-Supervised Clustering of Time Series

Learning from multivariate discrete sequential data using a restricted Boltzmann machine model

Extended Vertical Lists for Temporal Pattern Mining from Multivariate Time Series

Detecting Nonlinear Causality in Multivariate Time Series with Sparse Additive Models

Spatio-Temporal Neural Networks for Space-Time Series Forecasting and Relations Discovery

Calibration-free B0 correction of EPI data using structured low rank matrix recovery

Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks

An interpretable LSTM neural network for autoregressive exogenous model

Expressway visibility estimation based on image entropy and piecewise stationary time series analysis

Missing Slice Recovery for Tensors Using a Low-rank Model in Embedded Space

Time series kernel similarities for predicting Paroxysmal Atrial Fibrillation from ECGs

Bag of Recurrence Patterns Representation for Time-Series Classification

Non-Linear Temporal Subspace Representations for Activity Recognition

Chatter Classification in Turning Using Machine Learning and Topological Data Analysis

An Incremental Boolean Tensor Factorization approach to model Change Patterns of Objects in Images

Classification of simulated radio signals using Wide Residual Networks for use in the search for extra-terrestrial intelligence

Efficient Recurrent Neural Networks using Structured Matrices in FPGAs

An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples

Learning non-Gaussian Time Series using the Box-Cox Gaussian Process

ARMDN: Associative and Recurrent Mixture Density Networks for eRetail Demand Forecasting

Capturing Structure Implicitly from Time-Series having Limited Data

Sales forecasting using WaveNet within the framework of the Kaggle competition

Deep reinforcement learning for time series: playing idealized trading games

Hybrid Forecasting of Chaotic Processes: Using Machine Learning in Conjunction with a Knowledge-Based Model

News-based forecasts of macroeconomic indicators: A semantic path model for interpretable predictions

M3Fusion: A Deep Learning Architecture for Multi-{Scale/Modal/Temporal} satellite data fusion

Optimal Warping Paths are unique for almost every Pair of Time Series

Replacement AutoEncoder: A Privacy-Preserving Algorithm for Sensory Data Analysis

Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction

Missing Data in Sparse Transition Matrix Estimation for Sub-Gaussian Vector Autoregressive Processes

Differentiable Dynamic Programming for Structured Prediction and Attention

Pattern Localization in Time Series through Signal-To-Model Alignment in Latent Space

Inferring the time-varying functional connectivity of large-scale computer networks from emitted events

Explaining Aviation Safety Incidents Using Deep Temporal Multiple Instance Learning

Predicting Customer Churn: Extreme Gradient Boosting with Temporal Data

A Correlation Based Feature Representation for First-Person Activity Recognition

Brain EEG Time Series Selection: A Novel Graph-Based Approach for Classification

Lasso Guarantees for Time Series Estimation Under Subgaussian Tails and $ β$-Mixing

Deep Temporal Clustering : Fully Unsupervised Learning of Time-Domain Features

Model-Free Renewable Scenario Generation Using Generative Adversarial Networks

One-class Collective Anomaly Detection based on Long Short-Term Memory Recurrent Neural Networks

End-to-End Fine-Grained Action Segmentation and Recognition Using Conditional Random Field Models and Discriminative Sparse Coding

Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features

Hybrid Gradient Boosting Trees and Neural Networks for Forecasting Operating Room Data

Cost-Sensitive Convolution based Neural Networks for Imbalanced Time-Series Classification

Towards social pattern characterization in egocentric photo-streams

Co-Morbidity Exploration on Wearables Activity Data Using Unsupervised Pre-training and Multi-Task Learning

Multi-task learning of time series and its application to the travel demand

Lost in Time: Temporal Analytics for Long-Term Video Surveillance

A Shapelet Transform for Multivariate Time Series Classification

Squeezed Convolutional Variational AutoEncoder for Unsupervised Anomaly Detection in Edge Device Industrial Internet of Things

Dynamic Boltzmann Machines for Second Order Moments and Generalized Gaussian Distributions

Hierarchical internal representation of spectral features in deep convolutional networks trained for EEG decoding

Spatial-temporal wind field prediction by Artificial Neural Networks

Complex-valued Gaussian Process Regression for Time Series Analysis

Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs

Generative Adversarial Networks for Electronic Health Records: A Framework for Exploring and Evaluating Methods for Predicting Drug-Induced Laboratory Test Trajectories

Cross-modal Recurrent Models for Weight Objective Prediction from Multimodal Time-series Data

Cascaded Region-based Densely Connected Network for Event Detection: A Seismic Application

Train, Diagnose and Fix: Interpretable Approach for Fine-grained Action Recognition

Attend and Diagnose: Clinical Time Series Analysis using Attention Models

Aggregated Wasserstein Metric and State Registration for Hidden Markov Models

PSF : Introduction to R Package for Pattern Sequence Based Forecasting Algorithm

Spatial Mapping with Gaussian Processes and Nonstationary Fourier Features

Deep-ESN: A Multiple Projection-encoding Hierarchical Reservoir Computing Framework

Sparsification of the Alignment Path Search Space in Dynamic Time Warping

Accelerating Neural Architecture Search using Performance Prediction

DeepRain: ConvLSTM Network for Precipitation Prediction using Multichannel Radar Data

Transform-Invariant Non-Parametric Clustering of Covariance Matrices and its Application to Unsupervised Joint Segmentation and Action Discovery

Robust Maximum Likelihood Estimation of Sparse Vector Error Correction Model

Anomaly Detection in Multivariate Non-stationary Time Series for Automatic DBMS Diagnosis

Classification of Time-Series Images Using Deep Convolutional Neural Networks

Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks

Discovering Playing Patterns: Time Series Clustering of Free-To-Play Game Data

Solving differential equations with unknown constitutive relations as recurrent neural networks

Forecasting Player Behavioral Data and Simulating in-Game Events

A signature-based machine learning model for bipolar disorder and borderline personality disorder

Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks

DeepTFP: Mobile Time Series Data Analytics based Traffic Flow Prediction

Model-free prediction of noisy chaotic time series by deep learning

Symbolic Analysis-based Reduced Order Markov Modeling of Time Series Data

Anomaly Detection for a Water Treatment System Using Unsupervised Machine Learning

Nonnegative matrix factorization with side information for time series recovery and prediction

Prolongation of SMAP to Spatio-temporally Seamless Coverage of Continental US Using a Deep Learning Neural Network

R2N2: Residual Recurrent Neural Networks for Multivariate Time Series Forecasting

LSTM Fully Convolutional Networks for Time Series Classification

Boosting the kernelized shapelets: Theory and algorithms for local features

A State-Space Approach to Dynamic Nonnegative Matrix Factorization

m-TSNE: A Framework for Visualizing High-Dimensional Multivariate Time Series

Position-based Content Attention for Time Series Forecasting with Sequence-to-sequence RNNs

An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection

Driving Style Analysis Using Primitive Driving Patterns With Bayesian Nonparametric Approaches

Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction

A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction

Deep Recurrent Neural Networks for mapping winter vegetation quality coverage via multi-temporal SAR Sentinel-1

Time Series Anomaly Detection; Detection of anomalous drops with limited features and sparse examples in noisy highly periodic data

Detecting early signs of depressive and manic episodes in patients with bipolar disorder using the signature-based model

Tensorial Recurrent Neural Networks for Longitudinal Data Analysis

A Comparative Study of the Clinical use of Motion Analysis from Kinect Skeleton Data

Out-of-Sample Extension for Dimensionality Reduction of Noisy Time Series

Direct Load Control of Thermostatically Controlled Loads Based on Sparse Observations Using Deep Reinforcement Learning

Neighborhood Features Help Detecting Non-Technical Losses in Big Data Sets

Exercise Motion Classification from Large-Scale Wearable Sensor Data Using Convolutional Neural Networks

Recovering Latent Signals from a Mixture of Measurements using a Gaussian Process Prior

Improving Sparsity in Kernel Adaptive Filters Using a Unit-Norm Dictionary

Initialising Kernel Adaptive Filters via Probabilistic Inference

DeepTrend: A Deep Hierarchical Neural Network for Traffic Flow Prediction

Distance-to-Mean Continuous Conditional Random Fields to Enhance Prediction Problem in Traffic Flow Data

Non-parametric Estimation of Stochastic Differential Equations with Sparse Gaussian Processes

Composition Properties of Inferential Privacy for Time-Series Data

Visual Analytics of Movement Pattern Based on Time-Spatial Data: A Neural Net Approach

Structured Black Box Variational Inference for Latent Time Series Models

DeepSense: A Unified Deep Learning Framework for Time-Series Mobile Sensing Data Processing

Time Series Cluster Kernel for Learning Similarities between Multivariate Time Series with Missing Data

Forecasting and Granger Modelling with Non-linear Dynamical Dependencies

Inference of High-dimensional Autoregressive Generalized Linear Models

TimeNet: Pre-trained deep recurrent neural network for time series classification

Short-Term Forecasting of Passenger Demand under On-Demand Ride Services: A Spatio-Temporal Deep Learning Approach

Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding

Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier

Direct detection of pixel-level myocardial infarction areas via a deep-learning algorithm

Krylov Subspace Recycling for Fast Iterative Least-Squares in Machine Learning

Modeling The Intensity Function Of Point Process Via Recurrent Neural Networks

Sequence Summarization Using Order-constrained Kernelized Feature Subspaces

Time Series Structure Discovery via Probabilistic Program Synthesis

Distributed and parallel time series feature extraction for industrial big data applications

Prediction of Sea Surface Temperature using Long Short-Term Memory

Practical Processing of Mobile Sensor Data for Continual Deep Learning Predictions

ShortFuse: Biomedical Time Series Representations in the Presence of Structured Information

Mosquito Detection with Neural Networks: The Buzz of Deep Learning

With Whom Do I Interact? Detecting Social Interactions in Egocentric Photo-streams

A Novel Approach to Forecasting Financial Volatility with Gaussian Process Envelopes

Estimating 3D Trajectories from 2D Projections via Disjunctive Factored Four-Way Conditional Restricted Boltzmann Machines

PPMF: A Patient-based Predictive Modeling Framework for Early ICU Mortality Prediction

Times series averaging and denoising from a probabilistic perspective on time-elastic kernels

Automatic Anomaly Detection in the Cloud Via Statistical Learning

A Deep Learning Framework using Passive WiFi Sensing for Respiration Monitoring

Learning Time Series Detection Models from Temporally Imprecise Labels

Land Cover Classification via Multi-temporal Spatial Data by Recurrent Neural Networks

Investigation on the use of Hidden-Markov Models in automatic transcription of music

The MATLAB Toolbox SciXMiner: User's Manual and Programmer's Guide

Automated Diagnosis of Epilepsy Employing Multifractal Detrended Fluctuation Analysis Based Features

Optimal Policies for Observing Time Series and Related Restless Bandit Problems

Novel Structured Low-rank algorithm to recover spatially smooth exponential image time series

Collective Anomaly Detection based on Long Short Term Memory Recurrent Neural Network

Simulated Data Experiments for Time Series Classification Part 1: Accuracy Comparison with Default Settings

Joint Modeling of Event Sequence and Time Series with Attentional Twin Recurrent Neural Networks

Asymmetric Learning Vector Quantization for Efficient Nearest Neighbor Classification in Dynamic Time Warping Spaces

Methods for Mapping Forest Disturbance and Degradation from Optical Earth Observation Data: a Review

Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks

Exploiting Spatio-Temporal Structure with Recurrent Winner-Take-All Networks

A Statistical Machine Learning Approach to Yield Curve Forecasting

Analyzing Linear Dynamical Systems: From Modeling to Coding and Learning

Video and Accelerometer-Based Motion Analysis for Automated Surgical Skills Assessment

Ensembles of Randomized Time Series Shapelets Provide Improved Accuracy while Reducing Computational Costs

Robust Clustering for Time Series Using Spectral Densities and Functional Data Analysis

Hierarchical Symbolic Dynamic Filtering of Streaming Non-stationary Time Series Data

Riemannian-geometry-based modeling and clustering of network-wide non-stationary time series: The brain-network case

Nonsmooth Analysis and Subgradient Methods for Averaging in Dynamic Time Warping Spaces

Fusing Deep Learned and Hand-Crafted Features of Appearance, Shape, and Dynamics for Automatic Pain Estimation

Towards prediction of rapid intensification in tropical cyclones with recurrent neural networks

Learning Linear Dynamical Systems with High-Order Tensor Data for Skeleton based Action Recognition

Stage 4 validation of the Satellite Image Automatic Mapper lightweight computer program for Earth observation Level 2 product generation, Part 2 Validation

See the Near Future: A Short-Term Predictive Methodology to Traffic Load in ITS

Multi-Region Neural Representation: A novel model for decoding visual stimuli in human brains

Multivariate Industrial Time Series with Cyber-Attack Simulation: Fault Detection Using an LSTM-based Predictive Data Model

Revisiting Causality Inference in Memory-less Transition Networks

Mixing Times and Structural Inference for Bernoulli Autoregressive Processes

Automatic time-series phenotyping using massive feature extraction

Time Series Classification from Scratch with Deep Neural Networks: A Strong Baseline

A Bayesian Nonparametric Approach for Estimating Individualized Treatment-Response Curves

Deep Symbolic Representation Learning for Heterogeneous Time-series Classification

Multiclass Classification of Cervical Cancer Tissues by Hidden Markov Model

Short-term traffic flow forecasting with spatial-temporal correlation in a hybrid deep learning framework

Positive blood culture detection in time series data using a BiLSTM network

Predicting Patient State-of-Health using Sliding Window and Recurrent Classifiers

A General Framework for Density Based Time Series Clustering Exploiting a Novel Admissible Pruning Strategy

Autism Spectrum Disorder Classification using Graph Kernels on Multidimensional Time Series

Representation Learning with Deconvolution for Multivariate Time Series Classification and Visualization

Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models

Earliness-Aware Deep Convolutional Networks for Early Time Series Classification

Optimal Transport vs. Fisher-Rao distance between Copulas for Clustering Multivariate Time Series

Low Latency Anomaly Detection and Bayesian Network Prediction of Anomaly Likelihood

Recurrent Neural Networks for Multivariate Time Series with Missing Values

The Case for Temporal Transparency: Detecting Policy Change Events in Black-Box Decision Making Systems

Analysis of Nonstationary Time Series Using Locally Coupled Gaussian Processes

A scalable end-to-end Gaussian process adapter for irregularly sampled time series classification

Gaussian Process Kernels for Popular State-Space Time Series Models

Multiple Regularizations Deep Learning for Paddy Growth Stages Classification from LANDSAT-8

Combining Generative and Discriminative Neural Networks for Sleep Stages Classification

Recovering Multiple Nonnegative Time Series From a Few Temporal Aggregates

End-to-End Radio Traffic Sequence Recognition with Deep Recurrent Neural Networks

Automatic Construction of a Recurrent Neural Network based Classifier for Vehicle Passage Detection

Derivative Delay Embedding: Online Modeling of Streaming Time Series

Regularized Dynamic Boltzmann Machine with Delay Pruning for Unsupervised Learning of Temporal Sequences

Predicting Future Shanghai Stock Market Price using ANN in the Period 21-Sep-2016 to 11-Oct-2016

Learning conditional independence structure for high-dimensional uncorrelated vector processes

Learning Temporal Dependence from Time-Series Data with Latent Variables

Multi-Sensor Prognostics using an Unsupervised Health Index based on LSTM Encoder-Decoder

Expectation Propagation in Gaussian Process Dynamical Systems: Extended Version

A Distance for HMMs based on Aggregated Wasserstein Metric and State Registration

Fuzzy c-Shape: A new algorithm for clustering finite time series waveforms

Size-Consistent Statistics for Anomaly Detection in Dynamic Networks

Automatic Generation of Probabilistic Programming from Time Series Data

Facial Expression Classification Using Rotation Slepian-based Moment Invariants

Adapting ELM to Time Series Classification: A Novel Diversified Top-k Shapelets Extraction Method

Note on Equivalence Between Recurrent Neural Network Time Series Models and Variational Bayesian Models

Exact Bayesian inference for off-line change-point detection in tree-structured graphical models

Variational Inference for On-line Anomaly Detection in High-Dimensional Time Series

Deep Recurrent Convolutional Networks for Video-based Person Re-identification: An End-to-End Approach

metricDTW: local distance metric learning in Dynamic Time Warping

On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis

Specific Differential Entropy Rate Estimation for Continuous-Valued Time Series

Variational Bayesian Inference for Hidden Markov Models With Multivariate Gaussian Output Distributions

Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA

Automatic Classification of Irregularly Sampled Time Series with Unequal Lengths: A Case Study on Estimated Glomerular Filtration Rate

Multi-Scale Convolutional Neural Networks for Time Series Classification

Temporal Clustering of Time Series via Threshold Autoregressive Models: Application to Commodity Prices

Unsupervised Representation Learning of Structured Radio Communication Signals

Skill-Based Differences in Spatio-Temporal Team Behavior in Defence of The Ancients 2

Action-Affect Classification and Morphing using Multi-Task Representation Learning

Short-term time series prediction using Hilbert space embeddings of autoregressive processes

Learning Network of Multivariate Hawkes Processes: A Time Series Approach

Scalable Linear Causal Inference for Irregularly Sampled Time Series with Long Range Dependencies

Modeling the Sequence of Brain Volumes by Local Mesh Models for Brain Decoding

Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks

Semi-Markov Switching Vector Autoregressive Model-based Anomaly Detection in Aviation Systems

The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM

The Great Time Series Classification Bake Off: An Experimental Evaluation of Recently Proposed Algorithms. Extended Version

Shape Distributions of Nonlinear Dynamical Systems for Video-based Inference

Improved graph-based SFA: Information preservation complements the slowness principle

Optimal Copula Transport for Clustering Multivariate Time Series

On Clustering Time Series Using Euclidean Distance and Pearson Correlation

Statistical and Computational Guarantees for the Baum-Welch Algorithm

Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components

Distilling Knowledge from Deep Networks with Applications to Healthcare Domain

Alternating direction method of multipliers for penalized zero-variance discriminant analysis

Stochastic Collapsed Variational Inference for Hidden Markov Models

A Survey: Time Travel in Deep Learning Space: An Introduction to Deep Learning Models and How Deep Learning Models Evolved from the Initial Ideas

Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series

Blitzkriging: Kronecker-structured Stochastic Gaussian Processes

Linear-time Detection of Non-linear Changes in Massively High Dimensional Time Series

Accelerometer based Activity Classification with Variational Inference on Sticky HDP-SLDS

Clustering Noisy Signals with Structured Sparsity Using Time-Frequency Representation

Optimizing and Contrasting Recurrent Neural Network Architectures

Dynamical spectral unmixing of multitemporal hyperspectral images

Data-Driven Learning of the Number of States in Multi-State Autoregressive Models

p-Markov Gaussian Processes for Scalable and Expressive Online Bayesian Nonparametric Time Series Forecasting

Spatially Encoding Temporal Correlations to Classify Temporal Data Using Convolutional Neural Networks

Forecasting Method for Grouped Time Series with the Use of k-Means Algorithm

Learning the Number of Autoregressive Mixtures in Time Series Using the Gap Statistics

Toward a generic representation of random variables for machine learning

Time-series modeling with undecimated fully convolutional neural networks

AMP: a new time-frequency feature extraction method for intermittent time-series data

Evaluation of Spectral Learning for the Identification of Hidden Markov Models

Early Recognition of Human Activities from First-Person Videos Using Onset Representations

Anomaly Detection and Removal Using Non-Stationary Gaussian Processes

Times series averaging from a probabilistic interpretation of time-elastic kernel

Generalized Gradient Learning on Time Series under Elastic Transformations

Empirical Studies on Symbolic Aggregation Approximation Under Statistical Perspectives for Knowledge Discovery in Time Series

Filter characteristics in image decomposition with singular spectrum analysis

A Bayesian approach for structure learning in oscillating regulatory networks

Video-Based Action Recognition Using Rate-Invariant Analysis of Covariance Trajectories

Sparse plus low-rank autoregressive identification in neuroimaging time series

Ranking and significance of variable-length similarity-based time series motifs

Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets

Learning the Conditional Independence Structure of Stationary Time Series: A Multitask Learning Approach

Techniques for clustering interaction data as a collection of graphs

An Empirical Study of the L2-Boost technique with Echo State Networks

A Direct Estimation of High Dimensional Stationary Vector Autoregressions

Joint Estimation of Multiple Graphical Models from High Dimensional Time Series

Variational inference of latent state sequences using Recurrent Networks

Short-term solar irradiance and irradiation forecasts via different time series techniques: A preliminary study

Automated Machine Learning on Big Data using Stochastic Algorithm Tuning

An Experimental Evaluation of Nearest Neighbour Time Series Classification

Interval Forecasting of Electricity Demand: A Novel Bivariate EMD-based Support Vector Regression Modeling Framework

Constructing Time Series Shape Association Measures: Minkowski Distance and Data Standardization

Effective Bayesian Modeling of Groups of Related Count Time Series

Implementing spectral methods for hidden Markov models with real-valued emissions

Meteorological time series forecasting based on MLP modelling using heterogeneous transfer functions

Estimating Time-varying Brain Connectivity Networks from Functional MRI Time Series

Ensemble Committees for Stock Return Classification and Prediction

Compressive Nonparametric Graphical Model Selection For Time Series

An Empirical Evaluation of Similarity Measures for Time Series Classification

Multi-Step-Ahead Time Series Prediction using Multiple-Output Support Vector Regression

Distinguishing noise from chaos: objective versus subjective criteria using Horizontal Visibility Graph

Model-based clustering with Hidden Markov Model regression for time series with regime changes

An Unsupervised Approach for Automatic Activity Recognition based on Hidden Markov Model Regression

Joint segmentation of multivariate time series with hidden process regression for human activity recognition

Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC

Classifiers With a Reject Option for Early Time-Series Classification

On Recursive Edit Distance Kernels with Application to Time Series Classification

A dependent partition-valued process for multitask clustering and time evolving network modelling

Gaussian Process Conditional Copulas with Applications to Financial Time Series

Sparse Principal Component Analysis for High Dimensional Vector Autoregressive Models

Reducing statistical time-series problems to binary classification

Infinite Shift-invariant Grouped Multi-task Learning for Gaussian Processes

Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data

Multiple Change Point Estimation in Stationary Ergodic Time Series

Structure Discovery in Nonparametric Regression through Compositional Kernel Search

Sparse/Robust Estimation and Kalman Smoothing with Nonsmooth Log-Concave Densities: Modeling, Computation, and Theory

Learning Heteroscedastic Models by Convex Programming under Group Sparsity

Sparsistent Estimation of Time-Varying Discrete Markov Random Fields

A consistent clustering-based approach to estimating the number of change-points in highly dependent time-series

Learning Graphical Models of Images, Videos and Their Spatial Transformations

Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation

Bag-of-Words Representation for Biomedical Time Series Classification

Changepoint detection for high-dimensional time series with missing data

Anomaly Detection in Time Series of Graphs using Fusion of Graph Invariants

Fast Randomized Model Generation for Shapelet-Based Time Series Classification

Learning LiNGAM based on data with more variables than observations

Causal Inference on Time Series using Structural Equation Models

Conditional Chow-Liu Tree Structures for Modeling Discrete-Valued Vector Time Series

Time Series Classification by Class-Specific Mahalanobis Distance Measures

Discrete Elastic Inner Vector Spaces with Application in Time Series and Sequence Mining

Residual Component Analysis: Generalising PCA for more flexible inference in linear-Gaussian models

Learning the Dependence Graph of Time Series with Latent Factors

Large-Scale Automatic Labeling of Video Events with Verbs Based on Event-Participant Interaction

A Nonparametric Frequency Domain EM Algorithm for Time Series Classification with Applications to Spike Sorting and Macro-Economics

A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition

Feature Extraction for Change-Point Detection using Stationary Subspace Analysis

Dynamic Large Spatial Covariance Matrix Estimation in Application to Semiparametric Model Construction via Variable Clustering: the SCE approach

Translating biomarkers between multi-way time-series experiments

Discovering shared and individual latent structure in multiple time series

Discovering Graphical Granger Causality Using the Truncating Lasso Penalty

Variational Inducing Kernels for Sparse Convolved Multiple Output Gaussian Processes

CanICA: Model-based extraction of reproducible group-level ICA patterns from fMRI time series

How slow is slow? SFA detects signals that are slower than the driving force

Prediction of Zoonosis Incidence in Human using Seasonal Auto Regressive Integrated Moving Average (SARIMA)

Finding Anomalous Periodic Time Series: An Application to Catalogs of Periodic Variable Stars

Ultrametric Wavelet Regression of Multivariate Time Series: Application to Colombian Conflict Analysis

Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing Maps

Using state space differential geometry for nonlinear blind source separation

Channel-Independent and Sensor-Independent Stimulus Representations

Mining Heterogeneous Multivariate Time-Series for Learning Meaningful Patterns: Application to Home Health Telecare

Automated Pattern Detection--An Algorithm for Constructing Optimally Synchronizing Multi-Regular Language Filters

L1 regularization is better than L2 for learning and predicting chaotic systems

Three-Stream 3D/1D CNN for Fine-Grained Action Classification and Segmentation in Table Tennis

Efficient Global-Local Memory for Real-time Instrument Segmentation of Robotic Surgical Video

FastAno: Fast Anomaly Detection via Spatio-temporal Patch Transformation

A Novel Factor Graph-Based Optimization Technique for Stereo Correspondence Estimation

3D-CNN for Facial Micro- and Macro-expression Spotting on Long Video Sequences using Temporal Oriented Reference Frame

Video Abnormal Event Detection by Learning to Complete Visual Cloze Tests

RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matching

What happens in Face during a facial expression? Using data mining techniques to analyze facial expression motion vectors

Spatio-Temporal Recurrent Networks for Event-Based Optical Flow Estimation

Temporally Coherent Person Matting Trained on Fake-Motion Dataset

DS-Net: Dynamic Spatiotemporal Network for Video Salient Object Detection

Towards Better Generalization: Joint Depth-Pose Learning without PoseNet

Anomaly Detection with Prototype-Guided Discriminative Latent Embeddings

SlowFast Rolling-Unrolling LSTMs for Action Anticipation in Egocentric Videos

FlowReg: Fast Deformable Unsupervised Medical Image Registration using Optical Flow

A Pedestrian Detection and Tracking Framework for Autonomous Cars: Efficient Fusion of Camera and LiDAR Data

Learning Cross-modal Contrastive Features for Video Domain Adaptation

Neural Image Representations for Multi-Image Fusion and Layer Separation

A Fine-Grained Visual Attention Approach for Fingerspelling Recognition in the Wild

HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset

MM-ViT: Multi-Modal Video Transformer for Compressed Video Action Recognition

Out-of-boundary View Synthesis Towards Full-Frame Video Stabilization

Learning RAW-to-sRGB Mappings with Inaccurately Aligned Supervision

A Hybrid Video Anomaly Detection Framework via Memory-Augmented Flow Reconstruction and Flow-Guided Frame Prediction

Deep Motion Prior for Weakly-Supervised Temporal Action Localization

RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation

Multi-Source Fusion and Automatic Predictor Selection for Zero-Shot Video Object Segmentation

Self-supervised Learning of Occlusion Aware Flow Guided 3D Geometry Perception with Adaptive Cross Weighted Loss from Monocular Videos

Model-free Vehicle Tracking and State Estimation in Point Cloud Sequences

Dual approach for object tracking based on optical flow and swarm intelligence

Self-Supervised Regional and Temporal Auxiliary Tasks for Facial Action Unit Recognition

Learning to Estimate Hidden Motions with Global Motion Aggregation

Spot What Matters: Learning Context Using Graph Convolutional Networks for Weakly-Supervised Action Detection

WiP Abstract : Robust Out-of-distribution Motion Detection and Localization in Autonomous CPS

Detail Preserving Residual Feature Pyramid Modules for Optical Flow

Progressive Deep Video Dehazing without Explicit Alignment Estimation

DDCNet-Multires: Effective Receptive Field Guided Multiresolution CNN for Dense Prediction

Two-Stream Consensus Network: Submission to HACS Challenge 2021 Weakly-Supervised Learning Track

BEV-MODNet: Monocular Camera based Bird's Eye View Moving Object Detection for Autonomous Driving

DDCNet: Deep Dilated Convolutional Neural Network for Dense Prediction

NccFlow: Unsupervised Learning of Optical Flow With Non-occlusion from Geometry

Cyclist Trajectory Forecasts by Incorporation of Multi-View Video Information

The U-Net based GLOW for Optical-Flow-free Video Interframe Generation

SDOF-Tracker: Fast and Accurate Multiple Human Tracking by Skipped-Detection and Optical-Flow

Class agnostic moving target detection by color and location prediction of moving area

Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting

CloudCast: A Satellite-Based Dataset and Baseline for Forecasting Clouds

Shallow Optical Flow Three-Stream CNN for Macro- and Micro-Expression Spotting from Long Videos

Spot the Difference: Topological Anomaly Detection via Geometric Alignment

Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow Estimation

Self-Supervised Learning of Event-Based Optical Flow with Spiking Neural Networks

How Do Neural Networks Estimate Optical Flow? A Neuropsychology-Inspired Study

UPFlow: Upsampling Pyramid for Unsupervised Optical Flow Learning

Unsupervised Joint Learning of Depth, Optical Flow, Ego-motion from Video

UVid-Net: Enhanced Semantic Segmentation of UAV Aerial Videos by Embedding Temporal Information

End-to-End Video Object Detection with Spatial-Temporal Transformers

DeepAVO: Efficient Pose Refining with Feature Distilling for Deep Visual Odometry

Leveraging Semantic Scene Characteristics and Multi-Stream Convolutional Architectures in a Contextual Approach for Video-Based Visual Emotion Recognition in the Wild

EffiScene: Efficient Per-Pixel Rigidity Inference for Unsupervised Joint Learning of Optical Flow, Depth, Camera Pose and Motion Segmentation

SMURF: Self-Teaching Multi-Frame Unsupervised RAFT with Full-Image Warping

Confidence-guided Adaptive Gate and Dual Differential Enhancement for Video Salient Object Detection

FDAN: Flow-guided Deformable Alignment Network for Video Super-Resolution

Video Frame Interpolation via Structure-Motion based Iterative Fusion

Video Anomaly Detection By The Duality Of Normality-Granted Optical Flow

Interaction Detection Between Vehicles and Vulnerable Road Users: A Deep Generative Approach with Attention

LASR: Learning Articulated Shape Reconstruction from a Monocular Video

FDNet: A Deep Learning Approach with Two Parallel Cross Encoding Pathways for Precipitation Nowcasting

Motion-Augmented Self-Training for Video Recognition at Smaller Scale

Prediction of clinical tremor severity using Rank Consistent Ordinal Regression

A Reinforcement-Learning-Based Energy-Efficient Framework for Multi-Task Video Analytics Pipeline

Deep Video Matting via Spatio-Temporal Alignment and Aggregation

Comparing Correspondences: Video Prediction with Correspondence-wise Losses

Learning Interpretable End-to-End Vision-Based Motion Planning for Autonomous Driving with Optical Flow Distillation

Visually Guided Sound Source Separation and Localization using Self-Supervised Motion Representations

Leveraging Category Information for Single-Frame Visual Sound Source Separation

FLAVR: Flow-Agnostic Video Representations for Fast Frame Interpolation

VOLDOR-SLAM: For the Times When Feature-Based or Direct Methods Are Not Good Enough

VOLDOR: Visual Odometry from Log-logistic Dense Optical flow Residuals

MESD: Exploring Optical Flow Assessment on Edge of Motion Objects with Motion Edge Structure Difference

Back to Event Basics: Self-Supervised Learning of Image Reconstruction for Event Cameras via Photometric Constancy

ASFlow: Unsupervised Optical Flow Learning with Adaptive Pyramid Sampling

Progressive Temporal Feature Alignment Network for Video Inpainting

Multi-hierarchical Convolutional Network for Efficient Remote Photoplethysmograph Signal and Heart Rate Estimation from Face Video Clips

GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network

GLU-Net: Global-Local Universal Network for Dense Flow and Correspondences

TTVOS: Lightweight Video Object Segmentation with Adaptive Template Attention Module and Temporal Consistency Loss

PDWN: Pyramid Deformable Warping Network for Video Interpolation

"Forget" the Forget Gate: Estimating Anomalies in Videos using Self-contained Long Short-Term Memory Networks

Low-Fidelity End-to-End Video Encoder Pre-training for Temporal Action Localization

What Causes Optical Flow Networks to be Vulnerable to Physical Adversarial Attacks

Generalizing to the Open World: Deep Visual Odometry with Online Adaptation

Real-Time and Accurate Object Detection in Compressed Video by Long Short-term Feature Aggregation

FastFlowNet: A Lightweight Network for Fast Optical Flow Estimation

Automatic Quantification of Facial Asymmetry using Facial Landmarks

Unsupervised Video Anomaly Detection via Normalizing Flows with Implicit Latent Features

Fusion-FlowNet: Energy-Efficient Optical Flow Estimation using Sensor Fusion and Deep Fused Spiking-Analog Network Architectures

Deep Learning for Vision-Based Fall Detection System: Enhanced Optical Dynamic Flow

Fast Video Salient Object Detection via Spatiotemporal Knowledge Distillation

Restore from Restored: Video Restoration with Pseudo Clean Video

ARVo: Learning All-Range Volumetric Correspondence for Video Deblurring

Unsupervised Motion Representation Enhanced Network for Action Recognition

Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets with Multi-stream Inputs

Normalized Convolution Upsampling for Refined Optical Flow Estimation

Video Action Recognition Using spatio-temporal optical flow video frames

Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency

Parallax estimation for push-frame satellite imagery: application to super-resolution and 3D surface modeling from Skysat products

CyclingNet: Detecting cycling near misses from video streams in complex urban scenes with deep learning

OAS-Net: Occlusion Aware Sampling Network for Accurate Optical Flow

Multiple Video Frame Interpolation via Enhanced Deformable Separable Convolution

Supervision by Registration and Triangulation for Landmark Detection

A Discrete Scheme for Computing Image's Weighted Gaussian Curvature

Temporal Spatial-Adaptive Interpolation with Deformable Refinement for Electron Microscopic Images

Feature refinement: An expression-specific feature learning and fusion method for micro-expression recognition

Optical Flow Techniques for Facial Expression Analysis -- a Practical Evaluation Study

Dynamic Facial Expression Recognition under Partial Occlusion with Optical Flow Reconstruction

Multi Modal Adaptive Normalization for Audio to Video Generation

Denoising-based Turbo Message Passing for Compressed Video Background Subtraction

Self-Supervised Joint Encoding of Motion and Appearance for First Person Action Recognition

Nothing But Geometric Constraints: A Model-Free Method for Articulated Object Pose Estimation

Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow Estimation

FPCR-Net: Feature Pyramidal Correlation and Residual Reconstruction for Semi-supervised Optical Flow Estimation

Independent Sign Language Recognition with 3D Body, Hands, and Face Reconstruction

3D attention mechanism for fine-grained classification of table tennis strokes using a Twin Spatio-Temporal Convolutional Neural Networks

HMFlow: Hybrid Matching Optical Flow Network for Small and Fast-Moving Objects

Abnormal Event Detection in Urban Surveillance Videos Using GAN and Transfer Learning

JOLO-GCN: Mining Joint-Centered Light-Weight Information for Skeleton-Based Action Recognition

The Analysis of Facial Feature Deformation using Optical Flow Algorithm

Conquering the CNN Over-Parameterization Dilemma: A Volterra Filtering Approach for Action Recognition

MonoComb: A Sparse-to-Dense Combination Approach for Monocular Scene Flow

Video Semantic Segmentation with Distortion-Aware Feature Correction

A Multi-stream Convolutional Neural Network for Micro-expression Recognition Using Optical Flow and EVM

FlowCaps: Optical Flow Estimation with Capsule Networks For Action Recognition

Self-Supervised Object-in-Gripper Segmentation from Robotic Motions

SSGP: Sparse Spatial Guided Propagation for Robust and Generic Interpolation

CoT-AMFlow: Adaptive Modulation Network with Co-Teaching Strategy for Unsupervised Optical Flow Estimation

Displacement-Invariant Matching Cost Learning for Accurate Optical Flow Estimation

Motion and Region Aware Adversarial Learning for Fall Detection with Thermal Imaging

Towards Accurate Human Pose Estimation in Videos of Crowded Scenes

IPN Hand: A Video Dataset and Benchmark for Real-Time Continuous Hand Gesture Recognition

RWF-2000: An Open Large Scale Video Database for Violence Detection

Learning Visual Voice Activity Detection with an Automatically Annotated Dataset

Robust Two-Stream Multi-Feature Network for Driver Drowsiness Detection

Hierarchical Attention Learning of Scene Flow in 3D Point Clouds

A Flow-Guided Mutual Attention Network for Video-Based Person Re-Identification

A Flow Base Bi-path Network for Cross-scene Video Crowd Understanding in Aerial View

Feature Flow: In-network Feature Flow Estimation for Video Object Detection

Mesh Guided One-shot Face Reenactment using Graph Convolutional Networks

PRAFlow_RVC: Pyramid Recurrent All-Pairs Field Transforms for Optical Flow Estimation in Robust Vision Challenge 2020

Improving Deep Video Compression by Resolution-adaptive Flow Coding

Real-Time Segmentation of Non-Rigid Surgical Tools based on Deep Learning and Tracking

Approaches, Challenges, and Applications for Deep Visual Odometry: Toward to Complicated and Emerging Areas

High-quality Panorama Stitching based on Asymmetric Bidirectional Optical Flow

Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events

Deep learning-based computer vision to recognize and classify suturing gestures in robot-assisted surgery

RespVAD: Voice Activity Detection via Video-Extracted Respiration Patterns

Unsupervised Learning of Depth, Optical Flow and Pose with Occlusion from 3D Geometry

MineNav: An Expandable Synthetic Dataset Based on Minecraft for Aircraft Visual Navigation

SegCodeNet: Color-Coded Segmentation Masks for Activity Detection from Wearable Cameras

Meta Learning Deep Visual Words for Fast Video Object Segmentation

DTVNet: Dynamic Time-lapse Video Generation via Single Still Image

Fast and Accurate Optical Flow based Depth Map Estimation from Light Fields

2nd Place Scheme on Action Recognition Track of ECCV 2020 VIPriors Challenges: An Efficient Optical Flow Stream Guided Framework

Tracking in Crowd is Challenging: Analyzing Crowd based on Physical Characteristics

PAN: Towards Fast Action Recognition via Learning Persistence of Appearance

A Novel Indoor Positioning System for unprepared firefighting scenarios

Memory-augmented Dense Predictive Coding for Video Representation Learning

Residual Frames with Efficient Pseudo-3D CNN for Human Action Recognition

A Differentiable Recurrent Surface for Asynchronous Event-Based Data

MuCAN: Multi-Correspondence Aggregation Network for Video Super-Resolution

Optical Flow Distillation: Towards Efficient and Stable Video Style Transfer

Novel View Synthesis on Unpaired Data by Conditional Deformable Variational Auto-Encoder

MotionSqueeze: Neural Motion Feature Learning for Video Understanding

Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation

Beyond Single Stage Encoder-Decoder Networks: Deep Decoders for Semantic Image Segmentation

LiteFlowNet3: Resolving Correspondence Ambiguity for More Accurate Optical Flow Estimation

Two-stream Fusion Model for Dynamic Hand Gesture Recognition using 3D-CNN and 2D-CNN Optical Flow guided Motion Template

Real-time high speed motion prediction using fast aperture-robust event-driven visual flow

Visually Guided Sound Source Separation using Cascaded Opponent Filter Network

Fusing Motion Patterns and Key Visual Information for Semantic Event Recognition in Basketball Videos

STaRFlow: A SpatioTemporal Recurrent Cell for Lightweight Multi-Frame Optical Flow Estimation

Real-time Embedded Person Detection and Tracking for Shopping Behaviour Analysis

Patient-Specific Domain Adaptation for Fast Optical Flow Based on Teacher-Student Knowledge Transfer

OccInpFlow: Occlusion-Inpainting Optical Flow Estimation by Unsupervised Learning

Road obstacles positional and dynamic features extraction combining object detection, stereo disparity maps and optical flow data

ViPR: Visual-Odometry-aided Pose Regression for 6DoF Camera Localization

FDFlowNet: Fast Optical Flow Estimation using a Deep Lightweight Network

ResFPN: Residual Skip Connections in Multi-Resolution Feature Pyramid Networks for Accurate Dense Pixel Matching

Pseudo-LiDAR Point Cloud Interpolation Based on 3D Motion Representation and Spatial Supervision

An initial attempt of combining visual selective attention with deep reinforcement learning

Self-Supervised Representation Learning for Visual Anomaly Detection

Differentiable Forward and Backward Fixed-Point Iteration Layers

Fall Detector Adapted to Nursing Home Needs through an Optical-Flow based CNN

End-to-end Learning for Inter-Vehicle Distance and Relative Velocity Estimation in ADAS with a Monocular Camera

3D human pose estimation with adaptive receptive fields and dilated temporal convolutions

AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures

CNN-based Patch Matching for Optical Flow with Thresholded Hinge Embedding Loss

Self-supervised Transfer Learning for Instance Segmentation through Physical Interaction

Analytic Signal Phase in $N-D$ by Linear Symmetry Tensor--fingerprint modeling

Mean Oriented Riesz Features for Micro Expression Classification

Towards Accurate Vehicle Behaviour Classification With Multi-Relational Graph Convolutional Networks

Rolling-Unrolling LSTMs for Action Anticipation from First-Person Video

Exploiting Inter-Frame Regional Correlation for Efficient Action Recognition

Ego-motion and Surrounding Vehicle State Estimation Using a Monocular Camera

Multi-modal Egocentric Activity Recognition using Audio-Visual Features

Subjective Annotation for a Frame Interpolation Benchmark using Artefact Amplification

Leveraging Photometric Consistency over Time for Sparsely Supervised Hand-Object Reconstruction

Multi-Task Learning of Generalizable Representations for Video Action Recognition

MaskFlownet: Asymmetric Feature Matching with Learnable Occlusion Mask

Flow2Stereo: Effective Self-Supervised Learning of Optical Flow and Stereo Matching

Optical Flow in Dense Foggy Scenes using Semi-Supervised Learning

Distilled Semantics for Comprehensive Scene Understanding from Videos

Learning Multi-Object Tracking and Segmentation from Automatic Annotations

Extremely Dense Point Correspondences using a Learned Feature Descriptor

Video-based Person Re-Identification using Gated Convolutional Recurrent Neural Networks

Spotting Macro- and Micro-expression Intervals in Long Video Sequences

Fully Automated Hand Hygiene Monitoring\\in Operating Room using 3D Convolutional Neural Network

Multi-Modal Domain Adaptation for Fine-Grained Action Recognition

A Lightweight Optical Flow CNN - Revisiting Data Fidelity and Regularization

Belief Propagation Reloaded: Learning BP-Layers for Labeling Problems

Occlusion Aware Unsupervised Learning of Optical Flow From Video

Temporal Interpolation of Geostationary Satellite Imagery with Task Specific Optical Flow

Joint Unsupervised Learning of Optical Flow and Egomotion with Bi-Level Optimization

Multimodal feature fusion for CNN-based gait recognition: an empirical comparison

Human Action Recognition using Local Two-Stream Convolution Neural Network Features and Support Vector Machines

Feasibility of Video-based Sub-meter Localization on Resource-constrained Platforms

Modality Compensation Network: Cross-Modal Adaptation for Action Recognition

First image then video: A two-stage network for spatiotemporal video denoising

EpO-Net: Exploiting Geometric Constraints on Dense Trajectories for Motion Saliency

Unsupervised Learning of Camera Pose with Compositional Re-estimation

Rethinking Motion Representation: Residual Frames with 3D ConvNets for Better Action Recognition

AD-VO: Scale-Resilient Visual Odometry Using Attentive Disparity Map

Implementation of the VBM3D Video Denoising Method and Some Variants

Efficient Video Semantic Segmentation with Labels Propagation and Refinement

DepthTransfer: Depth Extraction from Video Using Non-parametric Sampling

EventGAN: Leveraging Large Scale Image Datasets for Event Cameras

Flow-Distilled IP Two-Stream Networks for Compressed Video Action Recognition

RST-MODNet: Real-time Spatio-temporal Moving Object Detection for Autonomous Driving

Semi-Supervised Video Salient Object Detection Using Pseudo-Labels

Every Frame Counts: Joint Learning of Video Segmentation and Optical Flow

Learning Depth from Monocular Videos Using Synthetic Data: A Temporally-Consistent Domain Adaptation Approach

Learning End-To-End Scene Flow by Distilling Single Tasks Knowledge

MIMAMO Net: Integrating Micro- and Macro-motion for Video Emotion Recognition

FuseMODNet: Real-Time Camera and LiDAR based Moving Object Detection for robust low-light Autonomous Driving

Unsupervised Domain Adaptation by Optical Flow Augmentation in Semantic Segmentation

Detailed Surface Geometry and Albedo Recovery from RGB-D Video Under Natural Illumination

Sim2real transfer learning for 3D human pose estimation: motion to the rescue

Plug-in, Trainable Gate for Streamlining Arbitrary Neural Networks

Fast Learning of Temporal Action Proposal via Dense Boundary Generator

A Proposed Artificial intelligence Model for Real-Time Human Action Localization and Tracking

Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection

Learning Monocular Visual Odometry through Geometry-Aware Curriculum Learning

High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks

Unsupervised motion saliency map estimation based on optical flow inpainting

Robust and Computationally-Efficient Anomaly Detection using Powers-of-Two Networks

Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments

Video Person Re-Identification using Learned Clip Similarity Aggregation

Real-time monitoring of driver drowsiness on mobile platforms using 3D neural networks

OmniTrack: Real-time detection and tracking of objects, text and logos in video

Generating Human Action Videos by Coupling 3D Game Engines and Probabilistic Graphical Models

CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing

Coupled Generative Adversarial Network for Continuous Fine-grained Action Segmentation

Unsupervised Segmentation of Fire and Smoke from Infra-Red Videos

Global Temporal Representation based CNNs for Infrared Action Recognition

Deep End-to-End Alignment and Refinement for Time-of-Flight RGB-D Module

Multimodal Deep Models for Predicting Affective Responses Evoked by Movies

On the Importance of Video Action Recognition for Visual Lipreading

Temporally Consistent Depth Prediction with Flow-Guided Memory Units

Visuomotor Understanding for Representation Learning of Driving Scenes

Self-supervised Learning with Geometric Constraints in Monocular Video: Connecting Flow, Depth, and Camera

Learning Task-Specific Generalized Convolutions in the Permutohedral Lattice

MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and Enhancement

Bypass Enhancement RGB Stream Model for Pedestrian Action Recognition of Autonomous Vehicles

AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit Detection

Shallow Triple Stream Three-dimensional CNN (STSTNet) for Micro-expression Recognition

Video-based Bottleneck Detection utilizing Lagrangian Dynamics in Crowded Scenes

End-to-End Learning of Representations for Asynchronous Event-Based Data

Some Aspects of Geometric Computer Vision for Analysing Dynamical Scenes focusing Automotive Applications

Hallucinating IDT Descriptors and I3D Optical Flow Features for Action Recognition with CNNs

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation

What goes around comes around: Cycle-Consistency-based Short-Term Motion Prediction for Anomaly Detection using Generative Adversarial Networks

Mono-Stixels: Monocular depth reconstruction of dynamic street scenes

Restoration of Non-rigidly Distorted Underwater Images using a Combination of Compressive Sensing and Local Polynomial Image Representations

What Would You Expect? Anticipating Egocentric Actions with Rolling-Unrolling LSTMs and Modality Attention

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM

Learning Spatio-Temporal Features with Two-Stream Deep 3D CNNs for Lipreading

Real-Time Driver State Monitoring Using a CNN Based Spatio-Temporal Approach

Speed estimation evaluation on the KITTI benchmark based on motion and monocular depth information

Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic Understanding

Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video

Two-Stream Region Convolutional 3D Network for Temporal Activity Detection

An Adaptive Training-less System for Anomaly Detection in Crowd Scenes

Neuro-Optimization: Learning Objective Functions Using Neural Networks

Bridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence

DeGraF-Flow: Extending DeGraF Features for accurate and efficient sparse-to-dense optical flow estimation

Frame-Recurrent Video Inpainting by Robust Optical Flow Inference

DMC-Net: Generating Discriminative Motion Cues for Fast Compressed Video Action Recognition

Sparse data interpolation using the geodesic distance affinity space

Zoom-In-to-Check: Boosting Video Interpolation via Instance-level Discrimination

FastReg: Fast Non-Rigid Registration via Accelerated Optimisation on the Manifold of Diffeomorphisms

Attention-guided Network for Ghost-free High Dynamic Range Imaging

Self-Supervised Flow Estimation using Geometric Regularization with Applications to Camera Image and Grid Map Sequences

Hierarchical Discrete Distribution Decomposition for Match Density Estimation

Estimation of Linear Motion in Dense Crowd Videos using Langevin Model

VORNet: Spatio-temporally Consistent Video Inpainting for Object Removal

Unsupervised Moving Object Detection via Contextual Information Separation

IF-TTN: Information Fused Temporal Transformation Network for Video Action Recognition

Iterative Residual Refinement for Joint Optical Flow and Occlusion Estimation

Unsupervised Deep Epipolar Flow for Stationary or Dynamic Scenes

SDC - Stacked Dilated Convolution: A Unified Descriptor Network for Dense Matching Tasks

Deep Predictive Video Compression with Bi-directional Prediction

SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception

Architecture Search of Dynamic Cells for Semantic Video Segmentation

Evaluation of the Spatio-Temporal features and GAN for Micro-expression Recognition System

Multigrid Predictive Filter Flow for Unsupervised Learning on Videos

TAN: Temporal Affine Network for Real-Time Left Ventricle Anatomical Structure Analysis Based on 2D Ultrasound Videos

Machine Vision for Natural Gas Methane Emissions Detection Using an Infrared Camera

Unsupervised Learning of a Hierarchical Spiking Neural Network for Optical Flow Estimation: From Events to Global Motion Perception

Explicit Spatiotemporal Joint Relation Learning for Tracking Human Pose

Micro-expression detection in long videos using optical flow and recurrent neural networks

Technical Report on Visual Quality Assessment for Frame Interpolation

Dense Depth Estimation of a Complex Dynamic Scene without Explicit 3D Motion Estimation

Ontology Based Global and Collective Motion Patterns for Event Classification in Basketball Videos

Investigation on Combining 3D Convolution of Image Data and Optical Flow to Generate Temporal Action Proposals

Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation

Demonstration of Vector Flow Imaging using Convolutional Neural Networks

Sparse Representations for Object and Ego-motion Estimation in Dynamic Scenes

Characterizing Human Behaviours Using Statistical Motion Descriptor

Semantic Adversarial Network with Multi-scale Pyramid Attention for Video Classification

Exploiting temporal and depth information for multi-frame face anti-spoofing

Egocentric Vision-based Future Vehicle Localization for Intelligent Driving Assistance Systems

Unsupervised Learning of Dense Optical Flow, Depth and Egomotion from Sparse Event Data

Motion Equivariant Networks for Event Cameras with the Temporal Normalization Transform

Motion Compensated Dynamic MRI Reconstruction with Local Affine Optical Flow Estimation

Robustness Meets Deep Learning: An End-to-End Hybrid Pipeline for Unsupervised Learning of Egomotion

The Error is the Feature: how to Forecast Lightning using a Model Prediction Error

Never Forget: Balancing Exploration and Exploitation via Learning Optical Flow

Ego-motion Sensor for Unmanned Aerial Vehicles Based on a Single-Board Computer

Real-time Joint Object Detection and Semantic Segmentation Network for Automated Driving

Optical Flow augmented Semantic Segmentation networks for Automated Driving

Flow Based Self-supervised Pixel Embedding for Image Segmentation

Learning Independent Object Motion from Unlabelled Stereoscopic Videos

Rate-Accuracy Trade-Off In Video Classification With Deep Convolutional Neural Networks

Action Recognition for Depth Video using Multi-view Dynamic Images

An Optical Flow-Based Approach for Minimally-Divergent Velocimetry Data Interpolation

Uncertainty Estimates and Multi-Hypotheses Networks for Optical Flow

Unsupervised Event-based Learning of Optical Flow, Depth, and Egomotion

Learning On-Road Visual Control for Self-Driving Vehicles with Auxiliary Tasks

Two-stream convolutional networks for end-to-end learning of self-driving cars

TDAN: Temporally Deformable Alignment Network for Video Super-Resolution

Spatial-temporal Fusion Convolutional Neural Network for Simulated Driving Behavior Recognition

From Third Person to First Person: Dataset and Baselines for Synthesis and Retrieval

Adversarial Attacks for Optical Flow-Based Action Recognition Classifiers

Fast Semantic Segmentation on Video Using Block Motion-Based Feature Interpolation

An Efficient Optical Flow Based Motion Detection Method for Non-stationary Scenes

Learning to Steer by Mimicking Features from Heterogeneous Auxiliary Networks

Evolvement Constrained Adversarial Learning for Video Style Transfer

ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs

Asymmetric Bilateral Phase Correlation for Optical Flow Estimation in the Frequency Domain

Flow Fields: Dense Correspondence Fields for Highly Accurate Large Displacement Optical Flow Estimation

Learning for Video Super-Resolution through HR Optical Flow Estimation

Left Ventricle Segmentation via Optical-Flow-Net from Short-axis Cine MRI: Preserving the Temporal Coherence of Cardiac Motion

Joint Unsupervised Learning of Optical Flow and Depth by Watching Stereo Videos

Inter-BMV: Interpolation with Block Motion Vectors for Fast Semantic Segmentation on Video

Finding Correspondences for Optical Flow and Disparity Estimations using a Sub-pixel Convolution-based Encoder-Decoder Network

Predicting Future Instance Segmentation by Forecasting Convolutional Features

A Simple Framework to Leverage State-Of-The-Art Single-Image Super-Resolution Methods to Restore Light Fields

SymmNet: A Symmetric Convolutional Neural Network for Occlusion Detection

Temporal Interpolation as an Unsupervised Pretraining Task for Optical Flow Estimation

Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation

On-Orbit Smart Camera System to Observe Illuminated and Unilluminated Space Objects

DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency

Temporally Coherent Video Harmonization Using Adversarial Networks

Unsupervised Video Object Segmentation using Motion Saliency-Guided Spatio-Temporal Propagation

Optical Flow Super-Resolution Based on Image Guidence Using Convolutional Neural Network

Hallucinating Dense Optical Flow from Sparse Lidar for Autonomous Vehicles

AAD: Adaptive Anomaly Detection through traffic surveillance videos

Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognition

FusionNet and AugmentedFlowNet: Selective Proxy Ground Truth for Training on Unlabeled Images

Every Pixel Counts: Unsupervised Geometry Learning with Holistic 3D Motion Understanding

EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Cameras

Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow Estimation

Hierarchical Metric Learning and Matching for 2D and 3D Geometric Correspondences

Motion Feature Network: Fixed Motion Filter for Action Recognition

Leveraging Motion Priors in Videos for Improving Human Segmentation

Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimation

Multimodal Classification with Deep Convolutional-Recurrent Neural Networks for Electroencephalography

Signal Alignment for Humanoid Skeletons via the Globally Optimal Reparameterization Algorithm

Three for one and one for three: Flow, Segmentation, and Surface Normals

Cross Pixel Optical Flow Similarity for Self-Supervised Learning

Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation

Optical Flow Based Real-time Moving Object Detection in Unconstrained Scenes

Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition

Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors

Modeling Spatio-Temporal Human Track Structure for Action Localization

Accurate and efficient video de-fencing using convolutional neural networks and temporal information

PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume

Best Vision Technologies Submission to ActivityNet Challenge 2018-Task: Dense-Captioning Events in Videos

CNN-based Action Recognition and Supervised Domain Adaptation on 3D Body Skeletons via Kernel Feature Maps

Task-Relevant Object Discovery and Categorization for Playing First-person Shooter Games

Simultaneous Optical Flow and Segmentation (SOFAS) using Dynamic Vision Sensor

Im2Flow: Motion Hallucination from Static Images for Action Recognition

Anomaly Detection and Localization in Crowded Scenes by Motion-field Shape Description and Similarity-based Statistical Learning

A Convolutional Feature Map based Deep Network targeted towards Traffic Detection and Classification

Cubes3D: Neural Network based Optical Flow in Omnidirectional Image Scenes

Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning

LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation

Joint direct estimation of 3D geometry and 3D motion using spatio temporal gradients

ABMOF: A Novel Optical Flow Algorithm for Dynamic Vision Sensors

Layered Optical Flow Estimation Using a Deep Neural Network with a Soft Mask

FlowFields++: Accurate Optical Flow Correspondences Meet Robust Interpolation

Low-Latency Human Action Recognition with Weighted Multi-Region Convolutional Neural Network

Learning Optical Flow via Dilated Networks and Occlusion Reasoning

Object Tracking in Satellite Videos Based on a Multi-Frame Optical Flow Tracker

End-to-end Video-level Representation Learning for Action Recognition

Temporal Unknown Incremental Clustering (TUIC) Model for Analysis of Traffic Surveillance Videos

Boundary Flow: A Siamese Network that Predicts Boundary Motion without Training on Motion

A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimation

End-to-End Learning of Motion Representation for Video Understanding

CNN in MRF: Video Object Segmentation via Inference in A CNN-Based Higher-Order Spatio-Temporal MRF

What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation?

Multi-Scale Video Frame-Synthesis Network with Transitive Consistency Loss

Queuing Theory Guided Intelligent Traffic Scheduling through Video Analysis using Dirichlet Process Mixture Model

GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose

A Feature Clustering Approach Based on Histogram of Oriented Optical Flow and Superpixels

End-to-end Flow Correlation Tracking with Spatial-temporal Attention

Instance Embedding Transfer to Unsupervised Video Object Segmentation

ActionFlowNet: Learning Motion Representation for Action Recognition

Less is More: Micro-expression Recognition from Video using Apex Frame

Robust Deformation Estimation in Wood-Composite Materials using Variational Optical Flow

Video Event Recognition and Anomaly Detection by Combining Gaussian Process and Hierarchical Dirichlet Process Models

Improving Multiple Object Tracking with Optical Flow and Edge Preprocessing

Plug-and-Play CNN for Crowd Motion Analysis: An Application in Abnormal Event Detection

Combining Stereo Disparity and Optical Flow for Basic Scene Flow

Light Field Super-Resolution using a Low-Rank Prior and Deep Convolutional Neural Networks

The ParallelEye Dataset: Constructing Large-Scale Artificial Scenes for Traffic Vision Research

Video Classification With CNNs: Using The Codec As A Spatio-Temporal Activity Sensor

LS-VO: Learning Dense Optical Subspace for Robust Visual Odometry Estimation

Dense Optical Flow based Change Detection Network Robust to Difference of Camera Viewpoints

Hierarchical Video Generation from Orthogonal Information: Optical Flow and Texture

UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss

Unsupervised learning of object frames by dense equivariant image labelling

3D Trajectory Reconstruction of Dynamic Objects Using Planarity Constraints

No Reference Stereoscopic Video Quality Assessment Using Joint Motion and Depth Statistics

Spatio-Temporal Saliency Networks for Dynamic Saliency Prediction

Vertical Landing for Micro Air Vehicles using Event-Based Optical Flow

Two-stream Collaborative Learning with Spatial-Temporal Attention for Video Classification

TransFlow: Unsupervised Motion Flow by Joint Geometric and Pixel-level Estimation

Spiking Optical Flow for Event-based Sensors Using IBM's TrueNorth Neurosynaptic System

Compressive Online Robust Principal Component Analysis with Optical Flow for Video Foreground-Background Separation

Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model

SegFlow: Joint Learning for Video Object Segmentation and Optical Flow

ClickBAIT: Click-based Accelerated Incremental Training of Convolutional Neural Networks

Abnormal Event Detection in Videos using Generative Adversarial Nets

Two-stream Flow-guided Convolutional Attention Networks for Action Recognition

Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras

Human Action Recognition System using Good Features and Multilayer Perceptron Network

Activity Recognition based on a Magnitude-Orientation Stream Network

MirrorFlow: Exploiting Symmetries in Joint Optical Flow and Occlusion Estimation

Segmentation-Aware Convolutional Networks Using Local Attention Masks

Video Deblurring via Semantic Segmentation and Pixel-Wise Non-Linear Kernel

Occlusion Handling using Semantic Segmentation and Visibility-Based Rendering for Mixed Reality

Large-scale, Fast and Accurate Shot Boundary Detection through Spatio-temporal Convolutional Neural Networks

One-Step Time-Dependent Future Video Frame Prediction with a Convolutional Encoder-Decoder Neural Network

Deep Optical Flow Estimation Via Multi-Scale Correspondence Structure Learning

End-to-End Learning of Video Super-Resolution with Motion Compensation

YoTube: Searching Action Proposal via Recurrent and Static Regression Networks

AdaScan: Adaptive Scan Pooling in Deep Convolutional Neural Networks for Human Action Recognition in Videos

Endoscopic Depth Measurement and Super-Spectral-Resolution Imaging

Block-Matching Optical Flow for Dynamic Vision Sensor- Algorithm and FPGA Implementation

Learning without Prejudice: Avoiding Bias in Webly-Supervised Action Recognition

Leveraging Structural Context Models and Ranking Score Fusion for Human Interaction Prediction

Learning Spatiotemporal Features for Infrared Action Recognition with 3D Convolutional Neural Networks

Single Image Action Recognition by Predicting Space-Time Saliency

Motion Prediction Under Multimodality with Conditional Stochastic Networks

STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling

Spatio-Temporal Facial Expression Recognition Using Convolutional Neural Networks and Conditional Random Fields

Joint Semantic and Motion Segmentation for dynamic scenes using Deep Convolutional Networks

A Nuclear-norm Model for Multi-Frame Super-Resolution Reconstruction from Video Clips

Hybrid Learning of Optical Flow and Next Frame Prediction to Boost Optical Flow in the Wild

Ordered Pooling of Optical Flow Sequences for Action Recognition

Google Map Aided Visual Navigation for UAVs in GPS-denied Environment

Saliency-guided video classification via adaptively weighted learning

Optical Flow-based 3D Human Motion Estimation from Monocular Video

Learning Rank Reduced Interpolation with Principal Component Analysis

InterpoNet, A brain inspired neural network for optical flow dense interpolation

An Analysis of Parallelized Motion Masking Using Dual-Mode Single Gaussian Models

Optical Flow Requires Multiple Strategies (but only one network)

SceneNet RGB-D: 5M Photorealistic Images of Synthetic Indoor Trajectories with Ground Truth

Real-Time Optical flow-based Video Stabilization for Unmanned Aerial Vehicles

Objective Micro-Facial Movement Detection Using FACS-Based Regions and Baseline Evaluation

A Maximum A Posteriori Estimation Framework for Robust High Dynamic Range Video Synthesis

FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

Estimating motion with principal component regression strategies

Regularized Pel-Recursive Motion Estimation Using Generalized Cross-Validation and Spatial Adaptation

Deep learning based fence segmentation and removal from an image using a video sequence

Short-term prediction of localized cloud motion using ground-based sky imagers

Crossing the Road Without Traffic Lights: An Android-based Safety Device

Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies

FALDOI: A new minimization strategy for large displacement variational optical flow

Pose from Action: Unsupervised Learning of Pose Features based on Motion

Efficient Two-Stream Motion and Appearance 3D CNNs for Video Classification

Exploiting Semantic Information and Deep Matching for Optical Flow

Back to Basics: Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness

Real-Time Intensity-Image Reconstruction for Event Cameras Using Manifold Regularisation

Deep Learning for Detecting Multiple Space-Time Action Tubes in Videos

Joint Optical Flow and Temporally Consistent Semantic Segmentation

Nonrigid Optical Flow Ground Truth for Real-World Scenes with Time-Varying Shading Effects

Dynamical optical flow of saliency maps for predicting visual attention

Covariance of Motion and Appearance Featuresfor Spatio Temporal Recognition Tasks

Spontaneous Subtle Expression Detection and Recognition based on Facial Strain

Point-wise mutual information-based video segmentation with high temporal consistency

DeepMovie: Using Optical Flow and Deep Neural Networks to Stylize Movies

Robust Optical Flow Estimation of Double-Layer Images under Transparency or Reflection

Full Flow: Optical Flow Estimation By Global Optimization over Regular Grids

Beyond Brightness Constancy: Learning Noise Models for Optical Flow

It's Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos

Position and Vector Detection of Blind Spot motion with the Horn-Schunck Optical Flow

Illumination-invariant image mosaic calculation based on logarithmic search

Dynamic Scene Deblurring using a Locally Adaptive Linear Blur Model

Drift Robust Non-rigid Optical Flow Enhancement for Long Sequences

A diffusion and clustering-based approach for finding coherent motions and understanding crowd scenes

A Semi-Automated Method for Object Segmentation in Infant's Egocentric Videos to Study Object Perception

Learning to Extract Motion from Videos in Convolutional Neural Networks

Solving Dense Image Matching in Real-Time using Discrete-Continuous Optimization

Unsupervised convolutional neural networks for motion estimation

Sparse Coding with Fast Image Alignment via Large Displacement Optical Flow

A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation

Coherent Motion Segmentation in Moving Camera Videos using Optical Flow Orientations

A Dual Fast and Slow Feature Interaction in Biologically Inspired Visual Recognition of Human Action

Parallel software implementation of recursive multidimensional digital filters for point-target detection in cluttered infrared scenes

Sparsity Based Methods for Overparameterized Variational Problems

A massively parallel multi-level approach to a domain decomposition method for the optical flow estimation with varying illumination

Simulation of optical flow and fuzzy based obstacle avoidance system for mobile robots

Video Compressive Sensing for Spatial Multiplexing Cameras using Motion-Flow Models

A Deep-structured Conditional Random Field Model for Object Silhouette Tracking

EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow

A robust and efficient video representation for action recognition

A spectral optical flow method for determining velocities from digital imagery

MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking

A Brief Survey of Recent Edge-Preserving Smoothing Algorithms on Digital Images

Multi-Action Recognition via Stochastic Modelling of Optical Flow and Gradients

Multidimensional Digital Filters for Point-Target Detection in Cluttered Infrared Scenes

Two-Stream Convolutional Networks for Action Recognition in Videos

Tracking Individual Targets in High Density Crowd Scenes Analysis of a Video Recording in Hajj 2009

Aggregation of local parametric candidates with exemplar-based occlusion handling for optical flow

Combining Spatio-Temporal Appearance Descriptors and Optical Flow for Human Action Recognition in Video Data

Head Gesture Recognition using Optical Flow based Classification with Reinforcement of GMM based Background Subtraction

Improved Anomaly Detection in Crowded Scenes via Cell-based Analysis of Foreground Speed, Size and Texture

A Unified Approach for Modeling and Recognition of Individual Actions and Group Activities

Vision-Based Navigation III: Pose and Motion from Omnidirectional Optical Flow and a Digital Terrain Map

Vision-Based Navigation II: Error Analysis for a Navigation Algorithm based on Optical-Flow and a Digital Terrain Map

A Framework for Real-Time Face and Facial Feature Tracking using Optical Flow Pre-estimation and Template Tracking

Gesture Recognition with a Focus on Important Actions by Using a Path Searching Method in Weighted Graph

Camera motion estimation through planar deformation determination

Total Variation Minimization and Graph Cuts for Moving Objects Segmentation

FORK: A Forward-Looking Actor For Model-Free Reinforcement Learning

Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth Function Approximation

Energy Aware Deep Reinforcement Learning Scheduling for Sensors Correlated in Time and Space

Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization

Formulation and validation of a car-following model based on deep reinforcement learning

A Theoretical Connection Between Statistical Physics and Reinforcement Learning

Information-Bottleneck-Based Behavior Representation Learning for Multi-agent Reinforcement learning

Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond

MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research

Efficiently Training On-Policy Actor-Critic Networks in Robotic Deep Reinforcement Learning with Demonstration-like Sampled Exploration

Reinforcement Learning and its Connections with Neuroscience and Psychology

MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning

Prioritized Experience-based Reinforcement Learning with Human Guidance: Methdology and Application to Autonomous Driving

LINDA: Multi-Agent Local Information Decomposition for Awareness of Teammates

L$^{2}$NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning

Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms

NICE: Robust Scheduling through Reinforcement Learning-Guided Integer Programming

Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment

A Graph Policy Network Approach for Volt-Var Control in Power Distribution Systems

Combing Policy Evaluation and Policy Improvement in a Unified f-Divergence Framework

Learnable Triangulation for Deep Learning-based 3D Reconstruction of Objects of Arbitrary Topology from Single RGB Images

A dynamic programming algorithm for informative measurements and near-optimal path-planning

Regularization Guarantees Generalization in Bayesian Reinforcement Learning through Algorithmic Stability

Parameter-Free Deterministic Reduction of the Estimation Bias in Continuous Control

Improved Soft Actor-Critic: Mixing Prioritized Off-Policy Samples with On-Policy Experience

Dimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning

Learning-Based Path Planning for Long-Range Autonomous Valet Parking

A Workflow for Offline Model-Free Robotic Reinforcement Learning

Expected Scalarised Returns Dominance: A New Solution Concept for Multi-Objective Decision Making

Estimation Error Correction in Deep Reinforcement Learning for Deterministic Actor-Critic Methods

Offline reinforcement learning with uncertainty for treatment strategies in sepsis

On Bonus-Based Exploration Methods in the Arcade Learning Environment

Jointly Learning Environments and Control Policies with Projected Stochastic Gradient Ascent

High-dimensional Bayesian Optimization for CNN Auto Pruning with Clustering and Rollback

Transient Non-Stationarity and Generalisation in Deep Reinforcement Learning

MEPG: A Minimalist Ensemble Policy Gradient Framework for Deep Reinforcement Learning

Tianshou: a Highly Modularized Deep Reinforcement Learning Library

Benchmarking Lane-changing Decision-making for Deep Reinforcement Learning

ES-ENAS: Blackbox Optimization over Hybrid Spaces via Combinatorial and Continuous Evolution

Deep Policies for Online Bipartite Matching: A Reinforcement Learning Approach

Whittle index based Q-learning for restless bandits with average reward

Learning offline: memory replay in biological and artificial reinforcement learning

LS3: Latent Space Safe Sets for Long-Horizon Visuomotor Control of Sparse Reward Iterative Tasks

A Simple Unified Framework for Anomaly Detection in Deep Reinforcement Learning

Context-Specific Representation Abstraction for Deep Option Learning

Reinforcement Learning for Finite-Horizon Restless Multi-Armed Multi-Action Bandits

IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Control

PowerGym: A Reinforcement Learning Environment for Volt-Var Control in Power Distribution Systems

CARL: Conditional-value-at-risk Adversarial Reinforcement Learning

EMVLight: A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles

Lifelong Robotic Reinforcement Learning by Retaining Experiences

Regularize! Don't Mix: Multi-Agent Reinforcement Learning without Explicit Centralized Structures

Greedy UnMixing for Q-Learning in Multi-Agent Reinforcement Learning

Multimodal Reward Shaping for Efficient Exploration in Reinforcement Learning

TFPnP: Tuning-free Plug-and-Play Proximal Algorithm with Applications to Inverse Imaging Problems

WarpDrive: Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU

Exploring the Robustness of Distributional Reinforcement Learning against Noisy State Observations

Leveraging Non-uniformity in First-order Non-convex Optimization

Integrating Deep Reinforcement and Supervised Learning to Expedite Indoor Mapping

Smoothed functional-based gradient algorithms for off-policy reinforcement learning: A non-asymptotic viewpoint

Dropout's Dream Land: Generalization from Learned Simulators to Reality

Accelerating Offline Reinforcement Learning Application in Real-Time Bidding and Recommendation: Potential Use of Simulation

RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning

Comparison and Unification of Three Regularization Methods in Batch Reinforcement Learning

Conservative Data Sharing for Multi-Task Offline Reinforcement Learning

Adversarial Attacks Against Deep Reinforcement Learning Framework in Internet of Vehicles

Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual Patterns

DCUR: Data Curriculum for Teaching via Samples with Reinforcement Learning

DROMO: Distributionally Robust Offline Model-based Policy Optimization

Teaching Agents how to Map: Spatial Reasoning for Multi-Object Navigation

A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning

Back to Basics: Deep Reinforcement Learning in Traffic Signal Control

Optimal Cycling of a Heterogenous Battery Bank via Reinforcement Learning

What Does The User Want? Information Gain for Hierarchical Dialogue Policy Optimisation

Convergence of a Human-in-the-Loop Policy-Gradient Algorithm With Eligibility Trace Under Reward, Policy, and Advantage Feedback

Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Reinforcement Learning

ROMAX: Certifiably Robust Deep Multiagent Reinforcement Learning via Convex Relaxation

Towards optimized actions in critical situations of soccer games with deep reinforcement learning

DSDF: An approach to handle stochastic agents in collaborative multi-agent reinforcement learning

Vision Transformer for Learning Driving Policies in Complex Multi-Agent Environments

Theoretical Guarantees of Fictitious Discount Algorithms for Episodic Reinforcement Learning and Global Convergence of Policy Gradient Methods

Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach

Uniform Generalization Bounds for Overparameterized Neural Networks

Systematic Generalisation through Task Temporal Logic and Deep Reinforcement Learning

RADARS: Memory Efficient Reinforcement Learning Aided Differentiable Neural Architecture Search

HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation

Concave Utility Reinforcement Learning with Zero-Constraint Violations

Optimizing a domestic battery and solar photovoltaic system with deep reinforcement learning

Projected State-action Balancing Weights for Offline Reinforcement Learning

OPIRL: Sample Efficient Off-Policy Inverse Reinforcement Learning via Distribution Matching

Self-supervised Reinforcement Learning with Independently Controllable Subgoals

TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting

On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)

Where Did You Learn That From? Surprising Effectiveness of Membership Inference Attacks Against Temporally Correlated Data in Deep Reinforcement Learning

Challenges and Countermeasures for Adversarial Attacks on Deep Reinforcement Learning

A Deep Reinforcement Learning Approach for Constrained Online Logistics Route Assignment

Convergence of Batch Asynchronous Stochastic Approximation With Applications to Reinforcement Learning

ADER:Adapting between Exploration and Robustness for Actor-Critic Methods

Optimizing Quantum Variational Circuits with Deep Reinforcement Learning

DRIVE: Deep Reinforced Accident Anticipation with Visual Explanation

Hindsight Reward Tweaking via Conditional Deep Reinforcement Learning

Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach

Using Logical Specifications of Objectives in Multi-Objective Reinforcement Learning

Mean-Variance Efficient Reinforcement Learning by Expected Quadratic Utility Maximization

Soft Hierarchical Graph Recurrent Networks for Many-Agent Partially Observable Environments

Eden: A Unified Environment Framework for Booming Reinforcement Learning Algorithms

Approximate information state for approximate planning and reinforcement learning in partially observed systems

Multi-agent Natural Actor-critic Reinforcement Learning Algorithms

Provably Safe Model-Based Meta Reinforcement Learning: An Abstraction-Based Approach

Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation

Reinforcement Learning for Battery Energy Storage Dispatch augmented with Model-based Optimizer

A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning

SocialAI: Benchmarking Socio-Cognitive Abilities in Deep Reinforcement Learning Agents

Catastrophic Interference in Reinforcement Learning: A Solution Based on Context Division and Knowledge Distillation

Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning

Communication-Computation Efficient Device-Edge Co-Inference via AutoML

Dynamic Pricing on E-commerce Platform with Deep Reinforcement Learning: A Field Experiment

Deep Reinforcement Learning at the Edge of the Statistical Precipice

Adaptive perturbation adversarial training: based on reinforcement learning

Integrated Decision and Control at Multi-Lane Intersections with Mixed Traffic Flow

Learning Meta Representations for Agents in Multi-Agent Reinforcement Learning

A Policy Efficient Reduction Approach to Convex Constrained Deep Reinforcement Learning

Autonomous Curiosity for Real-Time Training Onboard Robotic Agents

Influence-based Reinforcement Learning for Intrinsically-motivated Agents

Reinforcement Learning based Condition-oriented Maintenance Scheduling for Flow Line Systems

DexMV: Imitation Learning for Dexterous Manipulation from Human Videos

Reinforcement Learning-powered Semantic Communication via Semantic Similarity

Federated Reinforcement Learning: Techniques, Applications, and Open Challenges

Glimpse-Attend-and-Explore: Self-Attention for Active Visual Exploration

End-to-End Urban Driving by Imitating a Reinforcement Learning Coach

Neural Network iLQR: A Reinforcement Learning Architecture for Trajectory Optimization

Model-based Chance-Constrained Reinforcement Learning via Separated Proportional-Integral Lagrangian

Adaptive Control of Differentially Private Linear Quadratic Systems

Deep Reinforcement Learning in Computer Vision: A Comprehensive Survey

Memory-Augmented Reinforcement Learning for Image-Goal Navigation

Entropy-Aware Model Initialization for Effective Exploration in Deep Reinforcement Learning

Stochastic Treatment Recommendation with Deep Survival Dose Response Function (DeepSDRF)

Power Grid Cascading Failure Mitigation by Reinforcement Learning

Collect & Infer -- a fresh look at data-efficient Reinforcement Learning

Online Reinforcement Learning of Optimal Threshold Policies for Markov Decision Processes

BlockCopy: High-Resolution Video Processing with Block-Sparse Feature Propagation and Online Policies

Social NCE: Contrastive Learning of Socially-aware Motion Representations

Jointly-Learned State-Action Embedding for Efficient Reinforcement Learning

PatchMatch-RL: Deep MVS with Pixelwise Depth, Normal, and Visibility

Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning

Planning with Learned Dynamic Model for Unsupervised Point Cloud Registration

Global Convergence of the ODE Limit for Online Actor-Critic Algorithms in Reinforcement Learning

Trends in Neural Architecture Search: Towards the Acceleration of Search

Prior Is All You Need to Improve the Robustness and Safety for the First Time Deployment of Meta RL

Corruption-robust exploration in episodic reinforcement learning

Explainable Deep Reinforcement Learning Using Introspection in a Non-episodic Task

Robustifying Reinforcement Learning Policies with $\mathcal{L}_1$ Adaptive Control

Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay

Revisiting State Augmentation methods for Reinforcement Learning with Stochastic Delays

Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching

Mean-Field Controls with Q-learning for Cooperative MARL: Convergence and Complexity Analysis

Using Cyber Terrain in Reinforcement Learning for Penetration Testing

Introduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementation

Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach

Offline-Online Reinforcement Learning for Energy Pricing in Office Demand Response: Lowering Energy and Data Costs

A Microscopic Pandemic Simulator for Pandemic Prediction Using Scalable Million-Agent Reinforcement Learning

Fractional Transfer Learning for Deep Model-Based Reinforcement Learning

Deep Reinforcement Learning for L3 Slice Localization in Sarcopenia Assessment

Deep Reinforcement Learning for Electric Vehicle Routing Problem with Time Windows

Continual Backprop: Stochastic Gradient Descent with Persistent Randomness

Q-Mixing Network for Multi-Agent Pathfinding in Partially Observable Grid Environments

A functional mirror ascent view of policy gradient methods with function approximation

Reinforcement Learning Approach to Active Learning for Image Classification

Learning Test-time Augmentation for Content-based Image Retrieval

Robust Learning-Based Control via Bootstrapped Multiplicative Noise

Gap-Dependent Unsupervised Exploration for Reinforcement Learning

Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation

An Approach to Partial Observability in Games: Learning to Both Act and Observe

Truncated Emphatic Temporal Difference Methods for Prediction and Control

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction

Safe Deep Reinforcement Learning for Multi-Agent Systems with Continuous Action Spaces

Ask&Confirm: Active Detail Enriching for Cross-Modal Retrieval with Partial Query

Globally Optimal Hierarchical Reinforcement Learning for Linearly-Solvable Markov Decision Processes

Deep Reinforcement Learning for Demand Driven Services in Logistics and Transportation Systems: A Survey

Incorporation of Deep Neural Network & Reinforcement Learning with Domain Knowledge

Efficient Hyperparameter Optimization for Differentially Private Deep Learning

Adaptive Anomaly Detection for Internet of Things in Hierarchical Edge Computing: A Contextual-Bandit Approach

Whittle Index for A Class of Restless Bandits with Imperfect Observations

Mis-spoke or mis-lead: Achieving Robustness in Multi-Agent Communicative Reinforcement Learning

Meta-Reinforcement Learning in Broad and Non-Parametric Environments

Online Bootstrap Inference For Policy Evaluation in Reinforcement Learning

Efficient Representation for Electric Vehicle Charging Station Operations using Reinforcement Learning

Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning

Optimizing Large-Scale Fleet Management on a Road Network using Multi-Agent Deep Reinforcement Learning with Graph Neural Network

Building a Foundation for Data-Driven, Interpretable, and Robust Policy Design using the AI Economist

Inverse Reinforcement Learning Based Stochastic Driver Behavior Learning

Reinforcement Learning for Intelligent Healthcare Systems: A Comprehensive Survey

The AI Economist: Optimal Economic Policy Design via Two-level Deep Reinforcement Learning

Mean-Field Multi-Agent Reinforcement Learning: A Decentralized Network Approach

Lyapunov Robust Constrained-MDPs: Soft-Constrained Robustly Stable Policy Optimization under Model Uncertainty

Ensemble Consensus-based Representation Deep Reinforcement Learning for Hybrid FSO/RF Communication Systems

Hindsight Value Function for Variance Reduction in Stochastic Dynamic Environment

High Performance Across Two Atari Paddle Games Using the Same Perceptual Control Architecture Without Training

Efficient Neural Architecture Search with Performance Prediction

Learning Barrier Certificates: Towards Safe Reinforcement Learning with Zero Training-time Violations

How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review

Fully Autonomous Real-World Reinforcement Learning for Mobile Manipulation

Controlled Deep Reinforcement Learning for Optimized Slice Placement

Sequoia: A Software Framework to Unify Continual Learning Research

Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment

Average-reward model-free reinforcement learning: a systematic review and literature mapping

MBDP: A Model-based Approach to Achieve both Robustness and Sample Efficiency via Double Dropout Planning

Backdoor Scanning for Deep Neural Networks through K-Arm Optimization

Analysis and Optimisation of Bellman Residual Errors with Neural Function Approximation

Attend2Pack: Bin Packing through Deep Reinforcement Learning with Attention

Escaping from Zero Gradient: Revisiting Action-Constrained Reinforcement Learning via Frank-Wolfe Policy Optimization

Sample Efficient Policy Gradient Methods with Recursive Variance Reduction

Adaptable image quality assessment using meta-reinforcement learning of task amenability

Learning to Control Direct Current Motor for Steering in Real Time via Reinforcement Learning

Physics-informed Dyna-Style Model-Based Deep Reinforcement Learning for Dynamic Control

Extracting Grammars from a Neural Network Parser for Anomaly Detection in Unknown Formats

Strategically Efficient Exploration in Competitive Multi-agent Reinforcement Learning

Decision Making in Monopoly using a Hybrid Deep Reinforcement Learning Approach

Modular Deep Reinforcement Learning for Continuous Motion Planning with Temporal Logic

On the Convergence of Reinforcement Learning in Nonlinear Continuous State Space Problems

Gym-$μ$RTS: Toward Affordable Full Game Real-time Strategy Games Research with Deep Reinforcement Learning

A Reflection on Learning from Data: Epistemology Issues and Limitations

GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning

Reinforcement Learning for Decision-Making and Control in Power Systems: Tutorial, Review, and Vision

Finding Failures in High-Fidelity Simulation using Adaptive Stress Testing and the Backward Algorithm

Path-Restore: Learning Network Path Selection for Image Restoration

Decentralized Multi-Agent Reinforcement Learning for Task Offloading Under Uncertainty

On the Robustness of Deep Reinforcement Learning in IRS-Aided Wireless Communications Systems

Symbolic Relational Deep Reinforcement Learning based on Graph Neural Networks

Hierarchical Multiple-Instance Data Classification with Costly Features

Model-Free Non-Stationary RL: Near-Optimal Regret and Applications in Multi-Agent RL and Inventory Control

Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose?

Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare Settings

Generating Multi-type Temporal Sequences to Mitigate Class-imbalanced Problem

Decoupling Exploration and Exploitation in Reinforcement Learning

Overcoming Model Bias for Robust Offline Deep Reinforcement Learning

Necessary and Sufficient Conditions for Inverse Reinforcement Learning of Bayesian Stopping Time Problems

Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment

Generative Actor-Critic: An Off-policy Algorithm Using the Push-forward Model

A Deep Reinforcement Learning Approach for Fair Traffic Signal Control

On the Convergence of Prior-Guided Zeroth-Order Optimization Algorithms

Megaverse: Simulating Embodied Agents at One Million Experiences per Second

Proximal Policy Optimization for Tracking Control Exploiting Future Reference Information

An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients

Offline Meta-Reinforcement Learning with Online Self-Supervision

Improving exploration in policy gradient search: Application to symbolic optimization

Constrained Policy Gradient Method for Safe and Fast Reinforcement Learning: a Neural Tangent Kernel Based Approach

Constraints Penalized Q-Learning for Safe Offline Reinforcement Learning

Intrinsically Motivated Goal-Conditioned Reinforcement Learning: a Short Survey

Provably Efficient Multi-Task Reinforcement Learning with Model Transfer

MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning

A New Representation of Successor Features for Transfer across Dissimilar Environments

Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses

Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality

Hierarchical Reinforcement Learning with Optimal Level Synchronization based on a Deep Generative Model

AutoFL: Enabling Heterogeneity-Aware Energy Efficient Federated Learning

Smart Feasibility Pump: Reinforcement Learning for (Mixed) Integer Programming

Robust Risk-Sensitive Reinforcement Learning Agents for Trading Markets

Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data

Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms

A Reinforcement Learning Environment for Mathematical Reasoning via Program Synthesis

Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning

Reinforcement Learning for Education: Opportunities and Challenges

PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration

NeuSaver: Neural Adaptive Power Consumption Optimization for Mobile Video Streaming

Safer Reinforcement Learning through Transferable Instinct Networks

Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations

Likelihood ratio-based policy gradient methods for distorted risk measures: A non-asymptotic analysis

Going Beyond Linear RL: Sample Efficient Neural Function Approximation

Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks

Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability

Pessimistic Model-based Offline RL: PAC Bounds and Posterior Sampling under Partial Coverage

Transfer Learning in Multi-Agent Reinforcement Learning with Double Q-Networks for Distributed Resource Sharing in V2X Communication

POMO: Policy Optimization with Multiple Optima for Reinforcement Learning

Model Selection with Near Optimal Rates for Reinforcement Learning with General Model Classes

ReLLIE: Deep Reinforcement Learning for Customized Low-Light Image Enhancement

Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning

A Hierarchical Bayesian model for Inverse RL in Partially-Controlled Environments

Cautious Policy Programming: Exploiting KL Regularization in Monotonic Policy Improvement for Reinforcement Learning

Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning

Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing

Behavior Constraining in Weight Space for Offline Reinforcement Learning

Modeling Explicit Concerning States for Reinforcement Learning in Visual Dialogue

A Simple Reward-free Approach to Constrained Reinforcement Learning

Polynomial Time Reinforcement Learning in Correlated FMDPs with Linear Value Functions

Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States

Bilinear Classes: A Structural Framework for Provable Generalization in RL

UAV-assisted Online Machine Learning over Multi-Tiered Networks: A Hierarchical Nested Personalized Federated Learning Approach

Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks

Efficient Attention Network: Accelerate Attention by Searching Where to Plug

Backprop-Free Reinforcement Learning with Active Neural Generative Coding

Zero-Shot Adaptation for mmWave Beam-Tracking on Overhead Messenger Wires through Robust Adversarial Reinforcement Learning

Accelerating Safe Reinforcement Learning with Constraint-mismatched Policies

Learning Probabilistic Reward Machines from Non-Markovian Stochastic Reward Processes

NVCell: Standard Cell Layout in Advanced Technology Nodes with Reinforcement Learning

Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks

Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning

Learning Vision-Guided Quadrupedal Locomotion End-to-End with Cross-Modal Transformers

CamTuner: Reinforcement-Learning based System for Camera Parameter Tuning to enhance Analytics

Analytically Tractable Hidden-States Inference in Bayesian Neural Networks

Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learning

Deep Reinforcement Learning Methods for Structure-Guided Processing Path Optimization

Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices

Solving the scalarization issues of Advantage-based Reinforcement Learning Algorithms

GRIMGEP: Learning Progress for Robust Goal Sampling in Visual Deep Reinforcement Learning

AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning

Evaluating the progress of Deep Reinforcement Learning in the real world: aligning domain-agnostic and domain-specific research

A Unified Off-Policy Evaluation Approach for General Value Function

DeepOPG: Improving Orthopantomogram Finding Summarization with Weak Supervision

Embracing the Dark Knowledge: Domain Generalization Using Regularized Knowledge Distillation

Stateless actor-critic for instance segmentation with high-level priors

Bayesian Nonparametric Modelling for Model-Free Reinforcement Learning in LTE-LAA and Wi-Fi Coexistence

A Short Note on the Relationship of Information Gain and Eluder Dimension

Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement Learning

Disentangled Attention as Intrinsic Regularization for Bimanual Multi-Object Manipulation

Multi-Modal Mutual Information (MuMMI) Training for Robust Self-Supervised Deep Reinforcement Learning

The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games

MixStyle Neural Networks for Domain Generalization and Adaptation

S-TRIGGER: Continual State Representation Learning via Self-Triggered Generative Replay

Sample Efficient Reinforcement Learning via Model-Ensemble Exploration and Exploitation

Annotating Motion Primitives for Simplifying Action Search in Reinforcement Learning

S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning

Robust Restless Bandits: Tackling Interval Uncertainty with Deep Reinforcement Learning

Low-Dimensional State and Action Representation Learning with MDP Homomorphism Metrics

Mava: a research framework for distributed multi-agent reinforcement learning

Where is the Grass Greener? Revisiting Generalized Policy Iteration for Offline Reinforcement Learning

Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial Imitation Learning

Improper Reinforcement Learning with Gradient-based Policy Optimization

Examining average and discounted reward optimality criteria in reinforcement learning

Active Finite Reward Automaton Inference and Reinforcement Learning Using Queries and Counterexamples

Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning

Deep Model Compression Via Two-Stage Deep Reinforcement Learning

Fine-Grained Gap-Dependent Bounds for Tabular MDPs via Adaptive Multi-Step Bootstrap

Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning

RL-NCS: Reinforcement learning based data-driven approach for nonuniform compressed sensing

Stabilizing Deep Q-Learning with ConvNets and Vision Transformers under Data Augmentation

Decoupled Exploration and Exploitation Policies for Sample-Efficient Reinforcement Learning

Information-theoretic Task Selection for Meta-Reinforcement Learning

Markov Decision Process modeled with Bandits for Sequential Decision Making in Linear-flow

Adaptive Stochastic ADMM for Decentralized Reinforcement Learning in Edge Industrial IoT

Reinforcement Learning based Disease Progression Model for Alzheimer's Disease

Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex Envelopes

Gym-ANM: Reinforcement Learning Environments for Active Network Management Tasks in Electricity Distribution Systems

Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL

Understanding Adversarial Attacks on Observations in Deep Reinforcement Learning

Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon

Bias-reduced Multi-step Hindsight Experience Replay for Efficient Multi-goal Reinforcement Learning

Koopman Spectrum Nonlinear Regulator and Provably Efficient Online Learning

Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation

Multiagent Deep Reinforcement Learning: Challenges and Directions Towards Human-Like Approaches

A Reinforcement Learning Approach to the Orienteering Problem with Time Windows

Generalization of Reinforcement Learning with Policy-Aware Adversarial Data Augmentation

Reinforcement Learning of Implicit and Explicit Control Flow in Instructions

Expert Q-learning: Deep Q-learning With State Values From Expert Examples

Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning and Graph Neural Networks

Multi-task curriculum learning in a complex, visual, hard-exploration domain: Minecraft

Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits

Importance of Environment Design in Reinforcement Learning: A Study of a Robotic Environment

VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objects

Causal Reinforcement Learning using Observational and Interventional Data

Habitat 2.0: Training Home Assistants to Rearrange their Habitat

Instance-optimality in optimal value estimation: Adaptivity via variance-reduced Q-learning

Concentration of Contractive Stochastic Approximation and Reinforcement Learning

A Reinforcement Learning Approach for Sequential Spatial Transformer Networks

A Comprehensive Survey of Incentive Mechanism for Federated Learning

Model-Advantage Optimization for Model-Based Reinforcement Learning

Intrinsically Motivated Self-supervised Learning in Reinforcement Learning

Predictive Control Using Learned State Space Models via Rolling Horizon Evolution

Compositional Reinforcement Learning from Logical Specifications

Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems

Multi-Goal Reinforcement Learning environments for simulated Franka Emika Panda robot

MDP Playground: A Design and Debug Testbed for Reinforcement Learning

Branch Prediction as a Reinforcement Learning Problem: Why, How and Case Studies

MARL with General Utilities via Decentralized Shadow Reward Actor-Critic

Decision Transformer: Reinforcement Learning via Sequence Modeling

Planning with Exploration: Addressing Dynamics Bottleneck in Model-based Reinforcement Learning

Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation

Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings

Improving Playtesting Coverage via Curiosity Driven Reinforcement Learning Agents

Policy Gradient Methods for the Noisy Linear Quadratic Regulator over a Finite Horizon

Safe Learning and Optimization Techniques: Towards a Survey of the State of the Art

Variance-Aware Off-Policy Evaluation with Linear Function Approximation

Provably Efficient Representation Learning in Low-rank Markov Decision Processes

Goal-Directed Planning by Reinforcement Learning and Active Inference

Uniform-PAC Bounds for Reinforcement Learning with Linear Function Approximation

Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models

Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning

Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations

Boosting Offline Reinforcement Learning with Residual Generative Modeling

Interpretable Model-based Hierarchical Reinforcement Learning using Inductive Logic Programming

Unlocking Pixels for Reinforcement Learning via Implicit Attention

Continual World: A Robotic Benchmark For Continual Reinforcement Learning

State Entropy Maximization with Random Encoders for Efficient Exploration

OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation

Defense Against Reward Poisoning Attacks in Reinforcement Learning

Statistical Inference of the Value Function for Reinforcement Learning in Infinite Horizon Settings

Learning to Represent Action Values as a Hypergraph on the Action Vertices

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL

Certification of Iterative Predictions in Bayesian Neural Networks

Video Summarization through Reinforcement Learning with a 3D Spatio-Temporal U-Net

Benchmarking Perturbation-based Saliency Maps for Explaining Atari Agents

AdaZoom: Adaptive Zoom Network for Multi-Scale Object Detection in Large Scenes

Honey, I Shrunk The Actor: A Case Study on Preserving Performance with Smaller Actors in Actor-Critic RL

Learning the Preferences of Uncertain Humans with Inverse Decision Theory

Scenic4RL: Programmatic Modeling and Generation of Reinforcement Learning Environments

Pattern Transfer Learning for Reinforcement Learning in Order Dispatching

MADE: Exploration via Maximizing Deviation from Explored Regions

Deep Reinforcement Learning Models Predict Visual Responses in the Brain: A Preliminary Result

On the Sample Complexity of Batch Reinforcement Learning with Policy-Induced Data

Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL

Multi-Armed Bandits for Minesweeper: Profiting from Exploration-Exploitation Synergy

Local Information Agent Modelling in Partially-Observable Environments

Adapting the Function Approximation Architecture in Online Reinforcement Learning

Randomized Value Functions via Posterior State-Abstraction Sampling

SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies

A Deep Reinforcement Learning Approach towards Pendulum Swing-up Problem based on TF-Agents

Data-driven control of room temperature and bidirectional EV charging using deep reinforcement learning: simulations and experiments

Modelling resource allocation in uncertain system environment through deep reinforcement learning

CROP: Certifying Robust Policies for Reinforcement Learning through Functional Smoothing

TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning

Learning to Recommend Frame for Interactive Video Object Segmentation in the Wild

NPAS: A Compiler-aware Framework of Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration

DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting

A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants

Explicitly Encouraging Low Fractional Dimensional Trajectories Via Reinforcement Learning

How memory architecture affects performance and learning in simple POMDPs

Reinforcement Learning for Markovian Bandits: Is Posterior Sampling more Scalable than Optimism?

LemgoRL: An open-source Benchmark Tool to Train Reinforcement Learning Agents for Traffic Signal Control in a real-world simulation scenario

Fundamental Limits of Reinforcement Learning in Environment with Endogeneous and Exogeneous Uncertainty

On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control

Robust Reinforcement Learning Under Minimax Regret for Green Security

Optimizing Biomanufacturing Harvesting Decisions under Limited Historical Data

Decoupling Value and Policy for Generalization in Reinforcement Learning

On Multi-objective Policy Optimization as a Tool for Reinforcement Learning

Learning to Prevent Leakage: Privacy-Preserving Inference in the Mobile Cloud

Eye of the Beholder: Improved Relation Generalization for Text-based Reinforcement Learning Agents

Randomized Exploration for Reinforcement Learning with General Value Function Approximation

rSoccer: A Framework for Studying Reinforcement Learning in Small and Very Small Size Robot Soccer

Combining Semantic Guidance and Deep Reinforcement Learning For Generating Human Level Paintings

Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity

Poisoning Deep Reinforcement Learning Agents with In-Distribution Triggers

Unsupervised Program Synthesis for Images By Sampling Without Replacement

Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning

Continuous Coordination As a Realistic Scenario for Lifelong Learning

Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning

Human Apprenticeship Learning via Kernel-based Inverse Reinforcement Learning

Training like Playing: A Reinforcement Learning And Knowledge Graph-based framework for building Automatic Consultation System in Medical Field

User-Guided Personalized Image Aesthetic Assessment based on Deep Reinforcement Learning

Analysis of a Target-Based Actor-Critic Algorithm with Linear Function Approximation

On-Policy Deep Reinforcement Learning for the Average-Reward Criterion

Which Mutual-Information Representation Learning Objectives are Sufficient for Control?

Online Sub-Sampling for Reinforcement Learning with General Function Approximation

Temporal Predictive Coding For Model-Based Planning In Latent Space

Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise Safety

Not All Memories are Created Equal: Learning to Forget by Expiring

Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy

FedScale: Benchmarking Model and System Performance of Federated Learning

A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation

Recomposing the Reinforcement Learning Building Blocks with Hypernetworks

Unifying Cardiovascular Modelling with Deep Reinforcement Learning for Uncertainty Aware Control of Sepsis Treatment

Model-free Reinforcement Learning for Branching Markov Decision Processes

Locally Persistent Exploration in Continuous Control Tasks with Sparse Rewards

A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning

SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning

An Empirical Comparison of Off-policy Prediction Learning Algorithms on the Collision Task

PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators

A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning

Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning

Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation Errors

Courteous Behavior of Automated Vehicles at Unsignalized Intersections via Reinforcement Learning

Automatic Risk Adaptation in Distributional Reinforcement Learning

Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks

Going Beyond Linear Transformers with Recurrent Fast Weight Programmers

Represent Your Own Policies: Reinforcement Learning with Policy-extended Value Function Approximator

Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning

Multi-Task Reinforcement Learning with Context-based Representations

UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning

PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning

Informative Policy Representations in Multi-Agent Reinforcement Learning via Joint-Action Distributions

Robust MAML: Prioritization task buffer with adaptive learning process for model-agnostic meta-learning

Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data

Adversarial Reinforcement Learning for Procedural Content Generation

Hyperspace Neighbor Penetration Approach to Dynamic Programming for Model-Based Reinforcement Learning Problems with Slowly Changing Variables in A Continuous State Space

RLCorrector: Reinforced Proofreading for Connectomics Image Segmentation

SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II

Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning

Deception in Social Learning: A Multi-Agent Reinforcement Learning Perspective

Online Learning for Stochastic Shortest Path Model via Posterior Sampling

Self-Paced Context Evaluation for Contextual Reinforcement Learning

PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training

Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL

TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL

There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning

Concave Utility Reinforcement Learning: the Mean-field Game viewpoint

Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning

Pretraining Representations for Data-Efficient Reinforcement Learning

Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient Exploration

Curriculum Design for Teaching via Demonstrations: Theory and Applications

Towards Practical Credit Assignment for Deep Reinforcement Learning

A Deep Value-network Based Approach for Multi-Driver Order Dispatching

Learning Markov State Abstractions for Deep Reinforcement Learning

A Novel Greedy-Step Bellman Optimality Equation for Efficient Value Propagation

Beyond Fine-Tuning: Transferring Behavior in Reinforcement Learning

PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning

Left Ventricle Contouring in Cardiac Images Based on Deep Reinforcement Learning

Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games

Softmax Policy Gradient Methods Can Take Exponential Time to Converge

Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning

Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration

Beyond Target Networks: Improving Deep $Q$-learning with Functional Regularization

Offline Policy Comparison under Limited Historical Agent-Environment Interactions

Closed-Form Analytical Results for Maximum Entropy Reinforcement Learning

Batch Reinforcement Learning with a Nonparametric Off-Policy Policy Gradient

Learning without Knowing: Unobserved Context in Continuous Transfer Reinforcement Learning

Towards robust and domain agnostic reinforcement learning competitions

Model-Invariant State Abstractions for Model-Based Reinforcement Learning

Causal Influence Detection for Improving Efficiency in Reinforcement Learning

MixRL: Data Mixing Augmentation for Regression using Reinforcement Learning

The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces

On the Theory of Reinforcement Learning with Once-per-Episode Feedback

Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation

Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks

DisTop: Discovering a Topological representation to learn diverse and rewarding skills

ScheduleNet: Learn to solve multi-agent scheduling problems with reinforcement learning

Efficient Continuous Control with Double Actors and Regularized Critics

Constrained episodic reinforcement learning in concave-convex and knapsack settings

Learning Routines for Effective Off-Policy Reinforcement Learning

Same State, Different Task: Continual Reinforcement Learning without Interference

HMRL: Hyper-Meta Learning for Sparse Reward Reinforcement Learning Problem

Revisiting Maximum Entropy Inverse Reinforcement Learning: New Perspectives and Algorithms

Privacy-Preserving Kickstarting Deep Reinforcement Learning with Privacy-Aware Learners

Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs

Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits

Model-agnostic and Scalable Counterfactual Explanations via Reinforcement Learning

Transferable and Distributed User Association Policies for 5G and Beyond Networks

Nara: Learning Network-Aware Resource Allocation Algorithms for Cloud Data Centres

Online reinforcement learning with sparse rewards through an active inference capsule

RL-DARTS: Differentiable Architecture Search for Reinforcement Learning

Celebrating Diversity in Shared Multi-Agent Reinforcement Learning

Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL

MUSBO: Model-based Uncertainty Regularized and Sample Efficient Batch Optimization for Deployment Constrained Reinforcement Learning

Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision

Relevance-Guided Modeling of Object Dynamics for Reinforcement Learning

UVIP: Model-Free Approach to Evaluate Reinforcement Learning Algorithms

MICo: Learning improved representations via sampling-based state similarity for Markov decision processes

Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning

LiMIIRL: Lightweight Multiple-Intent Inverse Reinforcement Learning

A Provably-Efficient Model-Free Algorithm for Constrained Markov Decision Processes

Hyperbolically-Discounted Reinforcement Learning on Reward-Punishment Framework

Variational Empowerment as Representation Learning for Goal-Based Reinforcement Learning

SENTINEL: Taming Uncertainty with Ensemble-based Distributional Reinforcement Learning

Detecting Rewards Deterioration in Episodic Reinforcement Learning

An Entropy Regularization Free Mechanism for Policy-based Reinforcement Learning

A reinforcement learning approach to improve communication performance and energy utilization in fog-based IoT

Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning

Deep Reinforcement Learning in Quantitative Algorithmic Trading: A Review

Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs

SHAQ: Incorporating Shapley Value Theory into Q-Learning for Multi-Agent Reinforcement Learning

Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning

A unified view of likelihood ratio and reparameterization gradients

Generalizing Decision Making for Automated Driving with an Invariant Environment Representation using Deep Reinforcement Learning

Don't Do What Doesn't Matter: Intrinsic Motivation with Action Usefulness

Procedural Content Generation: Better Benchmarks for Transfer Reinforcement Learning

Efficient Hierarchical Exploration with Stable Subgoal Representation Learning

CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee

On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning

Agent-Level Maximum Entropy Inverse Reinforcement Learning for Mean Field Games

FIT: a Fast and Accurate Framework for Solving Medical Inquiring and Diagnosing Tasks

Continual Learning with Node-Importance based Adaptive Group Sparse Regularization

Risk-Aware Transfer in Reinforcement Learning using Successor Features

Joint Optimization of Multi-Objective Reinforcement Learning with Policy Gradient Based Algorithm

Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning

Reinforcement Learning reveals fundamental limits on the mixing of active particles

Task-Guided Inverse Reinforcement Learning Under Partial Information

Towards mental time travel: a hierarchical memory for reinforcement learning agents

Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model

Improving Generalization in Mountain Car Through the Partitioned Parameterized Policy Approach via Quasi-Stochastic Gradient Descent

Storchastic: A Framework for General Stochastic Automatic Differentiation

Transferable Deep Reinforcement Learning Framework for Autonomous Vehicles with Joint Radar-Data Communications

A Decentralized Policy Gradient Approach to Multi-task Reinforcement Learning

Improving Generalization in Meta-RL with Imaginary Tasks from Latent Dynamics Mixture

On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method

On the model-based stochastic value gradient for continuous reinforcement learning

CASA: A Bridge Between Gradient of Policy Improvement and Policy Evaluation

Optimistic Reinforcement Learning by Forward Kullback-Leibler Divergence Optimization

Online Algorithms and Policies Using Adaptive and Machine Learning Approaches

Bayesian Nonparametric Reinforcement Learning in LTE and Wi-Fi Coexistence

Synthesized Policies for Transfer and Adaptation across Tasks and Environments

Curiosity Killed or Incapacitated the Cat and the Asymptotically Optimal Agent

Successive Convex Approximation Based Off-Policy Optimization for Constrained Reinforcement Learning

Self-Imitation Learning for Robot Tasks with Sparse and Delayed Rewards

Unbiased Asymmetric Actor-Critic for Partially Observable Reinforcement Learning

Safe Model-based Off-policy Reinforcement Learning for Eco-Driving in Connected and Automated Hybrid Electric Vehicles

A Comparison of Reward Functions in Q-Learning Applied to a Cart Position Problem

Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence

Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners

Reducing Bus Bunching with Asynchronous Multi-Agent Reinforcement Learning

Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement Learning

Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound

Techniques Toward Optimizing Viewability in RTB Ad Campaigns Using Reinforcement Learning

Revisiting Rainbow: Promoting more Insightful and Inclusive Deep Reinforcement Learning Research

On Instrumental Variable Regression for Deep Offline Policy Evaluation

Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment

Data-Efficient Reinforcement Learning with Self-Predictive Representations

Minimum-Delay Adaptation in Non-Stationary Reinforcement Learning via Online High-Confidence Change-Point Detection

Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts

Learn Fine-grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images

Tonic: A Deep Reinforcement Learning Library for Fast Prototyping and Benchmarking

Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning

Reinforcement Learning Assisted Oxygen Therapy for COVID-19 Patients Under Intensive Care

Cache Replacement as a MAB with Delayed Feedback and Decaying Costs

Gym-ANM: Open-source software to leverage reinforcement learning for power system management in research and education

Adaptive ABAC Policy Learning: A Reinforcement Learning Approach

Dependent Multi-Task Learning with Causal Intervention for Image Captioning

SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems

Online Multimodal Transportation Planning using Deep Reinforcement Learning

Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach

Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting

Using Meta Reinforcement Learning to Bridge the Gap between Simulation and Experiment in Energy Demand Response

Principled Exploration via Optimistic Bootstrapping and Backward Induction

Non-asymptotic bounds for stochastic optimization with biased noisy gradient oracles

Reward Biased Maximum Likelihood Estimation for Reinforcement Learning

Feature-Based Interpretable Reinforcement Learning based on State-Transition Models

Non-decreasing Quantile Function Network with Efficient Exploration for Distributional Reinforcement Learning

DeepQAMVS: Query-Aware Hierarchical Pointer Networks for Multi-Video Summarization

Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature

Anomaly Detection via Controlled Sensing and Deep Active Inference

A Scalable Algorithm for Anomaly Detection via Learning-Based Controlled Sensing

Adversarial Reinforcement Learning in Dynamic Channel Access and Power Control

Exploring the Similarity of Representations in Model-Agnostic Meta-Learning

Smooth Variational Graph Embeddings for Efficient Neural Architecture Search

Interpretable performance analysis towards offline reinforcement learning: A dataset perspective

Return-based Scaling: Yet Another Normalisation Trick for Deep RL

Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective

A Reinforcement Learning Environment for Multi-Service UAV-enabled Wireless Systems

Hierarchical RNNs-Based Transformers MADDPG for Mixed Cooperative-Competitive Environments

Integrated Decision and Control: Towards Interpretable and Computationally Efficient Driving Intelligence

Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks

Context-Based Soft Actor Critic for Environments with Non-stationary Dynamics

Reinforcement Learning with Expert Trajectory For Quantitative Trading

RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning

Multi-agent Policy Optimization with Approximatively Synchronous Advantage Estimation

Reward prediction for representation learning and reward shaping

Policy Mirror Descent for Reinforcement Learning: Linear Convergence, New Sampling Complexity, and Generalized Problem Classes

Semi-On-Policy Training for Sample Efficient Multi-Agent Policy Gradients

Solve routing problems with a residual edge-graph attention neural network

Time-Aware Q-Networks: Resolving Temporal Irregularity for Deep Reinforcement Learning

FOCAL: Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization

FISAR: Forward Invariant Safe Reinforcement Learning with a Deep Neural Network-Based Optimize

Learning Algorithms for Regenerative Stopping Problems with Applications to Shipping Consolidation in Logistics

Generative Adversarial Reward Learning for Generalized Behavior Tendency Inference

Reinforcement Learning for Scalable Logic Optimization with Graph Neural Networks

OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning

Deep Reinforcement Learning for Adaptive Exploration of Unknown Environments

Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics

Full Gradient DQN Reinforcement Learning: A Provably Convergent Scheme

Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application

Efficiently Breaking the Curse of Horizon in Off-Policy Evaluation with Double Reinforcement Learning

Action Candidate Based Clipped Double Q-learning for Discrete and Continuous Action Tasks

InferNet for Delayed Reinforcement Tasks: Addressing the Temporal Credit Assignment Problem

Augmenting Policy Learning with Routines Discovered from a Single Demonstration

Better than the Best: Gradient-based Improper Reinforcement Learning for Network Scheduling

Reinforcement Learning for Traffic Signal Control: Comparison with Commercial Systems

CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition

What is Going on Inside Recurrent Meta Reinforcement Learning Agents?

Medium Access using Distributed Reinforcement Learning for IoTs with Low-Complexity Wireless Transceivers

Automated Image Data Preprocessing with Deep Reinforcement Learning

Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Plans

Pre-training of Deep RL Agents for Improved Learning under Domain Randomization

A Reinforcement Learning Environment for Polyhedral Optimizations

Adapting to Reward Progressivity via Spectral Reinforcement Learning

Nested Mixture of Experts: Cooperative and Competitive Learning of Hybrid Dynamical System

Learning Individually Inferred Communication for Multi-Agent Cooperation

Antagonistic Crowd Simulation Model Integrating Emotion Contagion and Deep Reinforcement Learning

Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms

A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning

Combining Off and On-Policy Training in Model-Based Reinforcement Learning

Optimizing the Neural Architecture of Reinforcement Learning Agents

Intelligent Roundabout Insertion using Deep Reinforcement Learning

Learning a Deep Reinforcement Learning Policy Over the Latent Space of a Pre-trained GAN for Semantic Age Manipulation

SocialAI 0.1: Towards a Benchmark to Stimulate Research on Socio-Cognitive Abilities in Deep Reinforcement Learning Agents

Implementing Reinforcement Learning Algorithms in Retail Supply Chains with OpenAI Gym Toolkit

Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning

Development of a Soft Actor Critic Deep Reinforcement Learning Approach for Harnessing Energy Flexibility in a Large Office Building

AWAC: Accelerating Online Reinforcement Learning with Offline Datasets

A Deep Reinforcement Learning Approach for the Meal Delivery Problem

DisCo RL: Distribution-Conditioned Reinforcement Learning for General-Purpose Policies

Safe Chance Constrained Reinforcement Learning for Batch Process Control

CropGym: a Reinforcement Learning Environment for Crop Management

Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention

Adaptive learning for financial markets mixing model-based and model-free RL for volatility targeting

Independent Reinforcement Learning for Weakly Cooperative Multiagent Traffic Control Problem

Causal Inference Q-Network: Toward Resilient Reinforcement Learning

Policy Fusion for Adaptive and Customizable Reinforcement Learning Agents

Revisiting the Monotonicity Constraint in Cooperative Multi-Agent Reinforcement Learning

CVLight: Deep Reinforcement Learning for Adaptive Traffic Signal Control with Connected Vehicles

An Energy-Saving Snake Locomotion Gait Policy Obtained Using Deep Reinforcement Learning

Discovering an Aid Policy to Minimize Student Evasion Using Offline Reinforcement Learning

SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning

Communication-Efficient Policy Gradient Methods for Distributed Reinforcement Learning

C-Learning: Learning to Achieve Goals via Recursive Classification

Training Value-Aligned Reinforcement Learning Agents Using a Normative Prior

Active Screening for Recurrent Diseases: A Reinforcement Learning Approach

Agent-Centric Representations for Multi-Agent Reinforcement Learning

Probabilistic Mixture-of-Experts for Efficient Deep Reinforcement Learning

Continuous Deep Q-Learning with Simulator for Stabilization of Uncertain Discrete-Time Systems

Zeus: Efficiently Localizing Actions in Videos using Reinforcement Learning

A Novel Approach to Curiosity and Explainable Reinforcement Learning via Interpretable Sub-Goals

An $L^2$ Analysis of Reinforcement Learning in High Dimensions with Kernel and Neural Network Approximation

Quick Learner Automated Vehicle Adapting its Roadmanship to Varying Traffic Cultures with Meta Reinforcement Learning

Intuitive Physics Guided Exploration for Sample Efficient Sim2real Transfer

Distributed Value Function Approximation for Collaborative Multi-Agent Reinforcement Learning

Action Advising with Advice Imitation in Deep Reinforcement Learning

Towards Standardizing Reinforcement Learning Approaches for Stochastic Production Scheduling

Safe Exploration in Model-based Reinforcement Learning using Control Barrier Functions

MEG: Generating Molecular Counterfactual Explanations for Deep Graph Networks

Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization

Structured learning of rigid-body dynamics: A survey and unified view from a robotics perspective

Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks

Jamming-Resilient Path Planning for Multiple UAVs via Deep Reinforcement Learning

Multi-Agent Reinforcement Learning Based Coded Computation for Mobile Ad Hoc Computing

Scale Invariant Solutions for Overdetermined Linear Systems with Applications to Reinforcement Learning

Generalising Discrete Action Spaces with Conditional Action Trees

Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers

Safe Continuous Control with Constrained Model-Based Policy Optimization

Constrained Model-Free Reinforcement Learning for Process Optimization

Visual Comfort Aware-Reinforcement Learning for Depth Adjustment of Stereoscopic 3D Images

Optimizing the Long-Term Average Reward for Continuing MDPs: A Technical Report

My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

GAN-Based Interactive Reinforcement Learning from Demonstration and Human Evaluative Feedback

Blending MPC & Value Function Approximation for Efficient Reinforcement Learning

Data-Driven Reinforcement Learning for Virtual Character Animation Control

Online and Offline Reinforcement Learning by Planning with a Learned Model

Subgoal-based Reward Shaping to Improve Efficiency in Reinforcement Learning

Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow

Thief, Beware of What Get You There: Towards Understanding Model Extraction Attack

Tightening Exploration in Upper Confidence Reinforcement Learning

Deep Q-Learning: Theoretical Insights from an Asymptotic Analysis

Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search

Learn Goal-Conditioned Policy with Intrinsic Motivation for Deep Reinforcement Learning

Symmetry reduction for deep reinforcement learning active control of chaotic spatiotemporal dynamics

Behavior-Guided Actor-Critic: Improving Exploration via Learning Policy Behavior Representation for Deep Reinforcement Learning

Learning Sampling Policy for Faster Derivative Free Optimization

GAEA: Graph Augmentation for Equitable Access via Reinforcement Learning

Risk-Conditioned Distributional Soft Actor-Critic for Risk-Sensitive Navigation

TaylorMade VDD: Domain-adaptive Visual Defect Detector for High-mix Low-volume Production of Non-convex Cylindrical Metal Objects

Learning to Reweight Imaginary Transitions for Model-Based Reinforcement Learning

Generalization in Reinforcement Learning by Soft Data Augmentation

Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization

ACERAC: Efficient reinforcement learning in fine time discretization

A Bayesian Approach to Reinforcement Learning of Vision-Based Vehicular Control

A Safe Reinforcement Learning Architecture for Antenna Tilt Optimisation

PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics

Learning to Sample with Local and Global Contexts in Experience Replay Buffer

Improving Robustness of Deep Reinforcement Learning Agents: Environment Attacks based on Critic Networks

Learning Invariant Representations for Reinforcement Learning without Reconstruction

Data-Driven Simulation of Ride-Hailing Services using Imitation and Reinforcement Learning

Context-Dependent Upper-Confidence Bounds for Directed Exploration

A Reinforcement Learning Approach for Rebalancing Electric Vehicle Sharing Systems

Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning

Design and implementation of an environment for Learning to Run a Power Network (L2RPN)

Progressive extension of reinforcement learning action dimension for asymmetric assembly tasks

MPC-based Reinforcement Learning for Economic Problems with Application to Battery Storage

Distributed Learning in Wireless Networks: Recent Progress and Future Challenges

A Dual-Critic Reinforcement Learning Framework for Frame-level Bit Allocation in HEVC/H.265

Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation

Modeling Affect-based Intrinsic Rewards for Exploration and Learning

Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy

Improving Actor-Critic Reinforcement Learning via Hamiltonian Policy

Distributional Offline Continuous-Time Reinforcement Learning with Neural Physics-Informed PDEs (SciPhy RL for DOCTR-L)

Neuromechanics-based Deep Reinforcement Learning of Neurostimulation Control in FES cycling

Low Dose Helical CBCT denoising by using domain filtering with deep reinforcement learning

How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?

SimPoE: Simulated Character Control for 3D Human Pose Estimation

Optimization Algorithm for Feedback and Feedforward Policies towards Robot Control Robust to Sensing Failures

A General Markov Decision Process Framework for Directly Learning Optimal Control Policies

DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation

Building Safer Autonomous Agents by Leveraging Risky Driving Behavior Knowledge

Energy Efficient Edge Computing: When Lyapunov Meets Distributed Reinforcement Learning

Deep Reinforcement Learning for Constrained Field Development Optimization in Subsurface Two-phase Flow

A Dynamic Penalty Function Approach for Constraints-Handling in Reinforcement Learning

Greedy-GQ with Variance Reduction: Finite-time Analysis and Improved Complexity

Hierarchical and Partially Observable Goal-driven Policy Learning with Goals Relational Graph

FaiR-IoT: Fairness-aware Human-in-the-Loop Reinforcement Learning for Harnessing Human Variability in Personalized IoT

Augmenting Automated Game Testing with Deep Reinforcement Learning

Deep Reinforcement Learning for Resource Allocation in Business Processes

Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark

Deep reinforcement learning of event-triggered communication and control for multi-agent cooperative transport

ReAgent: Point Cloud Registration using Imitation and Reinforcement Learning

Good, Better, Best: Textual Distractors Generation for Multi-Choice VQA via Policy Gradient

Increasing the Efficiency of Policy Learning for Autonomous Vehicles by Multi-Task Representation Learning

Weakly-Supervised Domain Adaptation of Deep Regression Trackers via Reinforced Knowledge Distillation

SegVisRL: Visuomotor Development for a Lunar Rover for Hazard Avoidance using Camera Images

MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement Learning

Meta-Adversarial Inverse Reinforcement Learning for Decision-making Tasks

Reinforcement Learning for Deceiving Reactive Jammers in Wireless Networks

Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning

Deep reinforcement learning for feedback control in a collective flashing ratchet

A storage expansion planning framework using reinforcement learning and simulation-based optimization

Reinforcement Learning for Autonomous Driving with Latent State Inference and Spatial-Temporal Relationships

The Gradient Convergence Bound of Federated Multi-Agent Reinforcement Learning with Efficient Communication

An Exponential Lower Bound for Linearly-Realizable MDPs with Constant Suboptimality Gap

Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification

An FPGA-Based On-Device Reinforcement Learning Approach using Online Sequential Learning

MIDAS: Multi-agent Interaction-aware Decision-making with Adaptive Strategies for Urban Autonomous Navigation

Drop-Bottleneck: Learning Discrete Compressed Representation for Noise-Robust Exploration

Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism

Learning to Robustly Negotiate Bi-Directional Lane Usage in High-Conflict Driving Scenarios

RMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agents

Provably Correct Optimization and Exploration with Non-linear Policies

Smart Scheduling based on Deep Reinforcement Learning for Cellular Networks

Image Synthesis for Data Augmentation in Medical CT using Deep Reinforcement Learning

Representation Matters: Improving Perception and Exploration for Robotics

MaAST: Map Attention with Semantic Transformersfor Efficient Visual Navigation

Self-Supervised Discovering of Interpretable Features for Reinforcement Learning

Deep reinforcement learning-based image classification achieves perfect testing set accuracy for MRI brain tumors with a training set of only 30 images

Unsupervised deep clustering and reinforcement learning can accurately segment MRI brain tumors with very small training sets

Reinforcement learning using Deep Q Networks and Q learning accurately localizes brain tumors on MRI with very small training sets

Reinforcement Learning for Joint Optimization of Multiple Rewards

Solving Compositional Reinforcement Learning Problems via Task Reduction

Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning

Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge Graphs

Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning

Meta-Learning of Structured Task Distributions in Humans and Machines

Efficient Wasserstein Natural Gradients for Reinforcement Learning

Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning

Adaptive Procedural Task Generation for Hard-Exploration Problems

Infinite-Horizon Offline Reinforcement Learning with Linear Function Approximation: Curse of Dimensionality and Algorithm

Weakly Supervised Reinforcement Learning for Autonomous Highway Driving via Virtual Safety Cages

Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online

Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis

Hierarchical Reinforcement Learning Framework for Stochastic Spaceflight Campaign Design

Local Differentially Private Regret Minimization in Reinforcement Learning

Model-Based Actor-Critic with Chance Constraint for Stochastic System

Baconian: A Unified Open-source Framework for Model-Based Reinforcement Learning

Successor Feature Sets: Generalizing Successor Representations Across Policies

A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets

Sample-efficient Reinforcement Learning Representation Learning with Curiosity Contrastive Forward Dynamics Model

Reinforcement Learning with Algorithms from Probabilistic Structure Estimation

Offline Reinforcement Learning with Fisher Divergence Critic Regularization

Optimal sequential decision making with probabilistic digital twins

Dreaming: Model-based Reinforcement Learning by Latent Imagination without Reconstruction

A Reinforcement Learning Based Approach to Play Calling in Football

Policy Search with Rare Significant Events: Choosing the Right Partner to Cooperate with

Adaptive Partial Scanning Transmission Electron Microscopy with Reinforcement Learning

A Game Theoretic Framework for Model Based Reinforcement Learning

ReinforceBug: A Framework to Generate Adversarial Textual Examples

Analyzing the Hidden Activations of Deep Policy Networks: Why Representation Matters

Hierarchical Reinforcement Learning By Discovering Intrinsic Options

Improving Context-Based Meta-Reinforcement Learning with Self-Supervised Trajectory Contrastive Learning

An Information-Theoretic Perspective on Credit Assignment in Reinforcement Learning

Inverse Reinforcement Learning of Autonomous Behaviors Encoded as Weighted Finite Automata

Provably Convergent Policy Gradient Methods for Model-Agnostic Meta-Reinforcement Learning

Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL

Non-asymptotic Confidence Intervals of Off-policy Evaluation: Primal and Dual Bounds

The AI Arena: A Framework for Distributed Multi-Agent Reinforcement Learning

Continuous Action Reinforcement Learning from a Mixture of Interpretable Experts

Differentiable Trust Region Layers for Deep Reinforcement Learning

Iterative Shrinking for Referring Expression Grounding Using Deep Reinforcement Learning

Learning to Play Soccer From Scratch: Sample-Efficient Emergent Coordination through Curriculum-Learning and Competition

Provably Efficient Cooperative Multi-Agent Reinforcement Learning with Function Approximation

Instabilities of Offline RL with Pre-Trained Neural Representation

Improved Corruption Robust Algorithms for Episodic Reinforcement Learning

Model-based versus Model-free Deep Reinforcement Learning for Autonomous Racing Cars

TempLe: Learning Template of Transitions for Sample Efficient Multi-task RL

Vision-Based Mobile Robotics Obstacle Avoidance With Deep Reinforcement Learning

Distributed Reinforcement Learning for Flexible and Efficient UAV Swarm Control

The Sample Complexity of Teaching-by-Reinforcement on Q-Learning

A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning

The Effect of Q-function Reuse on the Total Regret of Tabular, Model-Free, Reinforcement Learning

Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels

Markov Cricket: Using Forward and Inverse Reinforcement Learning to Model, Predict And Optimize Batting Performance in One-Day International Cricket

Bias-Reduced Hindsight Experience Replay with Virtual Goal Prioritization

Achieving Real-Time LiDAR 3D Object Detection on a Mobile Device

DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning

Visual Explanation using Attention Mechanism in Actor-Critic-based Deep Reinforcement Learning

Causal Reinforcement Learning: An Instrumental Variable Approach

On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk

Efficient Learning in Non-Stationary Linear Markov Decision Processes

Automatic Exploration Process Adjustment for Safe Reinforcement Learning with Joint Chance Constraint Satisfaction

Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch

Unsupervised Learning for Robust Fitting:A Reinforcement Learning Approach

DeepFreight: A Model-free Deep-reinforcement-learning-based Algorithm for Multi-transfer Freight Delivery

A Dual-Memory Architecture for Reinforcement Learning on Neuromorphic Platforms

Conservative Optimistic Policy Optimization via Multiple Importance Sampling

RL-Scope: Cross-Stack Profiling for Deep Reinforcement Learning Workloads

Online 3D Bin Packing with Constrained Deep Reinforcement Learning

An empirical investigation of the challenges of real-world reinforcement learning

Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings

Shape-driven Coordinate Ordering for Star Glyph Sets via Reinforcement Learning

Robust Constrained Reinforcement Learning for Continuous Control with Model Misspecification

Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction

Differentiable Neural Architecture Learning for Efficient Neural Network Design

Adversarial Environment Generation for Learning to Navigate the Web

Learning to run a Power Network Challenge: a Retrospective Analysis

Mind Mappings: Enabling Efficient Algorithm-Accelerator Mapping Space Search

Learning with Safety Constraints: Sample Complexity of Reinforcement Learning for Constrained MDPs

rl_reach: Reproducible Reinforcement Learning Experiments for Robotic Reaching Tasks

RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem

Content Masked Loss: Human-Like Brush Stroke Planning in a Reinforcement Learning Painting Agent

Reducing Conservativeness Oriented Offline Reinforcement Learning

On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning

Hindsight Expectation Maximization for Goal-conditioned Reinforcement Learning

Efficient Client Contribution Evaluation for Horizontal Federated Learning

Developing parsimonious ensembles using predictor diversity within a reinforcement learning framework

Developing parsimonious ensembles using ensemble diversity within a reinforcement learning framework

Revisiting Parameter Sharing In Multi-Agent Deep Reinforcement Learning

Learning Generalizable Visual Representations via Interactive Gameplay

Abstract Value Iteration for Hierarchical Reinforcement Learning

Learning Emergent Discrete Message Communication for Cooperative Reinforcement Learning

Balancing Rational and Other-Regarding Preferences in Cooperative-Competitive Environments

Credit Assignment with Meta-Policy Gradient for Multi-Agent Reinforcement Learning

DeepThermal: Combustion Optimization for Thermal Power Generating Units Using Offline Reinforcement Learning

Generalize a Small Pre-trained Model to Arbitrarily Large TSP Instances

State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning with Rewards

Challenges for Using Impact Regularizers to Avoid Negative Side Effects

QR-MIX: Distributional Value Function Factorisation for Cooperative Multi-Agent Reinforcement Learning

A Visual Communication Map for Multi-Agent Deep Reinforcement Learning

Review, Analysis and Design of a Comprehensive Deep Reinforcement Learning Framework

Domain-invariant NBV Planner for Active Cross-domain Self-localization

Regularization Matters in Policy Optimization -- An Empirical Study on Continuous Control

Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping

Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models

HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving

GELATO: Geometrically Enriched Latent Model for Offline Reinforcement Learning

Stratified Experience Replay: Correcting Multiplicity Bias in Off-Policy Reinforcement Learning

Sim-Env: Decoupling OpenAI Gym Environments from Simulation Models

Return-Based Contrastive Representation Learning for Reinforcement Learning

Improved Context-Based Offline Meta-RL with Attention and Contrastive Learning

A Novel Framework for Neural Architecture Search in the Hill Climbing Domain

Dealing with Non-Stationarity in Multi-Agent Reinforcement Learning via Trust Region Decomposition

Query-based Targeted Action-Space Adversarial Policies on Deep Reinforcement Learning Agents

Automatic Data Augmentation for Generalization in Deep Reinforcement Learning

Beyond variance reduction: Understanding the true impact of baselines on policy optimization

Variance-Aware Confidence Set: Variance-Dependent Bound for Linear Bandits and Horizon-Free Bound for Linear Mixture MDP

Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space

Logarithmic Regret for Reinforcement Learning with Linear Function Approximation

Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs

Efficient Reinforcement Learning in Resource Allocation Problems Through Permutation Invariant Multi-task Learning

Strategic bidding in freight transport using deep reinforcement learning

Learning Memory-Dependent Continuous Control from Demonstrations

Multi-Agent Reinforcement Learning of 3D Furniture Layout Simulation in Indoor Graphics Scenes

Nearly Optimal Regret for Learning Adversarial MDPs with Linear Function Approximation

Influence-aware Memory Architectures for Deep Reinforcement Learning

Learning to search efficiently for causally near-optimal treatments

Time Matters in Using Data Augmentation for Vision-based Deep Reinforcement Learning

Separated Proportional-Integral Lagrangian for Chance Constrained Reinforcement Learning

Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments

Multi-Stage Transmission Line Flow Control Using Centralized and Decentralized Reinforcement Learning Agents

Graph-based State Representation for Deep Reinforcement Learning

Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models

Generative Design by Reinforcement Learning: Enhancing the Diversity of Topology Optimization Designs

Inverse Reinforcement Learning in the Continuous Setting with Formal Guarantees

Data-Efficient Learning for Complex and Real-Time Physical Problem Solving using Augmented Simulation

Distributionally-Constrained Policy Optimization via Unbalanced Optimal Transport

Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees

Causal Markov Decision Processes: Learning Good Interventions Efficiently

Learning image quality assessment by reinforcing task amenable data selection

Almost Optimal Algorithms for Two-player Markov Games with Linear Function Approximation

Intelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement Learning

Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards

Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation

Sparse Attention Guided Dynamic Value Estimation for Single-Task Multi-Scene Reinforcement Learning

Reversible Action Design for Combinatorial Optimization with Reinforcement Learning

Model-free Representation Learning and Exploration in Low-rank MDPs

Equilibrium Inverse Reinforcement Learning for Ride-hailing Vehicle Network

Reinforcement Learning For Data Poisoning on Graph Neural Networks

Q-Value Weighted Regression: Reinforcement Learning with Limited Data

Upper Counterfactual Confidence Bounds: a New Optimism Principle for Contextual Bandits

RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning

Lifelong Incremental Reinforcement Learning with Online Bayesian Inference

Learning Robust State Abstractions for Hidden-Parameter Block MDPs

Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms

Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance Guarantees

Optimization Issues in KL-Constrained Approximate Policy Iteration

Representation Matters: Offline Pretraining for Sequential Decision Making

Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games

Machine versus Human Attention in Deep Reinforcement Learning Tasks

Personalization for Web-based Services using Offline Reinforcement Learning

Improving Model-Based Reinforcement Learning with Internal State Representations through Self-Supervision

PyTorchRL: Modular and Distributed Reinforcement Learning in PyTorch

Leveraging Reinforcement Learning for evaluating Robustness of KNN Search Algorithms

Enhancing efficiency of object recognition in different categorization levels by reinforcement learning in modular spiking neural networks

Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning

Policy Augmentation: An Exploration Strategy for Faster Convergence of Deep Reinforcement Learning Algorithms

Patterns, predictions, and actions: A story about machine learning

Multi-Agent Meta-Reinforcement Learning for Self-Powered and Sustainable Edge Computing Systems

Modeling the Interaction between Agents in Cooperative Multi-Agent Reinforcement Learning

Scheduling the NASA Deep Space Network with Deep Reinforcement Learning

Reinforcement Learning For Constraint Satisfaction Game Agents (15-Puzzle, Minesweeper, 2048, and Sudoku)

Deep Reinforcement Learning for Wireless Scheduling with Multiclass Services

Measuring Progress in Deep Reinforcement Learning Sample Efficiency

Structured Diversification Emergence via Reinforced Organization Control and Hierarchical Consensus Learning

Deep Reinforcement Learning Optimizes Graphene Nanopores for Efficient Desalination

Prior Preference Learning from Experts:Designing a Reward with Active Inference

Learning Causal State Representations of Partially Observable Environments

Contrasting Centralized and Decentralized Critics in Multi-Agent Reinforcement Learning

Learning Synthetic Environments for Reinforcement Learning with Evolution Strategies

Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning

NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning

SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments

Sparsely ensembled convolutional neural network classifiers via reinforcement learning

UPDeT: Universal Multi-agent Reinforcement Learning via Policy Decoupling with Transformers

A Sharp Analysis of Model-based Reinforcement Learning with Self-Play

A Hybrid Approach for Reinforcement Learning Using Virtual Policy Gradient for Balancing an Inverted Pendulum

GNN-RL Compression: Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning

Provably Efficient Algorithms for Multi-Objective Competitive RL

Deceptive Reinforcement Learning for Privacy-Preserving Planning

Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency

Alchemy: A structured task distribution for meta-reinforcement learning

Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments

Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design

Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning

Neural Recursive Belief States in Multi-Agent Reinforcement Learning

Near-Optimal Offline Reinforcement Learning via Double Variance Reduction

Towards Multi-agent Reinforcement Learning for Wireless Network Protocol Synthesis

Risk Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search

Improving Reinforcement Learning with Human Assistance: An Argument for Human Subject Studies with HIPPO Gym

Reinforcement Learning with Probabilistic Boolean Network Models of Smart Grid Devices

Efficient Reinforcement Learning for StarCraft by Abstract Forward Models and Transfer Learning

On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning

Learning Adversarial Markov Decision Processes with Delayed Feedback

Oracle-Efficient Reinforcement Learning in Factored MDPs with Unknown Structure

CoordiQ : Coordinated Q-learning for Electric Vehicle Charging Recommendation

The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors

Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning

Finite Sample Analysis of Two-Time-Scale Natural Actor-Critic Algorithm

Addressing Some Limitations of Transformers with Feedback Memory

ECOL-R: Encouraging Copying in Novel Object Captioning with Reinforcement Learning

GST: Group-Sparse Training for Accelerating Deep Reinforcement Learning

On Information Asymmetry in Competitive Multi-Agent Reinforcement Learning: Convergence and Optimality

Fully Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks

Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning

BNAS:An Efficient Neural Architecture Search Approach Using Broad Scalable Architecture

Variationally and Intrinsically motivated reinforcement learning for decentralized traffic signal control

The MineRL 2019 Competition on Sample Efficient Reinforcement Learning using Human Priors

Deep Reinforcement Learning for Producing Furniture Layout in Indoor Scenes

Learning Successor States and Goal-Dependent Values: A Mathematical Viewpoint

Langevin Dynamics for Adaptive Inverse Reinforcement Learning of Stochastic Gradient Algorithms

Stable deep reinforcement learning method by predicting uncertainty in rewards as a subtask

Cooperative and Competitive Biases for Multi-Agent Reinforcement Learning

Energy-based Surprise Minimization for Multi-Agent Value Factorization

Adaptive Remote Sensing Image Attribute Learning for Active Object Detection

Remote Electrical Tilt Optimization via Safe Reinforcement Learning

Robusta: Robust AutoML for Feature Selection via Reinforcement Learning

Evaluating Soccer Player: from Live Camera to Deep Reinforcement Learning

Learning and Fast Adaptation for Grid Emergency Control via Deep Meta Reinforcement Learning

EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL

Developing an OpenAI Gym-compatible framework and simulation environment for testing Deep Reinforcement Learning agents solving the Ambulance Location Problem

Linear Representation Meta-Reinforcement Learning for Instant Adaptation

Queue-Learning: A Reinforcement Learning Approach for Providing Quality of Service

Applicability and Challenges of Deep Reinforcement Learning for Satellite Frequency Plan Design

Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework

Independent Policy Gradient Methods for Competitive Reinforcement Learning

Learning Discrete State Abstractions With Deep Variational Inference

MELD: Meta-Reinforcement Learning from Images via Latent State Models

Deep Interactive Bayesian Reinforcement Learning via Meta-Learning

Provable Multi-Objective Reinforcement Learning with Generative Models

Resource Management in Wireless Networks via Multi-Agent Deep Reinforcement Learning

Parameterized MDPs and Reinforcement Learning Problems -- A Maximum Entropy Principle Based Framework

Identifying Decision Points for Safe and Interpretable Reinforcement Learning in Hypotension Treatment

Multi-path Neural Networks for On-device Multi-domain Visual Classification

Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes

CoachNet: An Adversarial Sampling Approach for Reinforcement Learning

Low Dimensional State Representation Learning with Reward-shaped Priors

Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints

Deep Reinforcement Learning with Quantum-inspired Experience Replay

An Efficient Asynchronous Method for Integrating Evolutionary and Gradient-based Policy Search

Enhanced Audit Techniques Empowered by the Reinforcement Learning Pertaining to IFRS 16 Lease

CARL: Controllable Agent with Reinforcement Learning for Quadruped Locomotion

MEDIRL: Predicting the Visual Attention of Drivers via Maximum Entropy Deep Inverse Reinforcement Learning

Health-Informed Policy Gradients for Multi-Agent Reinforcement Learning

The Value-Improvement Path: Towards Better Representations for Reinforcement Learning

Context-Aware Safe Reinforcement Learning for Non-Stationary Environments

A Provably Efficient Algorithm for Linear Markov Decision Process with Low Switching Cost

Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients

B-SMALL: A Bayesian Neural Network approach to Sparse Model-Agnostic Meta-Learning

Inverse reinforcement learning for autonomous navigation via differentiable semantic mapping and planning

Multi-agent Reinforcement Learning for Decentralized Stable Matching

AliExpress Learning-To-Rank: Maximizing Online Model Performance without Going Online

Asynchronous Advantage Actor Critic: Non-asymptotic Analysis and Linear Speedup

Auto Graph Encoder-Decoder for Model Compression and Network Acceleration

Model-Based Visual Planning with Self-Supervised Functional Distances

LISPR: An Options Framework for Policy Reuse with Reinforcement Learning

On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces

f-IRL: Inverse Reinforcement Learning via State Marginal Matching

Causal World Models by Unsupervised Deconfounding of Physical Dynamics

Risk-Sensitive Deep RL: Variance-Constrained Actor-Critic Provably Finds Globally Optimal Policy

Efficiency and Equity are Both Essential: A Generalized Traffic Signal Controller with Deep Reinforcement Learning

Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation

Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search

Towards Continual Reinforcement Learning: A Review and Perspectives

Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample Complexity

Off-Policy Exploitability-Evaluation in Two-Player Zero-Sum Markov Games

Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations

Regret Bound Balancing and Elimination for Model Selection in Bandits and RL

A Survey on Reinforcement Learning for Combinatorial Optimization

QVMix and QVMix-Max: Extending the Deep Quality-Value Family of Algorithms to Cooperative Multi-Agent Reinforcement Learning

Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies

Fast Physical Activity Suggestions: Efficient Hyperparameter Learning in Mobile Health

Offline Reinforcement Learning from Images with Latent Space Models

SIBRE: Self Improvement Based REwards for Adaptive Feedback in Reinforcement Learning

Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach

Multi-Decoder Attention Model with Embedding Glimpse for Solving Vehicle Routing Problems

CityLearn: Standardizing Research in Multi-Agent Reinforcement Learning for Demand Response and Urban Energy Management

Exact Reduction of Huge Action Spaces in General Reinforcement Learning

Centerline Depth World Reinforcement Learning-based Left Atrial Appendage Orifice Localization

Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning

MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning

Model-free and Bayesian Ensembling Model-based Deep Reinforcement Learning for Particle Accelerator Control Demonstrated on the FERMI FEL

Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic Forgetting

Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation

Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation

Learning to Sit: Synthesizing Human-Chair Interactions via Hierarchical Control

An Asymptotically Optimal Multi-Armed Bandit Algorithm and Hyperparameter Optimization

Learning to Run with Potential-Based Reward Shaping and Demonstrations from Video Data

Automated Design Space Exploration for optimised Deployment of DNN on Arm Cortex-A CPUs

Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning

OffWorld Gym: open-access physical robotics environment for real-world reinforcement learning benchmark and research

Feature Selection for Learning to Predict Outcomes of Compute Cluster Jobs with Application to Decision Support

SAT-MARL: Specification Aware Training in Multi-Agent Reinforcement Learning

Sim-to-real reinforcement learning applied to end-to-end vehicle control

Safe Reinforcement Learning with Stability & Safety Guarantees Using Robust MPC

Finite-Sample Analysis For Decentralized Batch Multi-Agent Reinforcement Learning With Networked Agents

Reinforcement Learning with Subspaces using Free Energy Paradigm

Semi-supervised reward learning for offline reinforcement learning

MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization

MLComp: A Methodology for Machine Learning-based Performance Estimation and Adaptive Selection of Pareto-Optimal Compiler Optimization Sequences

Performance-Weighed Policy Sampling for Meta-Reinforcement Learning

Risk-Averse Action Selection Using Extreme Value Theory Estimates of the CVaR

HIGhER : Improving instruction following with Hindsight Generation for Experience Replay

Exploration by Maximizing Rényi Entropy for Reward-Free RL Framework

MULTIPOLAR: Multi-Source Policy Aggregation for Transfer Reinforcement Learning between Diverse Environmental Dynamics

Optimal oracle inequalities for solving projected fixed-point equations

Deep Reinforcement Learning for Long Term Hydropower Production Scheduling

Extended Radial Basis Function Controller for Reinforcement Learning

A Deep Reinforcement Learning Approach for Ramp Metering Based on Traffic Video Data

Robust Domain Randomised Reinforcement Learning through Peer-to-Peer Distillation

Kinematics-Guided Reinforcement Learning for Object-Aware 3D Ego-Pose Estimation

A Model-free Learning Algorithm for Infinite-horizon Average-reward MDPs with Near-optimal Regret

Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning

Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes

Wasserstein Distance guided Adversarial Imitation Learning with Reward Shape Exploration

Reinforcement Based Learning on Classification Task Could Yield Better Generalization and Adversarial Accuracy

The Architectural Implications of Distributed Reinforcement Learning on CPU-GPU Systems

Distilled Thompson Sampling: Practical and Efficient Thompson Sampling via Imitation Learning

One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL

Resolving Spurious Correlations in Causal Models of Environments via Interventions

Efficient Reservoir Management through Deep Reinforcement Learning

Deep Policy Networks for NPC Behaviors that Adapt to Changing Design Parameters in Roguelike Games

Selective Pseudo-Labeling with Reinforcement Learning for Semi-Supervised Domain Adaptation

Vehicular Cooperative Perception Through Action Branching and Federated Reinforcement Learning

Mean-Variance Policy Iteration for Risk-Averse Reinforcement Learning

Hamiltonian Q-Learning: Leveraging Importance-sampling for Data Efficient RL

Optimistic Agent: Accurate Graph-Based Value Estimation for More Successful Visual Navigation

Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways

Distributed Multi-agent Meta Learning for Trajectory Design in Wireless Drone Networks

Demonstration-efficient Inverse Reinforcement Learning in Procedurally Generated Environments

Offline Meta-level Model-based Reinforcement Learning Approach for Cold-Start Recommendation

Counterfactual Data Augmentation using Locally Factored Dynamics

Dynamic RAN Slicing for Service-Oriented Vehicular Networks via Constrained Learning

DeepCrawl: Deep Reinforcement Learning for Turn-based Strategy Games

The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning

Learning Heuristics over Large Graphs via Deep Reinforcement Learning

Sample Complexity of Policy Gradient Finding Second-Order Stationary Points

Distributed Machine Learning for Wireless Communication Networks: Techniques, Architectures, and Applications

Convergence Proof for Actor-Critic Methods Applied to PPO and RUDDER

Are Gradient-based Saliency Maps Useful in Deep Reinforcement Learning?

Pareto Deterministic Policy Gradients and Its Application in 5G Massive MIMO Networks

Deep Model-Based Reinforcement Learning for High-Dimensional Problems, a Survey

Assessing and Accelerating Coverage in Deep Reinforcement Learning

Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning

Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning

Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning

IV-Posterior: Inverse Value Estimation for Interpretable Policy Certificates

Deep reinforcement learning with a particle dynamics environment applied to emergency evacuation of a room with obstacles

Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes

TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement Learning

Self-supervised Visual Reinforcement Learning with Object-centric Representations

Optimal Mixture Weights for Off-Policy Evaluation with Multiple Behavior Policies

DREAM: Deep Regret minimization with Advantage baselines and Model-free learning

Measuring Visual Generalization in Continuous Control from Pixels

Reinforcement Learning-based Joint Path and Energy Optimization of Cellular-Connected Unmanned Aerial Vehicles

Adaptable Automation with Modular Deep Reinforcement Learning and Policy Transfer

Efficient Information Diffusion in Time-Varying Graphs through Deep Reinforcement Learning

GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values

Predictive PER: Balancing Priority and Diversity towards Stable Deep Reinforcement Learning

System Identification via Meta-Learning in Linear Time-Varying Environments

Parameterized Reinforcement Learning for Optical System Optimization

Can $Q$-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?

PNS: Population-Guided Novelty Search Learning Method for Reinforcement Learning

Shapley Q-value: A Local Reward Approach to Solve Global Reward Games

Towards Learning Controllable Representations of Physical Systems

SegBlocks: Block-Based Dynamic Resolution Networks for Real-Time Segmentation

Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs

Interactively shaping robot behaviour with unlabeled human instructions

Solving The Lunar Lander Problem under Uncertainty using Reinforcement Learning

Joint Goal and Strategy Inference across Heterogeneous Demonstrators via Reward Network Distillation

GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations

An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare

Multi-Agent Reinforcement Learning for Dynamic Routing Games: A Unified Paradigm

Policy Teaching in Reinforcement Learning via Environment Poisoning Attacks

Double Meta-Learning for Data Efficient Policy Optimization in Non-Stationary Environments

No-Regret Reinforcement Learning with Value Function Approximation: a Kernel Embedding Approach

Efficient Exploration for Model-based Reinforcement Learning with Continuous States and Actions

Only Relevant Information Matters: Filtering Out Noisy Samples to Boost RL

Online Model Selection for Reinforcement Learning with Function Approximation

Inverse Reinforcement Learning via Matching of Optimality Profiles

OptiGAN: Generative Adversarial Networks for Goal Optimized Sequence Generation

A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress

Counterfactual Credit Assignment in Model-Free Reinforcement Learning

Edge Intelligence for Energy-efficient Computation Offloading and Resource Allocation in 5G Beyond

Deep Reinforcement Learning for Stochastic Computation Offloading in Digital Twin Networks

Weakly-Supervised Reinforcement Learning for Controllable Behavior

Multi-agent Reinforcement Learning Accelerated MCMC on Multiscale Inversion Problem

SeekNet: Improved Human Instance Segmentation via Reinforcement Learning Based Optimized Robot Relocation

Leveraging the Variance of Return Sequences for Exploration Policy

Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization

Low-latency Federated Learning and Blockchain for Edge Association in Digital Twin empowered 6G Networks

Dynamic Energy Dispatch Based on Deep Reinforcement Learning in IoT-Driven Smart Isolated Microgrids

Blind Decision Making: Reinforcement Learning with Delayed Observations

Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules

Learning Functionally Decomposed Hierarchies for Continuous Control Tasks with Path Planning

Reinforced Molecular Optimization with Neighborhood-Controlled Grammars

Convex Optimization with an Interpolation-based Projection and its Application to Deep Learning

Improving Offline Contextual Bandits with Distributional Robustness

ROLL: Visual Self-Supervised Reinforcement Learning with Object Reasoning

Critic PI2: Master Continuous Planning via Policy Improvement with Path Integrals and Deep Actor-Critic Reinforcement Learning

Generalized Inverse Planning: Learning Lifted non-Markovian Utility for Generalizable Task Representation

Reinforcement Learning with Videos: Combining Offline Observations with Interaction

On the convergence of projective-simulation-based reinforcement learning in Markov decision processes

Counterfactual Policy Evaluation for Decision-Making in Autonomous Driving

Cross Layer Optimization and Distributed Reinforcement Learning Approach for Tile-Based 360 Degree Wireless Video Streaming

Hierarchical reinforcement learning for efficient exploration and transfer

Automated Model Compression by Jointly Applied Pruning and Quantization

Gaussian RAM: Lightweight Image Classification via Stochastic Retina-Inspired Glimpse and Reinforcement Learning

Behaviorally Diverse Traffic Simulation via Reinforcement Learning

Proximal Policy Optimization via Enhanced Exploration Efficiency

Perturbation-based exploration methods in deep reinforcement learning

Emergent Reciprocity and Team Formation from Randomized Uncertain Social Preferences

Continual Learning of Control Primitives: Skill Discovery via Reset-Games

Uses and Abuses of the Cross-Entropy Loss: Case Studies in Modern Deep Learning

ActionSpotter: Deep Reinforcement Learning Framework for Temporal Action Spotting in Videos

Playing optical tweezers with deep reinforcement learning: in virtual, physical and augmented environments

Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms

Challenges of Applying Deep Reinforcement Learning in Dynamic Dispatching

Automated Adversary Emulation for Cyber-Physical Systems via Reinforcement Learning

Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning

Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning

Contrastive Variational Reinforcement Learning for Complex Observations

Multi-Agent Reinforcement Learning in Time-varying Networked Systems

Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient

Identifying Critical States by the Action-Based Variance of Expected Return

Single and Multi-Agent Deep Reinforcement Learning for AI-Enabled Wireless Networks: A Tutorial

The Value Equivalence Principle for Model-Based Reinforcement Learning

Robust Reinforcement Learning via Adversarial training with Langevin Dynamics

Learning to Utilize Shaping Rewards: A New Approach of Reward Shaping

Harnessing Distribution Ratio Estimators for Learning Agents with Quality and Diversity

Accelerating Deep Reinforcement Learning With the Aid of Partial Model: Energy-Efficient Predictive Video Streaming

Making Sense of Reinforcement Learning and Probabilistic Inference

A Variant of the Wang-Foster-Kakade Lower Bound for the Discounted Setting

Efficient Evaluation of Natural Stochastic Policies in Offline Reinforcement Learning

A Study of Policy Gradient on a Class of Exactly Solvable Models

Deep Reinforcement Learning Based Dynamic Route Planning for Minimizing Travel Time

PPO-CMA: Proximal Policy Optimization with Covariance Matrix Adaptation

Sample-efficient reinforcement learning using deep Gaussian processes

Reinforcement Learning with Efficient Active Feature Acquisition

BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning

Interpreting Graph Drawing with Multi-Agent Reinforcement Learning

Fast Reinforcement Learning with Incremental Gaussian Mixture Models

Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Learning Retrospective Knowledge with Reverse Reinforcement Learning

Adaptive Federated Learning and Digital Twin for Industrial Internet of Things

Image Classification by Reinforcement Learning with Two-State Q-Learning

Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation

Improving GAN Training with Probability Ratio Clipping and Sample Reweighting

Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics

Causal variables from reinforcement learning using generalized Bellman equations

A Composable Specification Language for Reinforcement Learning Tasks

Minimalistic Attacks: How Little it Takes to Fool a Deep Reinforcement Learning Policy

How do Offline Measures for Exploration in Reinforcement Learning behave?

Understanding the Pathologies of Approximate Policy Evaluation when Combined with Greedification in Reinforcement Learning

Finite-Time Analysis of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning

Model-based Policy Optimization with Unsupervised Model Adaptation

COG: Connecting New Skills to Past Experience with Offline Reinforcement Learning

Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning

Can Reinforcement Learning for Continuous Control Generalize Across Physics Engines?

Generating Automatic Curricula via Self-Supervised Active Domain Randomization

Reinforcement Learning Enhanced Heterogeneous Graph Neural Network

Track-Assignment Detailed Routing Using Attention-based Policy Model With Supervision

Neurosymbolic Reinforcement Learning with Formally Verified Exploration

Curriculum learning for multilevel budgeted combinatorial problems

Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model

UAV Path Planning for Wireless Data Harvesting: A Deep Reinforcement Learning Approach

Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning

Provably Efficient Safe Exploration via Primal-Dual Policy Optimization

Enhancing reinforcement learning by a finite reward response filter with a case study in intelligent structural control

Diff-DAC: Distributed Actor-Critic for Average Multitask Deep Reinforcement Learning

Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs

Improving the Exploration of Deep Reinforcement Learning in Continuous Domains using Planning for Policy Search

Beyond Exponentially Discounted Sum: Automatic Learning of Return Function

Preference-based Reinforcement Learning with Finite-Time Guarantees

Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning

Goal-directed Generation of Discrete Structures with Conditional Generative Models

Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces

Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning

Reinforcement Learning with Combinatorial Actions: An Application to Vehicle Routing

What are the Statistical Limits of Offline RL with Linear Function Approximation?

An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay

Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Learning Implicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning

Optimising Stochastic Routing for Taxi Fleets with Model Enhanced Reinforcement Learning

Fast Design Space Adaptation with Deep Reinforcement Learning for Analog Circuit Sizing

Selective Network Discovery via Deep Reinforcement Learning on Embedded Spaces

Deep Q-Network-based Adaptive Alert Threshold Selection Policy for Payment Fraud Systems in Retail Banking

Safe Reinforcement Learning with Nonlinear Dynamics via Model Predictive Shielding

Improving Generalization in Reinforcement Learning with Mixture Regularization

Safety Verification of Model Based Reinforcement Learning Controllers

Deep Reinforcement Learning in Lane Merge Coordination for Connected Vehicles

Reinforcement Learning for Optimization of COVID-19 Mitigation policies

Language Inference with Multi-head Automata through Reinforcement Learning

The Archimedean trap: Why traditional reinforcement learning will probably not yield AGI

Dream and Search to Control: Latent Space Planning for Continuous Control

Connections between Relational Event Model and Inverse Reinforcement Learning for Characterizing Group Interaction Sequences

Every Hidden Unit Maximizing Output Weights Maximizes The Global Reward

Chance-Constrained Control with Lexicographic Deep Reinforcement Learning

Learning Affordance Landscapes for Interaction Exploration in 3D Environments

Multi-Agent Reinforcement Learning in NOMA-aided UAV Networks for Cellular Offloading

DeepAveragers: Offline Reinforcement Learning by Solving Derived Non-Parametric MDPs

Assessment of Reward Functions in Reinforcement Learning for Multi-Modal Urban Traffic Control under Real-World limitations

Variational Dynamic for Self-Supervised Exploration in Deep Reinforcement Learning

Is Plug-in Solver Sample-Efficient for Feature-based Reinforcement Learning?

Policy Gradient for Continuing Tasks in Non-stationary Markov Decision Processes

Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control

Static Neural Compiler Optimization via Deep Reinforcement Learning

Interpretable Disease Prediction based on Reinforcement Path Reasoning over Knowledge Graphs

Policy Optimization Reinforcement Learning with Entropy Regularization

Deep Reinforcement Learning for Electric Transmission Voltage Control

Cooperative-Competitive Reinforcement Learning with History-Dependent Rewards

Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning

Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers

Blending Search and Discovery: Tag-Based Query Refinement with Contextual Reinforcement Learning

ALPaCA vs. GP-based Prior Learning: A Comparison between two Bayesian Meta-Learning Algorithms

An Alternative to Backpropagation in Deep Reinforcement Learning

Representation of Reinforcement Learning Policies in Reproducing Kernel Hilbert Spaces

A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning

A Nesterov's Accelerated quasi-Newton method for Global Routing using Deep Reinforcement Learning

Nonstationary Reinforcement Learning with Linear Function Approximation

Auto-STGCN: Autonomous Spatial-Temporal Graph Convolutional Network Search Based on Reinforcement Learning and Existing Research Results

Masked Contrastive Representation Learning for Reinforcement Learning

On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift

A Deep Q-Network for the Beer Game: A Deep Reinforcement Learning algorithm to Solve Inventory Optimization Problems

Adaptive Discretization for Continuous Control using Particle Filtering Policy Network

Random Network Distillation as a Diversity Metric for Both Image and Text Generation

Joint Perception and Control as Inference with an Object-based Implementation

Deep Reinforcement Learning and Transportation Research: A Comprehensive Review

AttendLight: Universal Attention-Based Reinforcement Learning Model for Traffic Signal Control

Deep Echo State Q-Network (DEQN) and Its Application in Dynamic Spectrum Sharing for 5G and Beyond

Leveraging the Capabilities of Connected and Autonomous Vehicles and Multi-Agent Reinforcement Learning to Mitigate Highway Bottleneck Congestion

Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image Classification

Fast active learning for pure exploration in reinforcement learning

Trust the Model When It Is Confident: Masked Model-based Actor-Critic

Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity

Robust Constrained-MDPs: Soft-Constrained Robust Policy Optimization under Model Uncertainty

Characterizing Policy Divergence for Personalized Meta-Reinforcement Learning

Hindsight Experience Replay with Kronecker Product Approximate Curvature

Deep RL With Information Constrained Policies: Generalization in Continuous Control

Instance Weighted Incremental Evolution Strategies for Reinforcement Learning in Dynamic Environments

EpidemiOptim: A Toolbox for the Optimization of Control Policies in Epidemiological Models

Continual learning using hash-routed convolutional neural networks

Learning to Locomote: Understanding How Environment Design Matters for Deep Reinforcement Learning

Information-Driven Adaptive Sensing Based on Deep Reinforcement Learning

Actor-Critic Algorithm for High-dimensional Partial Differential Equations

Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited

Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective

Minimax Weight and Q-Function Learning for Off-Policy Evaluation

Analytic Manifold Learning: Unifying and Evaluating Representations for Continuous Control

QTRAN++: Improved Value Transformation for Cooperative Multi-Agent Reinforcement Learning

Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning

AdaLead: A simple and robust adaptive greedy search algorithm for sequence design

A Novel Actor Dual-Critic Model for Remote Sensing Image Captioning

Action Guidance: Getting the Best of Sparse Rewards and Shaped Rewards for Real-time Strategy Games

The act of remembering: a study in partially observable reinforcement learning

Successor Features Combine Elements of Model-Free and Model-based Reinforcement Learning

Finding Effective Security Strategies through Reinforcement Learning and Self-Play

Deep Reinforcement Learning for Delay-Oriented IoT Task Scheduling in Space-Air-Ground Integrated Network

Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban

Provably More Efficient Q-Learning in the One-Sided-Feedback/Full-Feedback Settings

Reinforcement learning for the privacy preservation and manipulation of eye tracking data

Value-based Bayesian Meta-reinforcement Learning and Traffic Signal Control

Large-Scale Traffic Signal Control Using a Novel Multi-Agent Reinforcement Learning

Improving the Robustness of Graphs through Reinforcement Learning and Graph Neural Networks

Improving Generalization of Reinforcement Learning with Minimax Distributional Soft Actor-Critic

Bridging the gap between Markowitz planning and deep reinforcement learning

Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution

A Traffic Light Dynamic Control Algorithm with Deep Reinforcement Learning Based on GNN Prediction

PDLight: A Deep Reinforcement Learning Traffic Light Control Algorithm with Pressure and Dynamic Light Duration

Variance Reduced Advantage Estimation with $δ$ Hindsight Credit Assignment

Communicative Reinforcement Learning Agents for Landmark Detection in Brain Images

Reinforcement Learning-based N-ary Cross-Sentence Relation Extraction

Complementary Meta-Reinforcement Learning for Fault-Adaptive Control

Bootstrapped Q-learning with Context Relevant Observation Pruning to Generalize in Text-based Games

Learning in Volatile Environments with the Bayes Factor Surprise

What is the Reward for Handwriting? -- Handwriting Generation by Imitation Learning

Contextual Bandits for adapting to changing User preferences over time

Learn to Exceed: Stereo Inverse Reinforcement Learning with Concurrent Policy Optimization

Approximate exploitability: Learning a best response in large games

A Centralised Soft Actor Critic Deep Reinforcement Learning Approach to District Demand Side Management through CityLearn

Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learning

Option Discovery in Hierarchical Reinforcement Learning using Spatio-Temporal Clustering

A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning

CURL: Contrastive Unsupervised Representations for Reinforcement Learning

RL STaR Platform: Reinforcement Learning for Simulation based Training of Robots

Dynamic Horizon Value Estimation for Model-based Reinforcement Learning

Regret Bounds and Reinforcement Learning Exploration of EXP-based Algorithms

Simplifying Reinforced Feature Selection via Restructured Choice Strategy of Single Agent

Deep Reinforcement Learning for Closed-Loop Blood Glucose Control

HTMRL: Biologically Plausible Reinforcement Learning with Hierarchical Temporal Memory

DRL-FAS: A Novel Framework Based on Deep Reinforcement Learning for Face Anti-Spoofing

Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey

SREC: Proactive Self-Remedy of Energy-Constrained UAV-Based Networks via Deep Reinforcement Learning

GeneraLight: Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement Learning

Meta-AAD: Active Anomaly Detection with Deep Reinforcement Learning

Instance-dependent $\ell_\infty$-bounds for policy evaluation in tabular reinforcement learning

Autonomous Learning of Features for Control: Experiments with Embodied and Situated Agents

Risk-Sensitive Reinforcement Learning: a Martingale Approach to Reward Uncertainty

Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning

Multi-Objective Reinforcement Learning for Infectious Disease Control with Application to COVID-19 Spread

Guided Policy Search Based Control of a High Dimensional Advanced Manufacturing Process

RLCFR: Minimize Counterfactual Regret by Deep Reinforcement Learning

A framework for reinforcement learning with autocorrelated actions

COVID-19 Pandemic Cyclic Lockdown Optimization Using Reinforcement Learning

Controlling Level of Unconsciousness by Titrating Propofol with Deep Reinforcement Learning

DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control

Deep Learning and Reinforcement Learning for Autonomous Unmanned Aerial Systems: Roadmap for Theory to Deployment

Bayesian Inverse Reinforcement Learning for Collective Animal Movement

Reinforcement Learning on Job Shop Scheduling Problems Using Graph Networks

Deep Reinforcement Learning for Control of Probabilistic Boolean Networks

Safety Guarantees for Planning Based on Iterative Gaussian Processes

On the Expressivity of Neural Networks for Deep Reinforcement Learning

Visualizing the Loss Landscape of Actor Critic Methods with Applications in Inventory Optimization

Optimality-based Analysis of XCSF Compaction in Discrete Reinforcement Learning

Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model

A Multistep Lyapunov Approach for Finite-Time Analysis of Biased Stochastic Approximation

Dynamic Scheduling for Stochastic Edge-Cloud Computing Environments using A3C learning and Residual Recurrent Neural Networks

Deep Reinforcement Learning Designed Shinnar-Le Roux RF Pulse using Root-Flipping: DeepRF_SLR

Reinforced Axial Refinement Network for Monocular 3D Object Detection

Human-in-the-Loop Methods for Data-Driven and Reinforcement Learning Systems

Learning Classifiers on Positive and Unlabeled Data with Policy Gradient

Learning to Collaborate in Multi-Module Recommendation via Multi-Agent Reinforcement Learning without Communication

Voting-Based Multi-Agent Reinforcement Learning for Intelligent IoT

Delay-Aware Multi-Agent Reinforcement Learning for Cooperative and Competitive Environments

Sample Efficiency in Sparse Reinforcement Learning: Or Your Money Back

Meta Reinforcement Learning-Based Lane Change Strategy for Autonomous Vehicles

UNAS: Differentiable Architecture Search Meets Reinforcement Learning

A Deep Multi-Agent Reinforcement Learning Approach to Autonomous Separation Assurance

Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients

Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Constrained Markov Decision Processes via Backward Value Functions

NAS-DIP: Learning Deep Image Prior with Neural Architecture Search

Learning to Play No-Press Diplomacy with Best Response Policy Iteration

Inverse Policy Evaluation for Value-based Sequential Decision-making

Auxiliary-task Based Deep Reinforcement Learning for Participant Selection Problem in Mobile Crowdsourcing

Ensuring Monotonic Policy Improvement in Entropy-regularized Value-based Reinforcement Learning

Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow

Dynamic Dispatching for Large-Scale Heterogeneous Fleet via Multi-agent Deep Reinforcement Learning

CSCL: Critical Semantic-Consistent Learning for Unsupervised Domain Adaptation

Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison

Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning

Reward Design for Driver Repositioning Using Multi-Agent Reinforcement Learning

DSP: A Differential Spatial Prediction Scheme for Comprehensive real industrial datasets

Adapting Behaviour via Intrinsic Reward: A Survey and Empirical Study

Congested Urban Networks Tend to Be Insensitive to Signal Settings: Implications for Learning-Based Control

Online Learned Continual Compression with Adaptive Quantization Modules

Meta-Sim2: Unsupervised Learning of Scene Structure for Synthetic Data Generation

Reinforcement Learning for Low-Thrust Trajectory Design of Interplanetary Missions

Option Discovery in the Absence of Rewards with Manifold Analysis

Channel-wise Hessian Aware trace-Weighted Quantization of Neural Networks

Interestingness Elements for Explainable Reinforcement Learning: Understanding Agents' Capabilities and Limitations

Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning

Tripping through time: Efficient Localization of Activities in Videos

Towards Closing the Sim-to-Real Gap in Collaborative Multi-Robot Deep Reinforcement Learning

Generalized Maximum Causal Entropy for Inverse Reinforcement Learning

Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling

On the Sample Complexity of Reinforcement Learning with Policy Space Generalization

Imitation learning based on entropy-regularized forward and inverse reinforcement learning

Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence

SuperSuit: Simple Microwrappers for Reinforcement Learning Environments

Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems

AutoPose: Searching Multi-Scale Branch Aggregation for Pose Estimation

An adaptive synchronization approach for weights of deep reinforcement learning

The reinforcement learning-based multi-agent cooperative approach for the adaptive speed regulation on a metallurgical pickling line

What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?

Deep PQR: Solving Inverse Reinforcement Learning using Anchor Actions

Safe Reinforcement Learning in Constrained Markov Decision Processes

Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings

Composite Q-learning: Multi-scale Q-function Decomposition and Separable Optimization

Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions

PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning

I'm sorry Dave, I'm afraid I can't do that, Deep Q-learning from forbidden action

Leveraging Automated Mixed-Low-Precision Quantization for tiny edge microcontrollers

Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions

Reinforcement Learning Based Handwritten Digit Recognition with Two-State Q-Learning

Deep Reinforcement Learning with Label Embedding Reward for Supervised Image Hashing

Non-Adversarial Imitation Learning and its Connections to Adversarial Methods

Physics-Based Dexterous Manipulations with Estimated Hand Poses and Residual Reinforcement Learning

SafePILCO: a software tool for safe and data-efficient policy synthesis

Deep Q-Network Based Multi-agent Reinforcement Learning with Binary Action Agents

Fashion Captioning: Towards Generating Accurate Descriptions with Semantic Rewards

Follow the Object: Curriculum Learning for Manipulation Tasks with Imagined Goals

Optimizing AD Pruning of Sponsored Search with Reinforcement Learning

A Relearning Approach to Reinforcement Learning for Control of Smart Buildings

Learning Reinforced Agents with Counterfactual Simulation for Medical Automatic Diagnosis

Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills

Tracking the Race Between Deep Reinforcement Learning and Imitation Learning -- Extended Version

Dynamics Generalization via Information Bottleneck in Deep Reinforcement Learning

Predictive Coding for Boosting Deep Reinforcement Learning with Sparse Rewards

Fully Parameterized Quantile Function for Distributional Reinforcement Learning

Towards Efficient Connected and Automated Driving System via Multi-agent Graph Reinforcement Learning

Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning

Meta-SAC: Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient

Side-Tuning: A Baseline for Network Adaptation via Additive Side Networks

Moody Learners -- Explaining Competitive Behaviour of Reinforcement Learning Agents

Quantity vs. Quality: On Hyperparameter Optimization for Deep Reinforcement Learning

Compare and Select: Video Summarization with Multi-Agent Reinforcement Learning

Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders

Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning

Noisy Agents: Self-supervised Exploration by Predicting Auditory Events

Statistical Bootstrapping for Uncertainty Estimation in Off-Policy Evaluation

Leveraging Procedural Generation to Benchmark Reinforcement Learning

Unsupervisedly Learned Representations: Should the Quest be Over?

$H_\infty$ Model-free Reinforcement Learning with Robust Stability Guarantee

Variance Reduction for Deep Q-Learning using Stochastic Recursive Gradient

Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies

Challenging common bolus advisor for self-monitoring type-I diabetes patients using Reinforcement Learning

FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs

Provably Good Batch Reinforcement Learning Without Great Exploration

CATCH: Context-based Meta Reinforcement Learning for Transferrable Architecture Search

RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration

Adaptive Traffic Control with Deep Reinforcement Learning: Towards State-of-the-art and Beyond

Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search

Integrating Deep Reinforcement Learning Networks with Health System Simulations

Manipulating Reinforcement Learning: Poisoning Attacks on Cost Signals

A Short Note on Soft-max and Policy Gradients in Bandits Problems

Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning

Learning Force Control for Contact-rich Manipulation Tasks with Rigid Position-controlled Robots

PatchAttack: A Black-box Texture-based Attack with Reinforcement Learning

Learning Nearly Decomposable Value Functions Via Communication Minimization

Decentralized Deep Reinforcement Learning for Network Level Traffic Signal Control

Hierarchical Deep Reinforcement Learning Approach for Multi-Objective Scheduling With Varying Queue Sizes

PAC Bounds for Imitation and Model-based Batch Learning of Contextual Markov Decision Processes

Off-Policy Reinforcement Learning for Efficient and Effective GAN Architecture Search

Meta-Gradient Reinforcement Learning with an Objective Discovered Online

Learning to Transfer Learn: Reinforcement Learning-Based Selection for Adaptive Transfer Learning

VIREL: A Variational Inference Framework for Reinforcement Learning

Weighing Counts: Sequential Crowd Counting by Reinforcement Learning

DRIFT: Deep Reinforcement Learning for Functional Software Testing

Enhanced detection of fetal pose in 3D MRI by Deep Reinforcement Learning with physical structure priors on anatomy

Qgraph-bounded Q-learning: Stabilizing Model-Free Off-Policy Deep Reinforcement Learning

Robustifying Reinforcement Learning Agents via Action Space Adversarial Training

Compare and Reweight: Distinctive Image Captioning Using Similar Images Sets

Conditioning of Reinforcement Learning Agents and its Policy Regularization Application

A Provably Efficient Sample Collection Strategy for Reinforcement Learning

Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning

Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning

Deep Reinforced Attention Learning for Quality-Aware Visual Recognition

Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning

Learning Abstract Models for Strategic Exploration and Fast Reward Transfer

Simulating multi-exit evacuation using deep reinforcement learning

Long-Term Planning with Deep Reinforcement Learning on Autonomous Drones

Options as responses: Grounding behavioural hierarchies in multi-agent RL

Integrating Logical Rules Into Neural Multi-Hop Reasoning for Drug Repurposing

Pre-trained Word Embeddings for Goal-conditional Transfer Learning in Reinforcement Learning

A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces

One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control

Provable Self-Play Algorithms for Competitive Reinforcement Learning

Is Long Horizon Reinforcement Learning More Difficult Than Short Horizon Reinforcement Learning?

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images

Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning

RicciNets: Curvature-guided Pruning of High-performance Neural Networks Using Ricci Flow

Towards a practical measure of interference for reinforcement learning

Q-learning with Uniformly Bounded Variance: Large Discounting is Not a Barrier to Fast Learning

Predictive Maintenance for Edge-Based Sensor Networks: A Deep Reinforcement Learning Approach

Cognitive Radio Network Throughput Maximization with Deep Reinforcement Learning

An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality

Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning

TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?

Variational Policy Gradient Method for Reinforcement Learning with General Utilities

Harnessing Structures for Value-Based Planning and Reinforcement Learning

A Brief Look at Generalization in Visual Meta-Reinforcement Learning

Hedging using reinforcement learning: Contextual $k$-Armed Bandit versus $Q$-learning

Option Encoder: A Framework for Discovering a Policy Basis in Reinforcement Learning

Dueling Deep Q-Network for Unsupervised Inter-frame Eye Movement Correction in Optical Coherence Tomography Volumes

Reinforcement Learning Generalization with Surprise Minimization

ε-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning

Sequential Transfer in Reinforcement Learning with a Generative Model

Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search

Inferential Induction: A Novel Framework for Bayesian Reinforcement Learning

Student-Teacher Curriculum Learning via Reinforcement Learning: Predicting Hospital Inpatient Admission Location

Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving

Dynamic Regret of Policy Optimization in Non-stationary Environments

R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games

Reinforcement Learning for Robotic Manipulation using Simulated Locomotion Demonstrations

Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising

Dueling Posterior Sampling for Preference-Based Reinforcement Learning

Extracting Latent State Representations with Linear Dynamics from Rich Observations

Reinforcement Learning for Molecular Design Guided by Quantum Mechanics

Concept and the implementation of a tool to convert industry 4.0 environments modeled as FSM to an OpenAI Gym wrapper

Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning

Maximum Entropy Model Rollouts: Fast Model Based Policy Optimization without Compounding Errors

B-SCST: Bayesian Self-Critical Sequence Training for Image Captioning

Dynamic Sampling Networks for Efficient Action Recognition in Videos

Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?

DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning

A Closer Look at Invalid Action Masking in Policy Gradient Algorithms

Learning predictive representations in autonomous driving to improve deep reinforcement learning

What can I do here? A Theory of Affordances in Reinforcement Learning

Predicting Goal-directed Human Attention Using Inverse Reinforcement Learning

Noise, overestimation and exploration in Deep Reinforcement Learning

Generative Adversarial Imitation Learning with Neural Networks: Global Optimality and Convergence Rate

When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence

Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism

Local Stochastic Approximation: A Unified View of Federated Learning and Distributed Multi-Task Reinforcement Learning Algorithms

Adaptive Control and Regret Minimization in Linear Quadratic Gaussian (LQG) Setting

Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems

Control-Aware Representations for Model-based Reinforcement Learning

Towards Minimax Optimal Reinforcement Learning in Factored Markov Decision Processes

Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium

Environment Shaping in Reinforcement Learning using State Abstraction

Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization

Reward Tweaking: Maximizing the Total Reward While Planning for Short Horizons

Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning

Adaptive Reward-Poisoning Attacks against Reinforcement Learning

Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret

Graph Neural Networks and Reinforcement Learning for Behavior Generation in Semantic Environments

Provably Efficient Causal Reinforcement Learning with Confounded Observational Data

Constrained Combinatorial Optimization with Reinforcement Learning

Frequentist Regret Bounds for Randomized Least-Squares Value Iteration

Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning

Off-Policy Self-Critical Training for Transformer in Visual Paragraph Generation

$\sqrt{n}$-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank

Learning to combine primitive skills: A step towards versatile robotic manipulation

Unknown mixing times in apprenticeship and reinforcement learning

On Reward-Free Reinforcement Learning with Linear Function Approximation

Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension

Stable Policy Optimization via Off-Policy Divergence Regularization

Deep Reinforcement Learning for Human-Like Driving Policies in Collision Avoidance Tasks of Self-Driving Cars

A Reinforcement Learning Approach for Transient Control of Liquid Rocket Engines

NROWAN-DQN: A Stable Noisy Network with Noise Reduction and Online Weight Adjustment for Exploration

Efficient Ridesharing Dispatch Using Multi-Agent Reinforcement Learning

Adaptive Stress Testing without Domain Heuristics using Go-Explore

Cooperative Multi-Agent Reinforcement Learning with Partial Observations

Reparameterized Variational Divergence Minimization for Stable Imitation

Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning

Constructing Parsimonious Analytic Models for Dynamic Systems via Symbolic Regression

Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss

Active Learning for Nonlinear System Identification with Guarantees

Reducing Estimation Bias via Weighted Delayed Deep Deterministic Policy Gradient

Learning to Track Dynamic Targets in Partially Known Environments

Grasping in the Wild:Learning 6DoF Closed-Loop Grasping from Low-Cost Demonstrations

Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation

Forgetful Experience Replay in Hierarchical Reinforcement Learning from Demonstrations

Green Simulation Assisted Reinforcement Learning with Model Risk for Biomanufacturing Learning and Control

Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning

Solving the Order Batching and Sequencing Problem using Deep Reinforcement Learning

Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms

META-Learning Eligibility Traces for More Sample Efficient Temporal Difference Learning

Meta-Reinforcement Learning Robust to Distributional Shift via Model Identification and Experience Relabeling

Likelihood Quantile Networks for Coordinating Multi-Agent Reinforcement Learning

Near-Optimal Glimpse Sequences for Improved Hard Attention Neural Network Training

Adversarial Attacks and Detection on Reinforcement Learning-Based Interactive Recommender Systems

Reinforcement Learning with Supervision from Noisy Demonstrations

Non-local Policy Optimization via Diversity-regularized Collaborative Exploration

Safety-guaranteed Reinforcement Learning based on Multi-class Support Vector Machine

Mutual Information-based State-Control for Intrinsically Motivated Reinforcement Learning

Planning with Abstract Learned Models While Learning Transferable Subtasks

TorsionNet: A Reinforcement Learning Approach to Sequential Conformer Search

Mutual Information Based Knowledge Transfer Under State-Action Dimension Mismatch

StarCraft II Build Order Optimization using Deep Reinforcement Learning and Monte-Carlo Tree Search

Actor-Critic Policy Optimization in Partially Observable Multiagent Environments

Rotation, Translation, and Cropping for Zero-Shot Generalization

Learning to Solve Combinatorial Optimization Problems on Real-World Graphs in Linear Time

Feudal Steering: Hierarchical Learning for Steering Angle Prediction

Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination

DSAC: Distributional Soft Actor Critic for Risk-Sensitive Reinforcement Learning

Learning Navigation Costs from Demonstration with Semantic Observations

Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation

What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study

Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation

The Emergence of Individuality in Multi-Agent Reinforcement Learning

Contextual Policy Transfer in Reinforcement Learning Domains via Deep Mixtures-of-Experts

Causal Discovery from Incomplete Data using An Encoder and Reinforcement Learning

Distributed Learning on Heterogeneous Resource-Constrained Devices

Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory

Hallucinating Value: A Pitfall of Dyna-style Planning with Imperfect Environment Models

When Do Drivers Concentrate? Attention-based Driver Behavior Modeling With Deep Reinforcement Learning

Reinforcement Learning for Multi-Product Multi-Node Inventory Management in Supply Chains

Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity

Doubly Robust Off-Policy Value and Gradient Estimation for Deterministic Policies

Almost Optimal Model-Free Reinforcement Learning via Reference-Advantage Decomposition

Reinforcement Learning in Factored MDPs: Oracle-Efficient Algorithms and Tighter Regret Bounds for the Non-Episodic Setting

Learning Multi-Agent Coordination through Graph-driven Communication

Entropy-Augmented Entropy-Regularized Reinforcement Learning and a Continuous Path from Policy Gradient to Q-Learning

Concurrent Decentralized Channel Allocation and Access Point Selection using Multi-Armed Bandits in multi BSS WLANs

Explaining Autonomous Driving by Learning End-to-End Visual Attention

Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes

Visual Transfer for Reinforcement Learning via Wasserstein Domain Confusion

Refined Continuous Control of DDPG Actors via Parametrised Activation

Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty

Causality and Batch Reinforcement Learning: Complementary Approaches To Planning In Unknown Domains

Self-supervised Learning of Distance Functions for Goal-Conditioned Reinforcement Learning

Model-Based Reinforcement Learning with Value-Targeted Regression

Reinforcement learning and Bayesian data assimilation for model-informed precision dosing in oncology

Acme: A Research Framework for Distributed Reinforcement Learning

PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals

Adversarial Attacks on Reinforcement Learning based Energy Management Systems of Extended Range Electric Delivery Vehicles

MM-KTD: Multiple Model Kalman Temporal Differences for Reinforcement Learning

Local and Global Explanations of Agent Behavior: Integrating Strategy Summaries with Saliency Maps

Investigating Simple Object Representations in Model-Free Deep Reinforcement Learning

Domain Knowledge Integration By Gradient Matching For Sample-Efficient Reinforcement Learning

Emergence of Compositional Language with Deep Generational Transmission

Towards intervention-centric causal reasoning in learning agents

Meta-Reinforcement Learning for Trajectory Design in Wireless UAV Networks

Dynamic Value Estimation for Single-Task Multi-Scene Reinforcement Learning

Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO

Generator and Critic: A Deep Reinforcement Learning Approach for Slate Re-ranking in E-commerce

DRLViz: Understanding Decisions and Memory in Deep Reinforcement Learning

Efficient Deep Reinforcement Learning via Adaptive Policy Transfer

Should artificial agents ask for help in human-robot collaborative problem-solving?

When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey

Policy Gradient in Partially Observable Environments: Approximation and Convergence

Curiosity-Driven Experience Prioritization via Density Estimation

Learning Goal-Oriented Visual Dialog via Tempered Policy Gradient

Meta-Reinforcement Learning for Robotic Industrial Insertion Tasks

Attention Routing: track-assignment detailed routing using attention-based reinforcement learning

Towards Automated Safety Coverage and Testing for Autonomous Vehicles with Reinforcement Learning

Single-Agent Optimization Through Policy Iteration Using Monte-Carlo Tree Search

Automated Lane Change Strategy using Proximal Policy Optimization-based Deep Reinforcement Learning

Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise

Reinforcement Learning for Variable Selection in a Branch and Bound Algorithm

A reinforcement learning based decision support system in textile manufacturing process

Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning

Experience Augmentation: Boosting and Accelerating Off-Policy Multi-Agent Reinforcement Learning

Batch-Augmented Multi-Agent Reinforcement Learning for Efficient Traffic Signal Optimization

Ultrasound Video Summarization using Deep Reinforcement Learning

A Survey of Reinforcement Learning Algorithms for Dynamically Varying Environments

Prophet: Proactive Candidate-Selection for Federated Learning by Predicting the Qualities of Training and Reporting Phases

Non-Stationary Reinforcement Learning: The Blessing of (More) Optimism

Mutual Information Maximization for Robust Plannable Representations

Maximum Causal Entropy Specification Inference from Demonstrations

META-Learning State-based Eligibility Traces for More Sample-Efficient Policy Evaluation

EEG-based Drowsiness Estimation for Driving Safety using Deep Q-Learning

Safety Augmented Value Estimation from Demonstrations (SAVED): Safe Deep Model-Based RL for Sparse Cost Robotic Tasks

Proxy Experience Replay: Federated Distillation for Distributed Reinforcement Learning

Solve Traveling Salesman Problem by Monte Carlo Tree Search and Deep Neural Network

Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation

Unbiased Deep Reinforcement Learning: A General Training Framework for Existing and Future Algorithms

Delay-Aware Model-Based Reinforcement Learning for Continuous Control

Sketch Less for More: On-the-Fly Fine-Grained Sketch Based Image Retrieval

Reinforcement Learning for Thermostatically Controlled Loads Control using Modelica and Python

Hierarchical Cooperative Multi-Agent Reinforcement Learning with Skill Discovery

Non-asymptotic Convergence Analysis of Two Time-scale (Natural) Actor-Critic Algorithms

Intra-Variable Handwriting Inspection Reinforced with Idiosyncrasy Analysis

Covariance Matrix Adaptation for the Rapid Illumination of Behavior Space

AutoScale: Optimizing Energy Efficiency of End-to-End Edge Inference under Stochastic Variance

Demand-Side Scheduling Based on Deep Actor-Critic Learning for Smart Grids

Can We Learn Heuristics For Graphical Model Inference Using Reinforcement Learning?

Generalized Reinforcement Meta Learning for Few-Shot Optimization

Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey

Merging Deterministic Policy Gradient Estimations with Varied Bias-Variance Tradeoff for Effective Deep Reinforcement Learning

Improving Robustness via Risk Averse Distributional Reinforcement Learning

Learning robust control for LQR systems with multiplicative noise via policy gradient

Resource Management for Blockchain-enabled Federated Learning: A Deep Reinforcement Learning Approach

Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning

Maximum Likelihood Constraint Inference for Inverse Reinforcement Learning

Improving Target-driven Visual Navigation with Attention on 3D Spatial Relationships

Sample-Efficient Model-based Actor-Critic for an Interactive Dialogue Task

The Immersion of Directed Multi-graphs in Embedding Fields. Generalisations

Thinking While Moving: Deep Reinforcement Learning with Concurrent Control

The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget

Automatic low-bit hybrid quantization of neural networks through meta learning

Deep Reinforcement Learning with Modulated Hebbian plus Q Network Architecture

Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning

AutoEG: Automated Experience Grafting for Off-Policy Deep Reinforcement Learning

Comparing Observation and Action Representations for Deep Reinforcement Learning in $μ$RTS

Sequential Anomaly Detection using Inverse Reinforcement Learning

Statistically Model Checking PCTL Specifications on Markov Decision Processes via Reinforcement Learning

Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning

Improving reinforcement learning algorithms: towards optimal learning rate policies

Continual Reinforcement Learning in 3D Non-stationary Environments

Reinforcement Learning to Optimize the Logistics Distribution Routes of Unmanned Aerial Vehicle

Intelligent Querying for Target Tracking in Camera Networks using Deep Q-Learning with n-Step Bootstrapping

Learning When and Where to Zoom with Deep Reinforcement Learning

Learning as Reinforcement: Applying Principles of Neuroscience for More General Reinforcement Learning Agents

Model-Predictive Control via Cross-Entropy and Gradient-Based Optimization

Goal-conditioned Batch Reinforcement Learning for Rotation Invariant Locomotion

F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning

Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks

MARLeME: A Multi-Agent Reinforcement Learning Model Extraction Library

ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks

Analyzing Reinforcement Learning Benchmarks with Random Weight Guessing

Fast Template Matching and Update for Video Object Tracking and Segmentation

Diverse Behavior Is What Game AI Needs: Generating Varied Human-Like Playing Styles Using Evolutionary Multi-Objective Deep Reinforcement Learning

Reinforcement Learning in a Physics-Inspired Semi-Markov Environment

BabyAI++: Towards Grounded-Language Learning beyond Memorization

Bootstrapped model learning and error correction for planning with uncertainty in model-based RL

Neural Temporal-Difference and Q-Learning Provably Converge to Global Optima

Contextual-Bandit Anomaly Detection for IoT Data in Distributed Hierarchical Edge Computing

Stacked Auto Encoder Based Deep Reinforcement Learning for Online Resource Scheduling in Large-Scale MEC Networks

Google Research Football: A Novel Reinforcement Learning Environment

A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry

A Demonstration of Issues with Value-Based Multiobjective Reinforcement Learning Under Stochastic State Transitions

Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies

Imitation Learning for Fashion Style Based on Hierarchical Multimodal Representation

Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges

Federated Reinforcement Distillation with Proxy Experience Memory

Reinforcement Learning via Gaussian Processes with Neural Network Dual Kernels

CNN2Gate: Toward Designing a General Framework for Implementation of Convolutional Neural Networks on FPGA

Policy Gradient using Weak Derivatives for Reinforcement Learning

On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration

Deep Reinforcement Learning (DRL): Another Perspective for Unsupervised Wireless Localization

Continual Learning with Gated Incremental Memories for sequential data processing

Monte-Carlo Siamese Policy on Actor for Satellite Image Super Resolution

Stochastic Approximation with Markov Noise: Analysis and applications in reinforcement learning

How Do You Act? An Empirical Study to Understand Behavior of Deep Reinforcement Learning Agents

Ultrasound-Guided Robotic Navigation with Deep Reinforcement Learning

Efficient Object Detection in Large Images using Deep Reinforcement Learning

Technical Report: Adaptive Control for Linearizable Systems Using On-Policy Reinforcement Learning

Using Generative Adversarial Nets on Atari Games for Feature Extraction in Deep Reinforcement Learning

Unsupervised Reinforcement Learning of Transferable Meta-Skills for Embodied Navigation

Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal

Rationally Inattentive Inverse Reinforcement Learning Explains YouTube Commenting Behavior

Explain Your Move: Understanding Agent Actions Using Specific and Relevant Feature Attribution

Integrating Behavior Cloning and Reinforcement Learning for Improved Performance in Dense and Sparse Reward Environments

A Deep Ensemble Multi-Agent Reinforcement Learning Approach for Air Traffic Control

Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy

Average Reward Adjusted Discounted Reinforcement Learning: Near-Blackwell-Optimal Policies for Real-World Applications

Exploration of Reinforcement Learning for Event Camera using Car-like Robots

Towards Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling

Optimal Bidding Strategy without Exploration in Real-time Bidding

Optical Non-Line-of-Sight Physics-based 3D Human Pose Estimation

Importance of using appropriate baselines for evaluation of data-efficiency in deep reinforcement learning for Atari

POPCORN: Partially Observed Prediction COnstrained ReiNforcement Learning

Straight to the Point: Fast-forwarding Videos via Reinforcement Learning Using Textual Data

Posterior sampling for reinforcement learning: worst-case regret bounds

Stochastic Flows and Geometric Optimization on the Orthogonal Group

Gold Seeker: Information Gain from Policy Distributions for Goal-oriented Vision-and-Langauge Reasoning

Streamlined Empirical Bayes Fitting of Linear Mixed Models in Mobile Health

A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms

AirRL: A Reinforcement Learning Approach to Urban Air Quality Inference

Fiber: A Platform for Efficient Development and Distributed Training for Reinforcement Learning and Population-Based Methods

Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning

Learning to Play Soccer by Reinforcement and Applying Sim-to-Real to Compete in the Real World

Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning

Incorporating Relational Background Knowledge into Reinforcement Learning via Differentiable Inductive Logic Programming

Using Deep Reinforcement Learning Methods for Autonomous Vessels in 2D Environments

From Video Game to Real Robot: The Transfer between Action Spaces

Simultaneously Evolving Deep Reinforcement Learning Models using Multifactorial Optimization

Who2com: Collaborative Perception via Learnable Handshake Communication

Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks

Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task

Parameterized Indexed Value Function for Efficient Exploration in Reinforcement Learning

Mitigating Planner Overfitting in Model-Based Reinforcement Learning

A tutorial on recursive models for analyzing and predicting path choice behavior

Optimizing Medical Treatment for Sepsis in Intensive Care: from Reinforcement Learning to Pre-Trial Evaluation

Adversarial Active Exploration for Inverse Dynamics Model Learning

Improving Performance in Reinforcement Learning by Breaking Generalization in Neural Networks

DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction

End-to-End Model-Free Reinforcement Learning for Urban Driving using Implicit Affordances

Value Variance Minimization for Learning Approximate Equilibrium in Aggregation Systems

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Experimental Analysis of Reinforcement Learning Techniques for Spectrum Sharing Radar

The TrojAI Software Framework: An OpenSource tool for Embedding Trojans into Deep Learning Models

Sample Efficient Reinforcement Learning through Learning from Demonstrations in Minecraft

Heterogeneous Relational Reasoning in Knowledge Graphs with Reinforcement Learning

Analysis of Hyper-Parameters for Small Games: Iterations or Epochs in Self-Play?

Leveraging Communication Topologies Between Learning Agents in Deep Reinforcement Learning

On Hyper-parameter Tuning for Stochastic Optimization Algorithms

Transfer Reinforcement Learning under Unobserved Contextual Information

Human AI interaction loop training: New approach for interactive reinforcement learning

Zooming for Efficient Model-Free Reinforcement Learning in Metric Spaces

Software-Level Accuracy Using Stochastic Computing With Charge-Trap-Flash Based Weight Matrix

Learning Visuomotor Policies for Aerial Navigation Using Cross-Modal Representations

On the Robustness of Cooperative Multi-Agent Reinforcement Learning

Lane-Merging Using Policy-based Reinforcement Learning and Post-Optimization

Cost-Sensitive Portfolio Selection via Deep Reinforcement Learning

Balance Between Efficient and Effective Learning: Dense2Sparse Reward Shaping for Robot Manipulation with Environment Uncertainty

BERT as a Teacher: Contextual Embeddings for Sequence-Level Reward

Learning View and Target Invariant Visual Servoing for Navigation

Simulation-based reinforcement learning for real-world autonomous driving

MGHRL: Meta Goal-generation for Hierarchical Reinforcement Learning

Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards

Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning

A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation

Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning

Predicting optimal value functions by interpolating reward functions in scalarized multi-objective reinforcement learning

Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path

Learning Context-aware Task Reasoning for Efficient Meta-reinforcement Learning

Safe Reinforcement Learning for Autonomous Vehicles through Parallel Constrained Policy Optimization

PlaNet of the Bayesians: Reconsidering and Improving Deep Planning Network by Incorporating Bayesian Inference

RIDE: Rewarding Impact-Driven Exploration for Procedurally-Generated Environments

Weakly Supervised Video Summarization by Hierarchical Reinforcement Learning

Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?

Selective Transfer with Reinforced Transfer Network for Partial Domain Adaptation

Cautious Reinforcement Learning via Distributional Risk in the Dual Domain

Off-Policy Deep Reinforcement Learning with Analogous Disentangled Exploration

Training Adversarial Agents to Exploit Weaknesses in Deep Control Policies

Neural Architecture Evolution in Deep Reinforcement Learning for Continuous Control

Plannable Approximations to MDP Homomorphisms: Equivariance under Actions

GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation

Acceleration of Actor-Critic Deep Reinforcement Learning for Visual Grasping in Clutter by State Representation Learning Based on Disentanglement of a Raw Input Image

Learning Navigation Costs from Demonstration in Partially Observable Environments

Deep Reinforcement Learning with Linear Quadratic Regulator Regions

Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement

Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes

Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning

Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements

Can Agents Learn by Analogy? An Inferable Model for PAC Reinforcement Learning

Temporal Difference Models: Model-Free Deep RL for Model-Based Control

An Overview of Perception and Decision-Making in Autonomous Systems in the Era of Learning

How Transferable are the Representations Learned by Deep Q Agents?

Rapidly Personalizing Mobile Health Treatment Policies with Limited Data

Discriminative Particle Filter Reinforcement Learning for Complex Partial Observations

Constraining Implicit Space with Minimum Description Length: An Unsupervised Attention Mechanism across Neural Network Layers

Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation

Interaction-aware Decision Making with Adaptive Strategies under Merging Scenarios

Disentangling Controllable Object through Video Prediction Improves Visual Reinforcement Learning

Accelerating Reinforcement Learning with a Directional-Gaussian-Smoothing Evolution Strategy

oIRL: Robust Adversarial Inverse Reinforcement Learning with Temporally Extended Actions

Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning

Enhanced Adversarial Strategically-Timed Attacks against Deep Reinforcement Learning

Graph Convolutional Policy for Solving Tree Decomposition via Reinforcement Learning Heuristics

Learning with Good Feature Representations in Bandits and in RL with a Generative Model

Provably Efficient Reinforcement Learning with Aggregated States

Generalization of Reinforcement Learners with Working and Episodic Memory

Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation

GACEM: Generalized Autoregressive Cross Entropy Method for Multi-Modal Black Box Constraint Satisfaction

Tractable Reinforcement Learning of Signal Temporal Logic Objectives

Kalman meets Bellman: Improving Policy Evaluation through Value Tracking

Universal Value Density Estimation for Imitation Learning and Goal-Conditioned Reinforcement Learning

PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction

MRRC: Multiple Role Representation Crossover Interpretation for Image Captioning With R-CNN Feature Distribution Composition (FDC)

MDLdroid: a ChainSGD-reduce Approach to Mobile Deep Learning for Personal Mobile Sensing

Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning

Reinforcement Learning Enhanced Quantum-inspired Algorithm for Combinatorial Optimization

Improving Generalization in Meta Reinforcement Learning using Learned Objectives

Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization

Unsupervised Model Selection for Variational Disentangled Representation Learning

Dynamical Distance Learning for Semi-Supervised and Unsupervised Skill Discovery

Towards Similarity Graphs Constructed by Deep Reinforcement Learning

Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing

SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference

Robust Reinforcement Learning for Continuous Control with Model Misspecification

Learning Structured Communication for Multi-agent Reinforcement Learning

Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning

Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs

A Reinforcement Learning Framework for Time-Dependent Causal Effects Evaluation in A/B Testing

On the Convergence of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning

Towards Amortized Ranking-Critical Training for Collaborative Filtering

Stabilizing Deep Reinforcement Learning with Conservative Updates

A Deep Reinforcement Learning Algorithm Using Dynamic Attention Model for Vehicle Routing Problems

Comprehensive and Efficient Data Labeling via Adaptive Model Scheduling

RL-Duet: Online Music Accompaniment Generation Using Deep Reinforcement Learning

Off-policy Maximum Entropy Reinforcement Learning : Soft Actor-Critic with Advantage Weighted Mixture Policy(SAC-AWMP)

EgoMap: Projective mapping and structured egocentric memory for Deep RL

Adversarial Skill Networks: Unsupervised Robot Skill Learning from Video

Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making

Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks

Learning Task-Driven Control Policies via Information Bottlenecks

Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise

Optimal Passenger-Seeking Policies on E-hailing Platforms Using Markov Decision Process and Imitation Learning

Periodic Intra-Ensemble Knowledge Distillation for Reinforcement Learning

FiDi-RL: Incorporating Deep Reinforcement Learning with Finite-Difference Policy Search for Efficient Learning of Continuous Control

Predicting Goal-directed Attention Control Using Inverse-Reinforcement Learning

Exploratory Combinatorial Optimization with Reinforcement Learning

Multi-objective Neural Architecture Search via Non-stationary Policy Gradient

Survey of Deep Reinforcement Learning for Motion Planning of Autonomous Vehicles

Finite-Sample Analysis of Decentralized Temporal-Difference Learning with Linear Function Approximation

Using Fractal Neural Networks to Play SimCity 1 and Conway's Game of Life at Variable Scales

Variational Autoencoders for Opponent Modeling in Multi-Agent Systems

Robust Multimodal Image Registration Using Deep Recurrent Reinforcement Learning

Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning

Regret Bounds for Decentralized Learning in Cooperative Multi-Agent Dynamical Systems

Developing Multi-Task Recommendations with Long-Term Rewards via Policy Distilled Reinforcement Learning

Stochastic Recursive Variance Reduction for Efficient Smooth Non-Convex Compositional Optimization

CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning

End-to-End Vision-Based Adaptive Cruise Control (ACC) Using Deep Reinforcement Learning

Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation

Exploiting Hierarchy for Learning and Transfer in KL-regularized RL

IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks

Q-Learning in enormous action spaces via amortized approximate maximization

Local Policy Optimization for Trajectory-Centric Reinforcement Learning

On Solving Cooperative MARL Problems with a Few Good Experiences

CopyCAT: Taking Control of Neural Policies with Constant Attacks

Reinforcement Learning When All Actions are Not Always Available

DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames

Reinforcement Learning with Probabilistically Complete Exploration

Effects of sparse rewards of different magnitudes in the speed of learning of model-based actor critic methods

Tree-Structured Policy based Progressive Reinforcement Learning for Temporally Language Grounding in Video

Multi-agent Motion Planning for Dense and Dynamic Environments via Deep Reinforcement Learning

Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation

A Derivative-Free Method for Solving Elliptic Partial Differential Equations with Deep Neural Networks

Model-based Multi-Agent Reinforcement Learning with Cooperative Prioritized Sweeping

Robotic Grasp Manipulation Using Evolutionary Computing and Deep Reinforcement Learning

Non-Stationary Markov Decision Processes, a Worst-Case Approach using Model-Based Reinforcement Learning, Extended version

Continuous-action Reinforcement Learning for Playing Racing Games: Comparing SPG to PPO

NAT: Neural Architecture Transformer for Accurate and Compact Architectures

Closed-loop deep learning: generating forward models with back-propagation

Deep Reinforcement Learning for Complex Manipulation Tasks with Sparse Feedback

On Computation and Generalization of Generative Adversarial Imitation Learning

Represented Value Function Approach for Large Scale Multi Agent Reinforcement Learning

Identifying Distinct, Effective Treatments for Acute Hypotension with SODA-RL: Safely Optimized Diverse Accurate Reinforcement Learning

Finite-Time Analysis and Restarting Scheme for Linear Two-Time-Scale Stochastic Approximation

Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs

Population-Guided Parallel Policy Search for Reinforcement Learning

A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment

Optimal Options for Multi-Task Reinforcement Learning Under Time Constraints

Universal Successor Features for Transfer Reinforcement Learning

Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies

Optimizing Wireless Systems Using Unsupervised and Reinforced-Unsupervised Deep Learning

Zero-Shot Reinforcement Learning with Deep Attention Convolutional Neural Networks

Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics

Hierarchical model-based policy optimization: from actions to action sequences and back

A Reduction from Reinforcement Learning to No-Regret Online Learning

Generative Adversarial User Model for Reinforcement Learning Based Recommendation System

Long-Term Visitation Value for Deep Exploration in Sparse Reward Reinforcement Learning

Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning

Composing Task-Agnostic Policies with Deep Reinforcement Learning

Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

World Programs for Model-Based Learning and Planning in Compositional State and Action Spaces

Augmented Replay Memory in Reinforcement Learning With Continuous Control

Speeding up reinforcement learning by combining attention and agency features

SLM Lab: A Comprehensive Benchmark and Modular Software Framework for Reproducible Deep Reinforcement Learning

Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function

Regularizing Neural Networks for Future Trajectory Prediction via Inverse Reinforcement Learning Framework

Regularizing Trajectory Optimization with Denoising Autoencoders

Prioritized Guidance for Efficient Multi-Agent Reinforcement Learning Exploration

Variational Recurrent Models for Solving Partially Observable Control Tasks

Learning to Combat Compounding-Error in Model-Based Reinforcement Learning

Discrete and Continuous Action Representation for Practical RL in Video Games

Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning

Optimizing Collision Avoidance in Dense Airspace using Deep Reinforcement Learning

Exploiting the potential of deep reinforcement learning for classification tasks in high-dimensional and unstructured data

An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies

Taming an autonomous surface vehicle for path following and collision avoidance using deep reinforcement learning

Distributional Reinforcement Learning for Energy-Based Sequential Models

Unpaired Image Enhancement Featuring Reinforcement-Learning-Controlled Image Editing Software

S2DNAS:Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search

Regularized Anderson Acceleration for Off-Policy Deep Reinforcement Learning

Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data

Policy-Gradient Algorithms Have No Guarantees of Convergence in Linear Quadratic Games

PixelRL: Fully Convolutional Network with Reinforcement Learning for Image Processing

Natural Actor-Critic Converges Globally for Hierarchical Linear Quadratic Regulator

Recruitment-imitation Mechanism for Evolutionary Reinforcement Learning

More Efficient Off-Policy Evaluation through Regularized Targeted Learning

AC-Teach: A Bayesian Actor-Critic Method for Policy Learning with an Ensemble of Suboptimal Teachers

Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs

Online Deep Reinforcement Learning for Autonomous UAV Navigation and Exploration of Outdoor Environments

Near-optimal Optimistic Reinforcement Learning using Empirical Bernstein Inequalities

Marginalized State Distribution Entropy Regularization in Policy Optimization

Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning

Entropy Regularization with Discounted Future State Distribution in Policy Gradient Methods

Efficient and Robust Reinforcement Learning with Uncertainty-based Value Expansion

Reducing Catastrophic Forgetting in Modular Neural Networks by Dynamic Information Balancing

Adversarial recovery of agent rewards from latent spaces of the limit order book

Learning Latent State Spaces for Planning through Reward Prediction

Optimism in Reinforcement Learning with Generalized Linear Function Approximation

Modelling Bahdanau Attention using Election methods aided by Q-Learning

Learning Sparse Representations Incrementally in Deep Reinforcement Learning

Decentralized Multi-Agent Reinforcement Learning with Networked Agents: Recent Advances

From semantics to execution: Integrating action planning with reinforcement learning for robotic causal problem-solving

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning

Value-of-Information based Arbitration between Model-based and Model-free Control

Risk-Averse Trust Region Optimization for Reward-Volatility Reduction

Introducing Neuromodulation in Deep Neural Networks to Learn Adaptive Behaviours

A pedestrian path-planning model in accordance with obstacle's danger with reinforcement learning

Blind Inpainting of Large-scale Masks of Thin Structures with Adversarial and Reinforcement Learning

An Information-theoretic On-line Learning Principle for Specialization in Hierarchical Decision-Making Systems

A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound

Mo' States Mo' Problems: Emergency Stop Mechanisms from Observation

Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

Neural Architecture Refinement: A Practical Way for Avoiding Overfitting in NAS

Reducing Overestimation Bias in Multi-Agent Domains Using Double Centralized Critics

ORL: Reinforcement Learning Benchmarks for Online Stochastic Optimization Problems

Optimization for Reinforcement Learning: From Single Agent to Cooperative Agents

Off-Policy Policy Gradient Algorithms by Constraining the State Distribution Shift

Quadratic Q-network for Learning Continuous Control for Autonomous Vehicles

Qualitative Measurements of Policy Discrepancy for Return-Based Deep Q-Network

Where to Look Next: Unsupervised Active Visual Exploration on 360° Input

Predicting Head Movement in Panoramic Video: A Deep Reinforcement Learning Approach

Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization

Augmented Random Search for Quadcopter Control: An alternative to Reinforcement Learning

Improving Fictitious Play Reinforcement Learning with Expanding Models

Control-Tutored Reinforcement Learning: an application to the Herding Problem

GRIm-RePR: Prioritising Generating Important Features for Pseudo-Rehearsal

Multi-Agent Actor-Critic with Hierarchical Graph Attention Network

The problem with DDPG: understanding failures in deterministic environments with sparse rewards

Fully Bayesian Recurrent Neural Networks for Safe Reinforcement Learning

Self-organization of action hierarchy and compositionality by reinforcement learning with recurrent neural networks

An Autonomous Spectrum Management Scheme for Unmanned Aerial Vehicle Networks in Disaster Relief Operations

Biologically inspired architectures for sample-efficient deep reinforcement learning

Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem

Theory-based Causal Transfer: Integrating Instance-level Induction and Abstract-level Structure Learning

Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction

Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems

Disentangled Cumulants Help Successor Representations Transfer to New Tasks

Mitigate Bias in Face Recognition using Skewness-Aware Reinforcement Learning

A Deep Reinforcement Learning Architecture for Multi-stage Optimal Control

Which Channel to Ask My Question? Personalized Customer Service Request Stream Routing using Deep Reinforcement Learning

Reinforcement Learning from Imperfect Demonstrations under Soft Expert Guidance

From Persistent Homology to Reinforcement Learning with Applications for Retail Banking

Iteratively-Refined Interactive 3D Medical Image Segmentation with Multi-Agent Reinforcement Learning

Fleet Control using Coregionalized Gaussian Process Policy Iteration

Self-Attentional Credit Assignment for Transfer in Reinforcement Learning

Modular Deep Reinforcement Learning with Temporal Logic Specifications

Reinforcing an Image Caption Generator Using Off-Line Human Feedback

Information-Theoretic Confidence Bounds for Reinforcement Learning

Sample-Efficient Reinforcement Learning with Maximum Entropy Mellowmax Episodic Control

Memory-Efficient Episodic Control Reinforcement Learning with Dynamic Online k-means

GAN-powered Deep Distributional Reinforcement Learning for Resource Management in Network Slicing

Bayesian Curiosity for Efficient Exploration in Reinforcement Learning

Evaluating task-agnostic exploration for fixed-batch learning of arbitrary future tasks

Unsupervised Learning of Object Keypoints for Perception and Control

Efficient decorrelation of features using Gramian in Reinforcement Learning

Generalizable Resource Allocation in Stream Processing via Deep Reinforcement Learning

MANGA: Method Agnostic Neural-policy Generalization and Adaptation

Finite-Sample Analysis for SARSA with Linear Function Approximation

Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents

Efficient Exploration through Intrinsic Motivation Learning for Unsupervised Subgoal Discovery in Model-Free Hierarchical Reinforcement Learning

Language as an Abstraction for Hierarchical Deep Reinforcement Learning

A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning

Policy Search by Target Distribution Learning for Continuous Control

Collaborative Graph Walk for Semi-supervised Multi-Label Node Classification

Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient

Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning

Automated Augmentation with Reinforcement Learning and GANs for Robust Identification of Traffic Signs using Front Camera Images

Uncertainty-based Continual Learning with Adaptive Regularization

Atari-fying the Vehicle Routing Problem with Stochastic Service Requests

Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning

Learning to Communicate in Multi-Agent Reinforcement Learning : A Review

Accelerating Training in Pommerman with Imitation and Reinforcement Learning

Tactics of Adversarial Attack on Deep Reinforcement Learning Agents

Split Q Learning: Reinforcement Learning with Two-Stream Rewards

Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning

Schedule Earth Observation satellites with Deep Reinforcement Learning

Sample-Efficient Deep Reinforcement Learning via Episodic Backward Update

Learning Representations in Reinforcement Learning:An Information Bottleneck Approach

Reinforcement-Learning-Based Variational Quantum Circuits Optimization for Combinatorial Problems

Foundations for Restraining Bolts: Reinforcement Learning with LTLf/LDLf restraining specifications

Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learning

Privacy-preserving Q-Learning with Functional Noise in Continuous State Spaces

A Divergence Minimization Perspective on Imitation Learning Methods

A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation

Experience Sharing Between Cooperative Reinforcement Learning Agents

DeepRacer: Educational Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning

DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections

Provably Efficient $Q$-learning with Function Approximation via Distribution Shift Error Checking Oracle

An End-to-End Deep RL Framework for Task Arrangement in Crowdsourcing Platforms

A Model-based Approach for Sample-efficient Multi-task Reinforcement Learning

Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs

Maximum Entropy Diverse Exploration: Disentangling Maximum Entropy Reinforcement Learning

Thompson Sampling for Contextual Bandit Problems with Auxiliary Safety Constraints

Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds

Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control

Situated GAIL: Multitask imitation using task-conditioned adversarial inverse reinforcement learning

Read, Highlight and Summarize: A Hierarchical Neural Semantic Encoder-based Approach

Multi-Agent Reinforcement Learning with Multi-Step Generative Models

Safe, Efficient, and Comfortable Velocity Control based on Reinforcement Learning for Autonomous Driving

DeepLine: AutoML Tool for Pipelines Generation using Deep Reinforcement Learning and Hierarchical Actions Filtering

PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning

Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies

Adaptive Discretization for Episodic Reinforcement Learning in Metric Spaces

VASE: Variational Assorted Surprise Exploration for Reinforcement Learning

A Distributed Model-Free Algorithm for Multi-hop Ride-sharing using Deep Reinforcement Learning

Explainable AI: Deep Reinforcement Learning Agents for Residential Demand Side Cost Savings in Smart Grids

DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning

Learning to Perform Local Rewriting for Combinatorial Optimization

Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation

Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints

Improving Coordination in Small-Scale Multi-Agent Deep Reinforcement Learning through Memory-driven Communication

On Connections between Constrained Optimization and Reinforcement Learning

Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments

Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck

ZPD Teaching Strategies for Deep Reinforcement Learning from Demonstrations

Meta-Inverse Reinforcement Learning with Probabilistic Context Variables

Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning

HRL4IN: Hierarchical Reinforcement Learning for Interactive Navigation with Mobile Manipulators

Attention-based Curiosity-driven Exploration in Deep Reinforcement Learning

Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles

Reinforcement Learning with Structured Hierarchical Grammar Representations of Actions

Efficient Decoupled Neural Architecture Search by Structure and Operation Sampling

Distributed Power Control for Large Energy Harvesting Networks: A Multi-Agent Deep Reinforcement Learning Approach

Automatic Data Augmentation by Learning the Deterministic Policy

Model-free Deep Reinforcement Learning for Urban Autonomous Driving

A New Framework for Multi-Agent Reinforcement Learning -- Centralized Training and Exploration with Decentralized Execution via Policy Distillation

All-Action Policy Gradient Methods: A Numerical Integration Approach

A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning

Active 6D Multi-Object Pose Estimation in Cluttered Scenarios with Deep Reinforcement Learning

A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning

NEURO-DRAM: a 3D recurrent visual attention model for interpretable neuroimaging classification

On the Sample Complexity of Actor-Critic Method for Reinforcement Learning with Function Approximation

CrossNorm: Normalization for Off-Policy TD Reinforcement Learning

Creativity in Robot Manipulation with Deep Reinforcement Learning

Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments

Integration of Imitation Learning using GAIL and Reinforcement Learning using Task-achievement Rewards via Probabilistic Graphical Model

How a minimal learning agent can infer the existence of unobserved variables in a complex environment

Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions

A unified view of likelihood ratio and reparameterization gradients and an optimal importance sampling scheme

Learning a Prior over Intent via Meta-Inverse Reinforcement Learning

Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations

On the Convergence of Approximate and Regularized Policy Iteration Schemes

Federated Transfer Reinforcement Learning for Autonomous Driving

Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms

On the Reduction of Variance and Overestimation of Deep Q-Learning

Autonomous Navigation via Deep Reinforcement Learning for Resource Constraint Edge Nodes using Transfer Learning

Green Deep Reinforcement Learning for Radio Resource Management: Architecture, Algorithm Compression and Challenge

HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints

SURREAL-System: Fully-Integrated Stack for Distributed Deep Reinforcement Learning

Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling

Multi-agent Inverse Reinforcement Learning for Certain General-sum Stochastic Games

Efficient Intrinsically Motivated Robotic Grasping with Learning-Adaptive Imagination in Latent Space

Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards

PAC Guarantees for Cooperative Multi-Agent Reinforcement Learning with Restricted Communication

Model-Based Reinforcement Learning Exploiting State-Action Equivalence

Multiple-objective Reinforcement Learning for Inverse Design and Identification

Sim-to-Real Transfer of Robot Learning with Variable Length Inputs

Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

Reinforcing Medical Image Classifier to Improve Generalization on Small Datasets

Variational Inference MPC for Bayesian Model-based Reinforcement Learning

Biased Aggregation, Rollout, and Enhanced Policy Improvement for Reinforcement Learning

Manufacturing Dispatching using Reinforcement and Transfer Learning

Learning Robust Representations with Graph Denoising Policy Network

Improving Generative Visual Dialog by Answering Diverse Questions

Analyzing the Variance of Policy Gradient Estimators for the Linear-Quadratic Regulator

Deep Reinforcement Learning for Single-Shot Diagnosis and Adaptation in Damaged Robots

CWAE-IRL: Formulating a supervised approach to Inverse Reinforcement Learning problem

Learning scalable and transferable multi-robot/machine sequential assignment planning via graph embedding

RLCache: Automated Cache Management Using Reinforcement Learning

Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving

Tensor-based Cooperative Control for Large Scale Multi-intersection Traffic Signal Using Deep Reinforcement Learning and Imitation Learning

Optimizing Design Verification using Machine Learning: Doing better than Random

Accelerating the Computation of UCB and Related Indices for Reinforcement Learning

Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning

Counterfactual States for Atari Agents via Generative Deep Learning

Adaptive ROI Generation for Video Object Segmentation Using Reinforcement Learning

Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP

RL-LIM: Reinforcement Learning-based Locally Interpretable Modeling

RecSim: A Configurable Simulation Platform for Recommender Systems

Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over Simplex

SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards

Leveraging exploration in off-policy algorithms via normalizing flows

ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch

Active Learning for Risk-Sensitive Inverse Reinforcement Learning

Integrating independent and centralized multi-agent reinforcement learning for traffic signal network optimization

Compiler-Level Matrix Multiplication Optimization for Deep Learning

Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Estimators for Reinforcement Learning

Semantic RL with Action Grammars: Data-Efficient Learning of Hierarchical Task Abstractions

Multi-task Learning and Catastrophic Forgetting in Continual Reinforcement Learning

A Layered Architecture for Active Perception: Image Classification using Deep Reinforcement Learning

Transferable Pedestrian Motion Prediction Models at Intersections

Visual Tracking by means of Deep Reinforcement Learning and an Expert Demonstrator

A Hierarchical Two-tier Approach to Hyper-parameter Optimization in Reinforcement Learning

A Review of Tracking, Prediction and Decision Making Methods for Autonomous Driving

Wield: Systematic Reinforcement Learning With Progressive Randomization

Policy Prediction Network: Model-Free Behavior Policy with Model-Based Learning in Continuous Action Space

VILD: Variational Imitation Learning with Diverse-quality Demonstrations

Deep Reinforcement Learning For Modeling Chit-Chat Dialog With Discrete Attributes

AITuning: Machine Learning-based Tuning Tool for Run-Time Communication Libraries

DL2: A Deep Learning-driven Scheduler for Deep Learning Clusters

Reinforcement Learning: a Comparison of UCB Versus Alternative Adaptive Policies

An Online Reinforcement Learning Approach to Quality-Cost-Aware Task Allocation for Multi-Attribute Social Sensing

Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning

AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates

A Survey on Reproducibility by Evaluating Deep Reinforcement Learning Algorithms on Real-World Robots

Neural Proximal/Trust Region Policy Optimization Attains Globally Optimal Policy

Multi-Point Bandit Algorithms for Nonstationary Online Nonconvex Optimization

Translating Math Formula Images to LaTeX Sequences Using Deep Neural Networks with Sequence-level Training

Adversarial Policy Gradient for Deep Learning Image Augmentation

Solving Continual Combinatorial Selection via Deep Reinforcement Learning

Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity

Soft Policy Gradient Method for Maximum Entropy Deep Reinforcement Learning

Gradient Q$(σ, λ)$: A Unified Algorithm with Function Approximation for Reinforcement Learning

Classification with Costly Features as a Sequential Decision-Making Problem

Surprising Negative Results for Generative Adversarial Tree Search

Horizon: Facebook's Open Source Applied Reinforcement Learning Platform

Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?

Quasi-Newton Optimization Methods For Deep Learning Applications

Augmented Memory Networks for Streaming-Based Active One-Shot Learning

Deep Reinforcement Learning for Unmanned Aerial Vehicle-Assisted Vehicular Networks

Personalized Cancer Chemotherapy Schedule: a numerical comparison of performance and robustness in model-based and model-free scheduling methodologies

Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research

Curiosity-driven Reinforcement Learning for Diverse Visual Paragraph Generation

Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity

Learning 3D Navigation Protocols on Touch Interfaces with Cooperative Multi-Agent Reinforcement Learning

Urban flows prediction from spatial-temporal data using machine learning: A survey

On Convergence Rate of Adaptive Multiscale Value Function Approximation For Reinforcement Learning

Efficient Policy Learning for Non-Stationary MDPs under Adversarial Manipulation

MQLV: Optimal Policy of Money Management in Retail Banking with Q-Learning

A Deep Actor-Critic Reinforcement Learning Framework for Dynamic Multichannel Access

Skill Transfer in Deep Reinforcement Learning under Morphological Heterogeneity

3D Traffic Simulation for Autonomous Vehicles in Unity and Python

GraphNAS: Graph Neural Architecture Search with Reinforcement Learning

Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to ATARI games

Learning to Advertise for Organic Traffic Maximization in E-Commerce Product Feeds

Mitigating Multi-Stage Cascading Failure by Reinforcement Learning

VUSFA:Variational Universal Successor Features Approximator to Improve Transfer DRL for Target Driven Visual Navigation

Worst-Case Regret Bounds for Exploration via Randomized Value Functions

Online Feature Selection for Activity Recognition using Reinforcement Learning with Multiple Feedback

Deceptive Reinforcement Learning Under Adversarial Manipulations on Cost Signals

Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking

Iterative Update and Unified Representation for Multi-Agent Reinforcement Learning

Unpaired Cross-lingual Image Caption Generation with Self-Supervised Rewards

COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration

VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering

Towards Diverse and Accurate Image Captions via Reinforcing Determinantal Point Process

From Crystallized Adaptivity to Fluid Adaptivity in Deep Reinforcement Learning -- Insights from Biological Systems on Adaptive Flexibility

Superstition in the Network: Deep Reinforcement Learning Plays Deceptive Games

Dot-to-Dot: Explainable Hierarchical Reinforcement Learning for Robotic Manipulation

Load Balancing for Ultra-Dense Networks: A Deep Reinforcement Learning Based Approach

Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods

Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations

Incremental Reinforcement Learning --- a New Continuous Reinforcement Learning Frame Based on Stochastic Differential Equation methods

Provably Efficient Reinforcement Learning with Linear Function Approximation

Barrier-Certified Adaptive Reinforcement Learning with Applications to Brushbot Navigation

Attention Control with Metric Learning Alignment for Image Set-based Recognition

Improving Deep Reinforcement Learning in Minecraft with Action Advice

Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition

Robby is Not a Robber (anymore): On the Use of Institutions for Learning Normative Behavior

Reinforcement Learning with Wasserstein Distance Regularisation, with Applications to Multipolicy Learning

Model-Free Unsupervised Learning for Optimization Problems with Constraints

Control of nonlinear, complex and black-boxed greenhouse system with reinforcement learning

On Hard Exploration for Reinforcement Learning: a Case Study in Pommerman

Deep Reinforcement Learning for Personalized Search Story Recommendation

PPO Dash: Improving Generalization in Deep Reinforcement Learning

Dynamic Input for Deep Reinforcement Learning in Autonomous Driving

Terminal Prediction as an Auxiliary Task for Deep Reinforcement Learning

Multiple Landmark Detection using Multi-Agent Reinforcement Learning

Deep Reinforcement Learning for Clinical Decision Support: A Brief Survey

Towards Robust Deep Reinforcement Learning for Traffic Signal Control: Demand Surges, Incidents and Sensor Failures

An Actor-Critic-Attention Mechanism for Deep Reinforcement Learning in Multi-view Environments

Delegative Reinforcement Learning: learning to avoid traps with a little help

Relative Importance Sampling For Off-Policy Actor-Critic in Deep Reinforcement Learning

An Inductive Synthesis Framework for Verifiable Reinforcement Learning

Improved Reinforcement Learning through Imitation Learning Pretraining Towards Image-based Autonomous Driving

Efficient Autonomy Validation in Simulation with Adaptive Stress Testing

A Dual Memory Structure for Efficient Use of Replay Memory in Deep Reinforcement Learning

Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning

On the Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost

Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation

A Systematic Mapping Study on Testing of Machine Learning Programs

DisCoRL: Continual Reinforcement Learning via Policy Distillation

Constrained Policy Improvement for Safe and Efficient Reinforcement Learning

Interpretable Dynamics Models for Data-Efficient Reinforcement Learning

Variance-Based Risk Estimations in Markov Processes via Transformation with State Lumping

Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations

Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog

Provably Robust Blackbox Optimization for Reinforcement Learning

Intrinsic Motivation Driven Intuitive Physics Learning using Deep Reinforcement Learning with Intrinsic Reward Normalization

Playing Flappy Bird via Asynchronous Advantage Actor Critic Algorithm

A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning

Dependency-aware Attention Control for Unconstrained Face Recognition with Image Sets

Hierarchical Deep Multiagent Reinforcement Learning with Temporal Abstraction

Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation

Generalizing from a few environments in safety-critical reinforcement learning

CRAVES: Controlling Robotic Arm with a Vision-based Economic System

On mechanisms for transfer using landmark value functions in multi-task lifelong reinforcement learning

Learning World Graphs to Accelerate Hierarchical Reinforcement Learning

Cost-Sensitive Diagnosis and Learning Leveraging Public Health Data

Reinforcement Learning with Policy Mixture Model for Temporal Point Processes Clustering

Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions

Multi-agent Deep Reinforcement Learning for Zero Energy Communities

Emergence of Exploratory Look-Around Behaviors through Active Observation Completion

A Tractable Algorithm For Finite-Horizon Continuous Reinforcement Learning

A Geometric Perspective on Optimal Representations for Reinforcement Learning

Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives

Stochastic approximation with cone-contractive operators: Sharp $\ell_\infty$-bounds for $Q$-learning

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference

Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics

SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning

Learning Belief Representations for Imitation Learning in POMDPs

A neurally plausible model learns successor representations in partially observable environments

Leveraging Reinforcement Learning Techniques for Effective Policy Adoption and Validation

Continual Reinforcement Learning with Diversity Exploration and Adversarial Self-Correction

Scheduled Intrinsic Drive: A Hierarchical Take on Intrinsically Motivated Exploration

Placeto: Learning Generalizable Device Placement Algorithms for Distributed Machine Learning

When Multiple Agents Learn to Schedule: A Distributed Radio Resource Management Framework

Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates

Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning

Gap-Increasing Policy Evaluation for Efficient and Noise-Tolerant Reinforcement Learning

Sample-efficient Adversarial Imitation Learning from Observation

Online Antenna Tuning in Heterogeneous Cellular Networks with Deep Reinforcement Learning

Iterative Model-Based Reinforcement Learning Using Simulations in the Differentiable Neural Computer

Non-asymptotic Analysis of Biased Stochastic Approximation Scheme

Injecting Prior Knowledge for Transfer Learning into Reinforcement Learning Algorithms using Logic Tensor Networks

Modeling and Interpreting Real-world Human Risk Decision Making with Inverse Reinforcement Learning

An Optimization Framework for Task Sequencing in Curriculum Learning

Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound

Sub-Goal Trees -- a Framework for Goal-Directed Trajectory Prediction and Optimization

Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics

Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks

Towards Inverse Reinforcement Learning for Limit Order Book Dynamics

Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning

Continual Reinforcement Learning deployed in Real-life using Policy Distillation and Sim2Real Transfer

Generative Adversarial Imagination for Sample Efficient Deep Reinforcement Learning

Boosting Soft Actor-Critic: Emphasizing Recent Experience without Forgetting the Past

Deep Reinforcement Learning with Discrete Normalized Advantage Functions for Resource Management in Network Slicing

Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning

Dynamic Measurement Scheduling for Event Forecasting using Deep RL

Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion

Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation

Multi-modal Active Learning From Human Data: A Deep Reinforcement Learning Approach

Distribution-dependent and Time-uniform Bounds for Piecewise i.i.d Bandits

MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments

Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models

Improving Exploration in Soft-Actor-Critic with Normalizing Flows Policies

DeepMDP: Learning Continuous Latent Space Models for Representation Learning

Scaling and Benchmarking Self-Supervised Visual Representation Learning

Towards Interpretable Reinforcement Learning Using Attention Augmented Agents

Interactive Teaching Algorithms for Inverse Reinforcement Learning

Beyond Backprop: Online Alternating Minimization with Auxiliary Variables

Machine Learning and System Identification for Estimation in Physical Systems

Probabilistic hypergraph grammars for efficient molecular optimization

Reinforcement Learning with Low-Complexity Liquid State Machines

Posterior Variance Analysis of Gaussian Processes with Application to Average Learning Curves

Autonomous Reinforcement Learning of Multiple Interrelated Tasks

Reinforcement Learning for Dynamic Bidding in Truckload Markets: an Application to Large-Scale Fleet Management with Advance Commitments

Meta Reinforcement Learning with Task Embedding and Shared Policy

Macro Action Reinforcement Learning with Sequence Disentanglement using Variational Autoencoder

Sequential Triggers for Watermarking of Deep Reinforcement Learning Policies

RL-Based Method for Benchmarking the Adversarial Resilience and Robustness of Deep Reinforcement Learning Policies

An Empirical Study on Hyperparameters and their Interdependence for RL Generalization

On the Correctness and Sample Complexity of Inverse Reinforcement Learning

The Principle of Unchanged Optimality in Reinforcement Learning Generalization

Rogue-Gym: A New Challenge for Generalization in Reinforcement Learning

AutoSlim: Towards One-Shot Architecture Search for Channel Numbers

Diversity-Inducing Policy Gradient: Using Maximum Mean Discrepancy to Find a Set of Diverse Policies

Reinforcement Learning Experience Reuse with Policy Residual Representation

Effective Medical Test Suggestions Using Deep Reinforcement Learning

Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology

Attentional Policies for Cross-Context Multi-Agent Reinforcement Learning

Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning

Semantic White Balance: Semantic Color Constancy Using Convolutional Neural Network

MolecularRNN: Generating realistic molecular graphs with optimized properties

Exploring Computational User Models for Agent Policy Summarization

Defining Admissible Rewards for High Confidence Policy Evaluation

Hybrid Actor-Critic Reinforcement Learning in Parameterized Action Space

Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches

Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator

Don't Forget Your Teacher: A Corrective Reinforcement Learning Framework

Reinforcement Learning and Adaptive Sampling for Optimized DNN Compilation

Advantage Amplification in Slowly Evolving Latent-State Environments

On the Generalization Gap in Reparameterizable Reinforcement Learning

An Improved Convergence Analysis of Stochastic Variance-Reduced Policy Gradient

General solutions for nonlinear differential equations: a rule-based self-learning approach using deep reinforcement learning

Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning

Generation of Policy-Level Explanations for Reinforcement Learning

A General Family of Robust Stochastic Operators for Reinforcement Learning

Conditions on Features for Temporal Difference-Like Methods to Converge

Learning Efficient and Effective Exploration Policies with Counterfactual Meta Policy

Fingerprint Policy Optimisation for Robust Reinforcement Learning

Disentangling Dynamics and Returns: Value Function Decomposition with Future Prediction

Learning latent state representation for speeding up exploration

Failure-Scenario Maker for Rule-Based Agent using Multi-agent Adversarial Reinforcement Learning and its Application to Autonomous Driving

RL4health: Crowdsourcing Reinforcement Learning for Knee Replacement Pathway Optimization

Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies

InfoRL: Interpretable Reinforcement Learning using Information Maximization

Metatrace Actor-Critic: Online Step-size Tuning by Meta-gradient Descent for Reinforcement Learning Control

Automatic Machine Learning by Pipeline Synthesis using Model-Based Reinforcement Learning and a Grammar

Deep learning for molecular design - a review of the state of the art

A Learning based Branch and Bound for Maximum Common Subgraph Problems

Issues concerning realizability of Blackwell optimal policies in reinforcement learning

Revisiting the Softmax Bellman Operator: New Benefits and New Perspective

Reinforcement Learning for Learning of Dynamical Systems in Uncertain Environment: a Tutorial

Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning

Stratospheric Aerosol Injection as a Deep Reinforcement Learning Problem

TBQ($σ$): Improving Efficiency of Trace Utilization for Off-Policy Reinforcement Learning

MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning

Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells

Combining Parametric and Nonparametric Models for Off-Policy Evaluation

End-to-End Robotic Reinforcement Learning without Reward Engineering

Exploration-Exploitation Trade-off in Reinforcement Learning on Online Markov Decision Processes with Global Concave Rewards

Reinforcement Learning for Robotics and Control with Active Uncertainty Reduction

Self-Adapting Goals Allow Transfer of Predictive Models to New Tasks

Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment

Successor Options: An Option Discovery Framework for Reinforcement Learning

TauRieL: Targeting Traveling Salesman Problem with a deep reinforcement learning inspired architecture

QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning

Control Regularization for Reduced Variance Reinforcement Learning

Learning and Exploiting Multiple Subgoals for Fast Exploration in Hierarchical Reinforcement Learning

Metareasoning in Modular Software Systems: On-the-Fly Configuration using Reinforcement Learning with Rich Contextual Representations

Multi-Pass Q-Networks for Deep Reinforcement Learning with Parameterised Action Spaces

Autonomous Management of Energy-Harvesting IoT Nodes Using Deep Reinforcement Learning

Design of Artificial Intelligence Agents for Games using Deep Reinforcement Learning

Domain Adversarial Reinforcement Learning for Partial Domain Adaptation

Attention-based Deep Reinforcement Learning for Multi-view Environments

Function Space Particle Optimization for Bayesian Neural Networks

Meta Reinforcement Learning with Distribution of Exploration Parameters Learned by Evolution Strategies

Toybox: A Suite of Environments for Experimental Evaluation of Deep Reinforcement Learning

Object Exchangeability in Reinforcement Learning: Extended Abstract

Action Robust Reinforcement Learning and Applications in Continuous Control

Curious Meta-Controller: Adaptive Alternation between Model-Based and Model-Free Control in Deep Reinforcement Learning

Face Hallucination by Attentive Sequence Optimization with Reinforcement Learning

Arbitrage of Energy Storage in Electricity Markets with Deep Reinforcement Learning

Muscle Excitation Estimation in Biomechanical Simulation Using NAF Reinforcement Learning

Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference

Autonomous Air Traffic Controller: A Deep Multi-Agent Reinforcement Learning Approach

Similarities between policy gradient methods (PGM) in Reinforcement learning (RL) and supervised learning (SL)

Information-Theoretic Considerations in Batch Reinforcement Learning

RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for Real-Time Point Cloud Shape Completion

One-Shot Learning of Multi-Step Tasks from Observation via Activity Localization in Auxiliary Video

Autonomous Driving in Reality with Reinforcement Learning and Image Translation

Ray Interference: a Source of Plateaus in Deep Reinforcement Learning

Learnable Embedding Space for Efficient Neural Architecture Compression

Deep Reinforcement Learning for Optimal Critical Care Pain Management with Morphine using Dueling Double-Deep Q Networks

Towards Combining On-Off-Policy Methods for Real-World Applications

Decomposition Methods with Deep Corrections for Reinforcement Learning

Superquadrics Revisited: Learning 3D Shape Parsing beyond Cuboids

Adaptive Power System Emergency Control using Deep Reinforcement Learning

Mid-Level Visual Representations Improve Generalization and Sample Efficiency for Learning Visuomotor Policies

Safety-Guided Deep Reinforcement Learning via Online Gaussian Process Estimation

On Applications of Bootstrap in Continuous Space Reinforcement Learning

Compression and Localization in Reinforcement Learning for ATARI Games

When Simple Exploration is Sample Efficient: Identifying Sufficient Conditions for Random Exploration to Yield PAC RL Algorithms

Decoupled Data Based Approach for Learning to Control Nonlinear Dynamical Systems

Making History Matter: History-Advantage Sequence Training for Visual Dialog

Simion Zoo: A Workbench for Distributed Experimentation with Reinforcement Learning for Continuous Control Tasks

Saliency Prediction on Omnidirectional Images with Generative Adversarial Imitation Learning

Empirical Evaluation of Contextual Policy Search with a Comparison-based Surrogate Model and Active Covariance Matrix Adaptation

Let's Play Again: Variability of Deep Reinforcement Learning Agents in Atari Environments

Effective Scheduling Function Design in SDN through Deep Reinforcement Learning

ReinBo: Machine Learning pipeline search and configuration with Bayesian Optimization embedded Reinforcement Learning

Embryo staging with weakly-supervised region selection and dynamically-decoded predictions

Pre-training Neural Networks with Human Demonstrations for Deep Reinforcement Learning

Reinforcement Learning with Attention that Works: A Self-Supervised Approach

InfoBot: Transfer and Exploration via the Information Bottleneck

Jointly Pre-training with Supervised, Autoencoder, and Value Losses for Deep Reinforcement Learning

PaintBot: A Reinforcement Learning Approach for Natural Media Painting

Deep Reinforcement Learning on a Budget: 3D Control and Reasoning Without a Supercomputer

Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset

Finding and Visualizing Weaknesses of Deep Reinforcement Learning Agents

How to pick the domain randomization parameters for sim-to-real transfer of reinforcement learning policies?

Autoregressive Policies for Continuous Control Deep Reinforcement Learning

Teaching Inverse Reinforcement Learners via Features and Demonstrations

Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-Learning

Learning Where to See: A Novel Attention Model for Automated Immunohistochemical Scoring

On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning

CLIC: Curriculum Learning and Imitation for object Control in non-rewarding environments

Looking Fast and Slow: Memory-Guided Mobile Video Object Detection

Information-Directed Exploration for Deep Reinforcement Learning

Temporal Logic Guided Safe Reinforcement Learning Using Control Barrier Functions

Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator

Deep Hierarchical Reinforcement Learning Based Recommendations via Multi-goals Abstraction

DQN with model-based exploration: efficient learning on environments with sparse rewards

Distributed off-Policy Actor-Critic Reinforcement Learning with Policy Consensus

Towards automatic construction of multi-network models for heterogeneous multi-task learning

End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks

Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables

A Comparison of Prediction Algorithms and Nexting for Short Term Weather Forecasts

Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future

A Review of Reinforcement Learning for Autonomous Building Energy Management

Policy Distillation and Value Matching in Multiagent Reinforcement Learning

Reinforcement Learning and Inverse Reinforcement Learning with System 1 and System 2

Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces

Deep Reinforcement Learning of Volume-guided Progressive View Inpainting for 3D Point Scene Completion from a Single Depth Image

Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control

Accelerating Minibatch Stochastic Gradient Descent using Typicality Sampling

Scene Memory Transformer for Embodied Agents in Long-Horizon Tasks

Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning

Towards Understanding Chinese Checkers with Heuristics, Monte Carlo Tree Search, and Deep Reinforcement Learning

RLOC: Neurobiologically Inspired Hierarchical Reinforcement Learning Algorithm for Continuous Control of Nonlinear Dynamical Systems

Hierarchical Reinforcement Learning via Advantage-Weighted Information Maximization

Recurrent 3D Attentional Networks for End-to-End Active Object Recognition

Asynchronous Episodic Deep Deterministic Policy Gradient: Towards Continuous Control in Computationally Complex Environments

How to Organize your Deep Reinforcement Learning Agents: The Importance of Communication Topology

Automating Predictive Modeling Process using Reinforcement Learning

OmniDRL: Robust Pedestrian Detection using Deep Reinforcement Learning on Omnidirectional Cameras

Straight to the point: reinforcement learning for user guidance in ultrasound

Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning

RLgraph: Modular Computation Graphs for Deep Reinforcement Learning

Catalyst.RL: A Distributed Framework for Reproducible RL Research

Learning First-to-Spike Policies for Neuromorphic Control Using Policy Gradients

Learning to Adapt in Dynamic, Real-World Environments Through Meta-Reinforcement Learning

Distributed Edge Caching via Reinforcement Learning in Fog Radio Access Networks

Variance Reduction for Reinforcement Learning in Input-Driven Environments

Deep Reinforcement Learning Based High-level Driving Behavior Decision-making Model in Heterogeneous Traffic

Joint Modeling of Dense and Incomplete Trajectories for Citywide Traffic Volume Inference

Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation

Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning

Adversarial Imitation via Variational Inverse Reinforcement Learning

Effective 3D Humerus and Scapula Extraction using Low-contrast and High-shape-variability MR Data

A Comparative Analysis of Expected and Distributional Reinforcement Learning

Investigating Generalisation in Continuous Deep Reinforcement Learning

Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs

Simultaneously Learning Vision and Feature-based Control Policies for Real-world Ball-in-a-Cup

Message-Dropout: An Efficient Training Method for Multi-Agent Deep Reinforcement Learning

Variance Networks: When Expectation Does Not Meet Your Expectations

Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams

Unsupervised Basis Function Adaptation for Reinforcement Learning

Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications

Hyperbolic Embeddings for Learning Options in Hierarchical Reinforcement Learning

Robust Reinforcement Learning in POMDPs with Incomplete and Noisy Observations

Policy Optimization With Penalized Point Probability Distance: An Alternative To Proximal Policy Optimization

Long and Short Memory Balancing in Visual Co-Tracking using Q-Learning

Off-Policy Actor-Critic in an Ensemble: Achieving Maximum General Entropy and Effective Environment Exploration in Deep Reinforcement Learning

Curriculum goal masking for continuous deep reinforcement learning

Sample Complexity of Estimating the Policy Gradient for Nearly Deterministic Dynamical Systems

Improving Image Captioning with Conditional Generative Adversarial Nets

End-to-end Active Object Tracking and Its Real-world Deployment via Reinforcement Learning

Deep Reinforcement Learning from Policy-Dependent Human Feedback

Performance Dynamics and Termination Errors in Reinforcement Learning: A Unifying Perspective

WiseMove: A Framework for Safe Deep Reinforcement Learning for Autonomous Driving

CEM-RL: Combining evolutionary and gradient-based methods for policy search

Latent Space Reinforcement Learning for Steering Angle Prediction

Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous Flight

A Bandit Framework for Optimal Selection of Reinforcement Learning Agents

Distributional reinforcement learning with linear function approximation

Rethinking the Discount Factor in Reinforcement Learning: A Decision Theoretic Approach

Understanding Multi-Step Deep Reinforcement Learning: A Systematic Study of the DQN Target

Metaoptimization on a Distributed System for Deep Reinforcement Learning

Learning to detect chest radiographs containing lung nodules using visual attention networks

Tsallis Reinforcement Learning: A Unified Framework for Maximum Entropy Reinforcement Learning

On overfitting and asymptotic bias in batch reinforcement learning with partial observability

Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications

Total stochastic gradient algorithms and applications in reinforcement learning

PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos

The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint

A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning

Learning from Longitudinal Face Demonstration - Where Tractable Deep Modeling Meets Inverse Reinforcement Learning

Learning User Preferences via Reinforcement Learning with Spatial Interface Valuing

Formulation of Deep Reinforcement Learning Architecture Toward Autonomous Driving for On-Ramp Merge

Visual Rationalizations in Deep Reinforcement Learning for Atari Games

Motion Perception in Reinforcement Learning with Dynamic Objects

Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective

Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement

Learning Actionable Representations with Goal-Conditioned Policies

Recall Traces: Backtracking Models for Efficient Reinforcement Learning

Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL

Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift

Modularization of End-to-End Learning: Case Study in Arcade Games

Model-based Deep Reinforcement Learning for Dynamic Portfolio Optimization

Towards Physically Safe Reinforcement Learning under Supervision

Regret Bounds for Reinforcement Learning via Markov Chain Concentration

Natively Interpretable Machine Learning and Artificial Intelligence: Preliminary Results and Future Directions

Hierarchically Structured Reinforcement Learning for Topically Coherent Visual Story Generation

Amplifying the Imitation Effect for Reinforcement Learning of UCAV's Mission Execution

Representation Learning on Graphs: A Reinforcement Learning Application

CodeX: Bit-Flexible Encoding for Streaming-based FPGA Acceleration of DNNs

Exploring applications of deep reinforcement learning for real-world autonomous driving systems

AMC: AutoML for Model Compression and Acceleration on Mobile Devices

Learning State Representations in Complex Systems with Multimodal Data

Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning

On the Global Convergence of Imitation Learning: A Case for Linear Quadratic Regulator

Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization

Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement Learning

Backprop-Q: Generalized Backpropagation for Stochastic Computation Graphs

What Should I Do Now? Marrying Reinforcement Learning and Symbolic Planning

Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior

Optimal Decision-Making in Mixed-Agent Partially Observable Stochastic Environments via Reinforcement Learning

Floyd-Warshall Reinforcement Learning: Learning from Past Experiences to Reach New Goals

Accelerating Goal-Directed Reinforcement Learning by Model Characterization

Self-supervised Learning of Image Embedding for Continuous Control

Imminent Collision Mitigation with Reinforcement Learning and Vision

Human-Like Autonomous Car-Following Model with Deep Reinforcement Learning

End-to-End Video Captioning with Multitask Reinforcement Learning

Partial Policy-based Reinforcement Learning for Anatomical Landmark Localization in 3D Medical Images

Reinforced Temporal Attention and Split-Rate Transfer for Depth-Based Person Re-Identification

A New Concept of Deep Reinforcement Learning based Augmented General Sequence Tagging System

Learning to Coordinate Multiple Reinforcement Learning Agents for Diverse Query Reformulation

VMAV-C: A Deep Attention-based Reinforcement Learning Algorithm for Model-based Control

NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning

Parallelized Interactive Machine Learning on Autonomous Vehicles

Estimating Rationally Inattentive Utility Functions with Deep Clustering for Framing - Applications in YouTube Engagement Dynamics

ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation

Pre-training with Non-expert Human Demonstration for Deep Reinforcement Learning

Fuzzy Controller of Reward of Reinforcement Learning For Handwritten Digit Recognition

Decentralized Computation Offloading for Multi-User Mobile Edge Computing: A Deep Reinforcement Learning Approach

Scalable Coordinated Exploration in Concurrent Reinforcement Learning

Measuring and Characterizing Generalization in Deep Reinforcement Learning

Continual State Representation Learning for Reinforcement Learning using Generative Replay

Efficient Model-Free Reinforcement Learning Using Gaussian Process

KF-LAX: Kronecker-factored curvature estimation for control variate optimization in reinforcement learning

Zero-shot Deep Reinforcement Learning Driving Policy Transfer for Autonomous Vehicles based on Robust Control

Ranked Reward: Enabling Self-Play Reinforcement Learning for Combinatorial Optimization

The effects of negative adaptation in Model-Agnostic Meta-Learning

Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures

Deep Reinforcement Learning for Intelligent Transportation Systems

FoldingZero: Protein Folding from Scratch in Hydrophobic-Polar Model

Multi-agent Deep Reinforcement Learning with Extremely Noisy Observations

Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning

Towards Solving Text-based Games by Producing Adaptive Action Spaces

A Reinforcement Learning Approach to Target Tracking in a Camera Network

MONAS: Multi-Objective Neural Architecture Search using Reinforcement Learning

Disentangled Variational Auto-Encoder for Semi-supervised Learning

Practical Deep Reinforcement Learning Approach for Stock Trading

Dynamic Measurement Scheduling for Adverse Event Forecasting using Deep RL

Using Monte Carlo Tree Search as a Demonstrator within Asynchronous Deep RL

Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling

Flow Shape Design for Microfluidic Devices Using Deep Reinforcement Learning

Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation

Definition and evaluation of model-free coordination of electrical vehicle charging with reinforcement learning

A Structure-aware Online Learning Algorithm for Markov Decision Processes

Answerer in Questioner's Mind: Information Theoretic Approach to Goal-Oriented Visual Dialog

QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation

Unsupervised Control Through Non-Parametric Discriminative Rewards

Scaling Configuration of Energy Harvesting Sensors with Reinforcement Learning

Quality-Aware Multimodal Saliency Detection via Deep Reinforcement Learning

A Model-Based Reinforcement Learning Approach for a Rare Disease Diagnostic Task

Planning in Dynamic Environments with Conditional Autoregressive Models

Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation

TorchProteinLibrary: A computationally efficient, differentiable representation of protein structure

Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning

Integrating Reinforcement Learning to Self Training for Pulmonary Nodule Segmentation in Chest X-rays

High-Level Strategy Selection under Partial Observability in StarCraft: Brood War

Model-Based Regularization for Deep Reinforcement Learning with Transcoder Networks

Representation Learning of Pedestrian Trajectories Using Actor-Critic Sequence-to-Sequence Autoencoder

The Mirage of Action-Dependent Baselines in Reinforcement Learning

Scalable agent alignment via reward modeling: a research direction

Learning to infer: RL-based search for DNN primitive selection on Heterogeneous Embedded Systems

Parameter Sharing Reinforcement Learning Architecture for Multi Agent Driving Behaviors

The Utility of Sparse Representations for Control in Reinforcement Learning

Reward learning from human preferences and demonstrations in Atari

Reward-estimation variance elimination in sequential decision processes

Concept Learning through Deep Reinforcement Learning with Memory-Augmented Neural Networks

Large-scale Interactive Recommendation with Tree-structured Policy Gradient

Emergence of Addictive Behaviors in Reinforcement Learning Agents

Fully Convolutional Network with Multi-Step Reinforcement Learning for Image Processing

Modelling the Dynamic Joint Policy of Teammates with Attention Multi-agent DDPG

Coordinating Disaster Emergency Response with Heuristic Reinforcement Learning

Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition

Learning data augmentation policies using augmented random search

Towards Governing Agent's Efficacy: Action-Conditional $β$-VAE for Deep Transparent Reinforcement Learning

Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining

Sample-Efficient Policy Learning based on Completely Behavior Cloning

Correlation Filter Selection for Visual Tracking Using Reinforcement Learning

Reward Estimation for Variance Reduction in Deep Reinforcement Learning

QUOTA: The Quantile Option Architecture for Reinforcement Learning

ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search

A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation

Reinforcement Learning based Dynamic Model Selection for Short-Term Load Forecasting

You Only Search Once: Single Shot Neural Architecture Search via Direct Sparse Optimization

Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models

Dantzig Selector with an Approximately Optimal Denoising Matrix and its Application to Reinforcement Learning

Automated Theorem Proving in Intuitionistic Propositional Logic by Deep Reinforcement Learning

Learning a Generative Model for Validity in Complex Discrete Structures

Towards a Simple Approach to Multi-step Model-based Reinforcement Learning

TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow

ANS: Adaptive Network Scaling for Deep Rectifier Reinforcement Learning Models

Reinforcement Learning and Deep Learning based Lateral Control for Autonomous Driving

A Reinforcement Learning Hyper-Heuristic in Multi-Objective Single Point Search with Application to Structural Fault Identification

Virtual-to-Real: Learning to Control in Visual Semantic Segmentation

Distributive Dynamic Spectrum Access through Deep Reinforcement Learning: A Reservoir Computing Based Approach

Differential Variable Speed Limits Control for Freeway Recurrent Bottlenecks via Deep Reinforcement learning

Regret Minimization for Partially Observable Deep Reinforcement Learning

Meta-modeling game for deriving theoretical-consistent, micro-structural-based traction-separation laws via deep reinforcement learning

The Faults in Our Pi Stars: Security Issues and Open Challenges in Deep Reinforcement Learning

Hierarchical Approaches for Reinforcement Learning in Parameterized Action Space

High-Dimensional Continuous Control Using Generalized Advantage Estimation

Transfer Learning versus Multi-agent Learning regarding Distributed Decision-Making in Highway Traffic

Fast deep reinforcement learning using online adjustments from the past

Using Deep Reinforcement Learning for the Continuous Control of Robotic Arms

Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning

Sequential Learning of Movement Prediction in Dynamic Environments using LSTM Autoencoder

Optimal Hierarchical Learning Path Design with Reinforcement Learning

Empowerment-driven Exploration using Mutual Information Estimation

The Laplacian in RL: Learning Representations with Efficient Approximations

S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning

Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space

Investigating Enactive Learning for Autonomous Intelligent Agents

Personalized Dynamics Models for Adaptive Assistive Navigation Systems

On the function approximation error for risk-sensitive reinforcement learning

Model-Free Linear Quadratic Control via Reduction to Expert Prediction

Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods

Comparison of Reinforcement Learning algorithms applied to the Cart Pole problem

Deep Reinforcement Learning for Time Scheduling in RF-Powered Backscatter Cognitive Radio Networks

The Dreaming Variational Autoencoder for Reinforcement Learning Environments

Bayesian Transfer Reinforcement Learning with Prior Knowledge Rules

Interactive Learning with Corrective Feedback for Policies based on Deep Neural Networks

Using State Predictions for Value Regularization in Curiosity Driven Deep Reinforcement Learning

Switching Isotropic and Directional Exploration with Parameter Space Noise in Deep Reinforcement Learning

Visual Diagnostics for Deep Reinforcement Learning Policy Development

Low Precision Policy Distillation with Application to Low-Power, Real-time Sensation-Cognition-Action Loop with Neuromorphic Computing

Better Safe than Sorry: Evidence Accumulation Allows for Safe Reinforcement Learning

EpiRL: A Reinforcement Learning Agent to Facilitate Epistasis Detection

Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration

Accuracy-based Curriculum Learning in Deep Reinforcement Learning

Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting

Benchmarking Reinforcement Learning Algorithms on Real-World Robots

GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms

Multiple-Step Greedy Policies in Online and Approximate Reinforcement Learning

Prosocial or Selfish? Agents with different behaviors for Contract Negotiation using Reinforcement Learning

From Game-theoretic Multi-agent Log Linear Learning to Reinforcement Learning

Generalizing Across Multi-Objective Reward Functions in Deep Reinforcement Learning

Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics

Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation

Transparency and Explanation in Deep Reinforcement Learning Neural Networks

Adversarial Reinforcement Learning for Observer Design in Autonomous Systems under Cyber Attacks

Deep PDF: Probabilistic Surface Optimization and Density Estimation

VPE: Variational Policy Embedding for Transfer Reinforcement Learning

Online Cyber-Attack Detection in Smart Grid: A Reinforcement Learning Approach

Sequential Coordination of Deep Models for Learning Visual Arithmetic

Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising

Adaptive Behavior Generation for Autonomous Driving using Deep Reinforcement Learning with Compact Semantic States

Flatland: a Lightweight First-Person 2-D Environment for Reinforcement Learning

Probabilistic Prediction of Interactive Driving Behavior via Hierarchical Inverse Reinforcement Learning

Improving On-policy Learning with Statistical Reward Accumulation

ARCHER: Aggressive Rewards to Counter bias in Hindsight Experience Replay

Two geometric input transformation methods for fast online reinforcement learning with neural nets

Challenges of Context and Time in Reinforcement Learning: Introducing Space Fortress as a Benchmark

A Robotic Auto-Focus System based on Deep Reinforcement Learning

Effective Exploration for Deep Reinforcement Learning via Bootstrapped Q-Ensembles under Tsallis Entropy Regularization

Transferring Deep Reinforcement Learning with Adversarial Objective and Augmentation

Video Summarisation by Classification with Deep Reinforcement Learning

Visual Transfer between Atari Games using Competitive Reinforcement Learning

APES: a Python toolbox for simulating reinforcement learning environments

Application of Self-Play Reinforcement Learning to a Four-Player Game of Imperfect Information

A Study of Reinforcement Learning for Neural Machine Translation

NavigationNet: A Large-scale Interactive Indoor Navigation Dataset

How Local is the Local Diversity? Reinforcing Sequential Determinantal Point Processes with Dynamic Ground Sets for Supervised Video Summarization

LIFT: Reinforcement Learning in Computer Systems by Learning From Demonstrations

Feature-Based Aggregation and Deep Reinforcement Learning: A Survey and Some New Implementations

Importance mixing: Improving sample reuse in evolutionary policy search methods

Learning Robust Rewards with Adversarial Inverse Reinforcement Learning

Visual Sensor Network Reconfiguration with Deep Reinforcement Learning

Directed Policy Gradient for Safe Reinforcement Learning with Human Advice

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Bayesian bandits: balancing the exploration-exploitation tradeoff via double sampling

Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN

Personalized Exposure Control Using Adaptive Metering and Reinforcement Learning

Automating Vehicles by Deep Reinforcement Learning using Task Separation with Hill Climbing

Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam

A Hierarchical Bayesian Linear Regression Model with Local Features for Stochastic Dynamics Approximation

Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors

Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning

Reinforcement Learning To Adapt Speech Enhancement to Instantaneous Input Signal Quality

Look Before You Leap: Bridging Model-Free and Model-Based Reinforcement Learning for Planned-Ahead Vision-and-Language Navigation

Object-oriented Neural Programming (OONP) for Document Understanding

Discrete linear-complexity reinforcement learning in continuous action spaces for Q-learning algorithms

Contrastive Explanations for Reinforcement Learning in terms of Expected Consequences

NAVREN-RL: Learning to fly in real environment via end-to-end deep reinforcement learning using monocular images

Automatically Designing CNN Architectures for Medical Image Segmentation

Self-Organizing Maps as a Storage and Transfer Mechanism in Reinforcement Learning

Generative Temporal Models with Spatial Memory for Partially Observed Environments

Online Robust Policy Learning in the Presence of Unknown Adversaries

Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees

Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation

A Constrained Randomized Shortest-Paths Framework for Optimal Exploration

Will it Blend? Composing Value Functions in Reinforcement Learning

CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving

Auto Deep Compression by Reinforcement Learning Based Actor-Critic Structure

Equivalence Between Wasserstein and Value-Aware Loss for Model-based Reinforcement Learning

Deep Reinforcement Learning Attention Selection for Person Re-Identification

Meta Reinforcement Learning with Latent Variable Gaussian Processes

Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning

Arcades: A deep model for adaptive decision making in voice controlled smart-home

Deep Reinforcement Learning for Doom using Unsupervised Auxiliary Tasks

Beyond Winning and Losing: Modeling Human Motivations and Behaviors Using Inverse Reinforcement Learning

How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments

Per-decision Multi-step Temporal Difference Learning with Control Variates

Towards Mixed Optimization for Reinforcement Learning with Program Synthesis

Human-level performance in first-person multiplayer games with population-based deep reinforcement learning

Progress & Compress: A scalable framework for continual learning

Bayesian Inference with Anchored Ensembles of Neural Networks, and Application to Exploration in Reinforcement Learning

Speeding up the Metabolism in E-commerce by Reinforcement Mechanism Design

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations

A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning

Deep Reinforcement Learning for Surgical Gesture Segmentation and Classification

Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation

Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning

An Online Prediction Algorithm for Reinforcement Learning with Linear Function Approximation using Cross Entropy Method

Implicit Quantile Networks for Distributional Reinforcement Learning

Deep Reinforcement Learning for Dynamic Urban Transportation Problems

Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control

Meta-Learning Transferable Active Learning Policies by Deep Reinforcement Learning

Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation

Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents

Fidelity-based Probabilistic Q-learning for Control of Quantum Systems

Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings

Path-Level Network Transformation for Efficient Architecture Search

QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

ScreenerNet: Learning Self-Paced Curriculum for Deep Neural Networks

Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations

PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust Decision-Making

SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation

Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning

Mitigation of Policy Manipulation Attacks on Deep Q-Networks with Parameter-Space Noise

Relational inductive bias for physical construction in humans and machines

TD or not TD: Analyzing the Role of Temporal Differencing in Deep Reinforcement Learning

Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling

Efficient Entropy for Policy Gradient with Multidimensional Action Space

Integrating Episodic Memory into a Reinforcement Learning Agent using Reservoir Sampling

A Reinforcement Learning Approach to Age of Information in Multi-User Networks

Evaluating Reinforcement Learning Algorithms in Observational Health Settings

Observe and Look Further: Achieving Consistent Performance on Atari

Truncated Horizon Policy Search: Combining Reinforcement Learning & Imitation Learning

Importance Weighted Transfer of Samples in Reinforcement Learning

Learning to Play General Video-Games via an Object Embedding Network

A Sliding-Window Algorithm for Markov Decision Processes with Arbitrarily Changing Rewards and Transitions

Finite Sample Analysis of LSTD with Random Projections and Eligibility Traces

Myopic Bayesian Design of Experiments via Posterior Sampling and Probabilistic Programming

Reinforcement Learning to Rank in E-Commerce Search Engine: Formalization, Analysis, and Application

Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis

Learning to Optimize via Wasserstein Deep Inverse Optimal Control

Scalable Centralized Deep Multi-Agent Reinforcement Learning via Policy Gradients

Disentangling Controllable and Uncontrollable Factors of Variation by Interacting with the World

A Framework and Method for Online Inverse Reinforcement Learning

Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review

Unsupervised Video Object Segmentation for Deep Reinforcement Learning

Self-supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation

Optimized Computation Offloading Performance in Virtual Edge Computing Systems via Deep Reinforcement Learning

Low-pass Recurrent Neural Networks - A memory architecture for longer-term correlation discovery

Approximate Temporal Difference Learning is a Gradient Descent for Reversible Policies

Multi-modality Sensor Data Classification with Selective Attention

Hashing over Predicted Future Frames for Informed Exploration of Deep Reinforcement Learning

Learning Deep Mean Field Games for Modeling Large Population Behavior

MQGrad: Reinforcement Learning of Gradient Quantization in Parameter Server

Modeling and Simultaneously Removing Bias via Adversarial Neural Networks

Distort-and-Recover: Color Enhancement using Deep Reinforcement Learning

CytonRL: an Efficient Reinforcement Learning Open-source Toolkit Implemented in C++

Taking gradients through experiments: LSTMs and memory proximal policy optimization for black-box quantum control

DORA The Explorer: Directed Outreaching Reinforcement Action-Selection

Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning

Building Generalizable Agents with a Realistic and Rich 3D Environment

Hierarchical Modular Reinforcement Learning Method and Knowledge Acquisition of State-Action Rule for Multi-target Problem

A Benchmarking Environment for Reinforcement Learning Based Task Oriented Dialogue Management

Synthesizing Programs for Images using Reinforced Adversarial Learning

Renewal Monte Carlo: Renewal theory based reinforcement learning

Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches

Learning Structural Weight Uncertainty for Sequential Decision-Making

Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments

Deep Reinforcement Learning for Traffic Light Control in Vehicular Networks

Dynamic Zoom-in Network for Fast Object Detection in Large Images

Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++

Accelerating Learning in Constructive Predictive Frameworks with the Successor Representation

Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines

Setting up a Reinforcement Learning Task with a Real-World Robot

Simple random search provides a competitive approach to reinforcement learning

Inverse Visual Question Answering: A New Benchmark and VQA Diagnosis Tool

Combating Reinforcement Learning's Sisyphean Curse with Intrinsic Fear

Hierarchical Reinforcement Learning: Approximating Optimal Discounted TSP Using Local Policies

A2-RL: Aesthetics Aware Reinforcement Learning for Image Cropping

Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research

The Advantage of Doubling: A Deep Reinforcement Learning Approach to Studying the Double Team in the NBA

Towards Synthesizing Complex Programs from Input-Output Examples

Comparing Deep Reinforcement Learning and Evolutionary Methods in Continuous Control

Variance-Aware Regret Bounds for Undiscounted Reinforcement Learning in MDPs

Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-offs by Selective Execution

Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning

Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents

Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling

Overcoming Exploration in Reinforcement Learning with Demonstrations

Backpropagation through the Void: Optimizing control variates for black-box gradient estimation

Action-depedent Control Variates for Policy Optimization via Stein's Identity

An Analysis of Categorical Distributional Reinforcement Learning

Meta-Reinforcement Learning of Structured Exploration Strategies

Improving Mild Cognitive Impairment Prediction via Reinforcement Learning and Dialogue Simulation

Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward

Progressive Reinforcement Learning with Distillation for Multi-Skilled Motion Control

Precision medicine as a control problem: Using simulation and deep reinforcement learning to discover adaptive, personalized multi-cytokine therapy for sepsis

Learning and Querying Fast Generative Models for Reinforcement Learning

Improving the Universality and Learnability of Neural Programmer-Interpreters with Combinator Abstraction

SCH-GAN: Semi-supervised Cross-modal Hashing by Generative Adversarial Network

Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models

Multimodal Sentiment Analysis with Word-Level Fusion and Reinforcement Learning

GitGraph - Architecture Search Space Creation through Frequent Computational Subgraph Mining

Sample-Efficient Reinforcement Learning through Transfer and Architectural Priors

Applications of Deep Learning and Reinforcement Learning to Biological Data

Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning

Generalization Tower Network: A Novel Deep Neural Network Architecture for Multi-Task Learning

Routing Networks: Adaptive Selection of Non-linear Functions for Multi-Task Learning

Accelerated Method for Stochastic Composition Optimization with Nonsmooth Regularization

A short variational proof of equivalence between policy gradients and soft Q learning

Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator

Learning to Look Around: Intelligently Exploring Unseen Environments for Unknown Tasks

Recurrent Attentional Reinforcement Learning for Multi-label Image Recognition

On Wasserstein Reinforcement Learning and the Fokker-Planck equation

N2N Learning: Network to Network Compression via Policy Gradient Reinforcement Learning

DANCin SEQ2SEQ: Fooling Text Classifiers with Adversarial Text Example Generation

Multi-focus Attention Network for Efficient Deep Reinforcement Learning

MINOS: Multimodal Indoor Simulator for Navigation in Complex Environments

Deep Primal-Dual Reinforcement Learning: Accelerating Actor-Critic using Bellman Duality

Representation and Reinforcement Learning for Personalized Glycemic Control in Septic Patients

MAgent: A Many-Agent Reinforcement Learning Platform for Artificial Collective Intelligence

Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning

Uncertainty Estimates for Efficient Neural Network-based Dialogue Policy Optimisation

Hierarchical Policy Search via Return-Weighted Density Estimation

Transferring Autonomous Driving Knowledge on Simulated and Real Intersections

Safe Exploration for Identifying Linear Systems via Robust Optimization

Plan, Attend, Generate: Planning for Sequence-to-Sequence Models

Malaria Likelihood Prediction By Effectively Surveying Households Using Deep Reinforcement Learning

OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning

BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems

Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning

Asking the Difficult Questions: Goal-Oriented Visual Question Generation via Intermediate Rewards

Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning

Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning

Saliency-based Sequential Image Attention with Multiset Prediction

Safe Model-based Reinforcement Learning with Stability Guarantees

Variance Reduced methods for Non-convex Composition Optimization

Uncertainty Decomposition in Bayesian Neural Networks with Latent Variables

Deep Reinforcement Learning with Surrogate Agent-Environment Interface

Learning to Mix n-Step Returns: Generalizing lambda-Returns for Deep Reinforcement Learning

Analysis of Agent Expertise in Ms. Pac-Man using Value-of-Information-based Policies

Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning

Unifying Value Iteration, Advantage Learning, and Dynamic Policy Programming

Exploiting generalization in the subspaces for faster model-based learning

Primal-Dual $π$ Learning: Sample Complexity and Sublinear Run Time for Ergodic Markov Decision Problems

Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control

Estimating Dynamic Treatment Regimes in Mobile Health Using V-learning

Sparse Markov Decision Processes with Causal Sparse Tsallis Entropy Regularization for Reinforcement Learning

Gaussian Processes for Data-Efficient Learning in Robotics and Control

Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight

The detour problem in a stochastic environment: Tolman revisited

Predictive-State Decoders: Encoding the Future into Recurrent Networks

Why Pay More When You Can Pay Less: A Joint Learning Framework for Active Feature Acquisition and Classification

Learning Unknown Markov Decision Processes: A Thompson Sampling Approach

Learning Policies for Adaptive Tracking with Deep Feature Cascades

Linear Stochastic Approximation: Constant Step-Size and Iterate Averaging

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Approximating meta-heuristics with homotopic recurrent neural networks

LADDER: A Human-Level Bidding Agent for Large-Scale Real-Time Online Auctions

ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity?

SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient

Cohesion-based Online Actor-Critic Reinforcement Learning for mHealth Intervention

A Function Approximation Method for Model-based High-Dimensional Inverse Reinforcement Learning

Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation

Group-driven Reinforcement Learning for Personalized mHealth Intervention

Inverse Reinforcement Learning in Large State Spaces via Function Approximation

Towards Diverse and Natural Image Descriptions via a Conditional GAN

Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control

Attention-Aware Face Hallucination via Deep Reinforcement Learning

Learning Multimodal Transition Dynamics for Model-Based Reinforcement Learning

GPLAC: Generalizing Vision-Based Robotic Skills using Weakly Labeled Images

First-Person Activity Forecasting with Online Inverse Reinforcement Learning

Query-guided Regression Network with Context Policy for Phrase Grounding

Reinforcement learning techniques for Outer Loop Link Adaptation in 4G/5G systems

Variational Generative Stochastic Networks with Collaborative Shaping

Batch Reinforcement Learning on the Industrial Benchmark: First Experiences

3DCNN-DQN-RNN: A Deep Reinforcement Learning Framework for Semantic Parsing of Large-scale 3D Point Clouds

On-line Building Energy Optimization using Deep Reinforcement Learning

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

Empirical evaluation of a Q-Learning Algorithm for Model-free Autonomous Soaring

Tracking as Online Decision-Making: Learning a Policy from Streaming Videos with Reinforcement Learning

Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability

Deep Q-Networks for Accelerating the Training of Deep Neural Networks

Learning Visual Servoing with Deep Features and Fitted Q-Iteration

Learning to Learn: Meta-Critic Networks for Sample Efficient Learning

A Self-Adaptive Proposal Model for Temporal Action Detection based on Reinforcement Learning

Statistical Mechanics of Node-perturbation Learning with Noisy Baseline

Dex: Incremental Learning for Complex Environments in Deep Reinforcement Learning

A Laplacian Framework for Option Discovery in Reinforcement Learning

On Optimistic versus Randomized Exploration in Reinforcement Learning

Why is Posterior Sampling Better than Optimism for Reinforcement Learning?

Symmetry Learning for Function Approximation in Reinforcement Learning

Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning

Non-Markovian Control with Gated End-to-End Memory Policy Networks

Sequential Dynamic Decision Making with Deep Neural Nets on a Test-Time Budget

Free energy-based reinforcement learning using a quantum processor

An Attention-Driven Approach of No-Reference Image Quality Assessment

Traffic Light Control Using Deep Policy-Gradient and Value-Function Based Reinforcement Learning

EX2: Exploration with Exemplar Models for Deep Reinforcement Learning

Multi-task learning with deep model based reinforcement learning

Continuous State-Space Models for Optimal Sepsis Treatment - a Deep Reinforcement Learning Approach

Effective Warm Start for the Online Actor-Critic Reinforcement Learning based mHealth Intervention

Learning to Factor Policies and Action-Value Functions: Factored Action Space Representations for Deep Reinforcement learning

Cryptocurrency Portfolio Management with Deep Reinforcement Learning

Deep Episodic Value Iteration for Model-based Meta-Reinforcement Learning

Beating the World's Best at Super Smash Bros. with Deep Reinforcement Learning

Analyzing Knowledge Transfer in Deep Q-Networks for Autonomously Handling Multiple Intersections

Learning Control for Air Hockey Striking using Deep Reinforcement Learning

PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning

Data-efficient Deep Reinforcement Learning for Dexterous Manipulation

Deep Reinforcement Learning for Visual Object Tracking in Videos

Designing Neural Network Architectures using Reinforcement Learning

Fully Convolutional Attention Networks for Fine-Grained Recognition

Learning Dexterous Manipulation for a Soft Robotic Hand from Human Demonstration

Online Learning for Offloading and Autoscaling in Energy Harvesting Mobile Edge Computing

Improving Policy Gradient by Exploring Under-appreciated Rewards

Loss is its own Reward: Self-Supervision for Reinforcement Learning

Deep Variation-structured Reinforcement Learning for Visual Relationship and Attribute Detection

Tree-Structured Reinforcement Learning for Sequential Object Localization

Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks

Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning

EPOpt: Learning Robust Neural Network Policies Using Model Ensembles

Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction

Reinforcement Learning through Asynchronous Advantage Actor-Critic on a GPU

Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic

Changing Model Behavior at Test-Time Using Reinforcement Learning

Learning to predict where to look in interactive environments using deep recurrent q-learning

Collaborative Deep Reinforcement Learning for Joint Object Search

Uncertainty-Aware Reinforcement Learning for Collision Avoidance

FPGA Architecture for Deep Learning and its application to Planetary Robotics

Learning what to look in chest X-rays with a recurrent visual attention model

Connecting Generative Adversarial Networks and Actor-Critic Methods

Vulnerability of Deep Reinforcement Learning to Policy Induction Attacks

A Threshold-based Scheme for Reinforcement Learning in Neural Networks

Real-Time Bidding by Reinforcement Learning in Display Advertising

Reinforcement Learning via Recurrent Convolutional Neural Networks

Towards deep learning with spiking neurons in energy based models with contrastive Hebbian plasticity

Stochastic Primal-Dual Methods and Sample Complexity of Reinforcement Learning

Success Probability of Exploration: a Concrete Analysis of Learning Efficiency

Contextual Decision Processes with Low Bellman Rank are PAC-Learnable

Training an Interactive Humanoid Robot Using Multimodal Deep Reinforcement Learning

Learning in Quantum Control: High-Dimensional Global Optimization for Noisy Quantum Dynamics

A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models

Multiscale Inverse Reinforcement Learning using Diffusion Wavelets

Recurrent Attention Models for Depth-Based Person Identification

Safe Exploration in Finite Markov Decision Processes with Gaussian Processes

Reinforcement Learning Approach for Parallelization in Filters Aggregation Based Feature Selection Algorithms

Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening

Using a Deep Reinforcement Learning Agent for Traffic Signal Control

Learning Locomotion Skills Using DeepRL: Does the Choice of Action Space Matter?

Learning Runtime Parameters in Computer Systems with Delayed Experience Injection

Utilization of Deep Reinforcement Learning for saccadic-based object visual search

Online Contrastive Divergence with Generative Replay: Experience Replay without Storing Data

The End of Optimism? An Asymptotic Analysis of Finite-Armed Linear Bandits

Convolutional Neural Networks For Automatic State-Time Feature Extraction in Reinforcement Learning Applied to Residential Load Control

Reset-Free Guided Policy Search: Efficient Deep Reinforcement Learning with Stochastic Initial States

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search

Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer

Policy Error Bounds for Model-Based Reinforcement Learning with Factored Linear Models

ViZDoom: A Doom-based AI Research Platform for Visual Reinforcement Learning

Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning

Single photon in hierarchical architecture for physical reinforcement learning: Photon intelligence

Actor-critic versus direct policy search: a comparison based on sample complexity

Reinforcement Learning algorithms for regret minimization in structured Markov Decision Processes

One-Shot Learning of Manipulation Skills with Online Dynamics Adaptation and Neural Network Priors

Online Adaptation of Deep Architectures with Reinforcement Learning

Efficient Reinforcement Learning in Deterministic Systems with Value Function Generalization

Deep Reinforcement Learning from Self-Play in Imperfect-Information Games

Approachability in Stackelberg Stochastic Games with Vector Costs

Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks

Reinforcement Learning for Semantic Segmentation in Indoor Scenes

Thompson Sampling is Asymptotically Optimal in General Environments

Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation

Deep Reinforcement Learning Radio Control and Signal Detection with KeRLym, a Gym RL Agent

Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization

Doubly Robust Off-policy Value Evaluation for Reinforcement Learning

Localizing by Describing: Attribute-Guided Attention Localization for Fine-Grained Recognition

Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning

State of the Art Control of Atari Games Using Shallow Reinforcement Learning

Theoretically-Grounded Policy Advice from Multiple Teachers in Reinforcement Learning Settings with Applications to Negative Transfer

A statistical learning strategy for closed-loop control of fluid flows

Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning

Optimal Recommendation to Users that React: Online Learning for a Class of POMDPs

Model-based Reinforcement Learning with Parametrized Physical Models and Optimism-Driven Exploration

Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control

Learning Deep Control Policies for Autonomous Aerial Vehicles with MPC-Guided Policy Search

Data-Efficient Reinforcement Learning in Continuous-State POMDPs

How to Discount Deep Reinforcement Learning: Towards New Dynamic Strategies

On the convergence of cycle detection for navigational reinforcement learning

Action-Conditional Video Prediction using Deep Networks in Atari Games

Reinforcement Learning Applied to an Electric Water Heater: From Theory to Practice

Towards Vision-Based Deep Reinforcement Learning for Robotic Motion Control

Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning

The Online Coupon-Collector Problem and Its Application to Lifelong Reinforcement Learning

The Advantage of Cross Entropy over Entropy in Iterative Information Gathering

Optimization of anemia treatment in hemodialysis patients via reinforcement learning

Compatible Value Gradients for Reinforcement Learning of Continuous Deep Policies

Reward Shaping with Recurrent Neural Networks for Speeding up On-Line Policy Learning in Spoken Dialogue Systems

Learning from Real Users: Rating Dialogue Success with Neural Networks for Reinforcement Learning in Spoken Dialogue Systems

From Pixels to Torques: Policy Learning with Deep Dynamical Models

Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret

Optimal Nudging: Solving Average-Reward Semi-Markov Decision Processes as a Minimal Sequence of Cumulative Tasks

Autonomous CRM Control via CLV Approximation with Deep Reinforcement Learning in Discrete and Continuous Action Space

Thompson Sampling for Learning Parameterized Markov Decision Processes

DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation

Optimistic Risk Perception in the Temporal Difference error Explains the Relation between Risk-taking, Gambling, Sensation-seeking and Low Fear

Grounding Hierarchical Reinforcement Learning Models for Knowledge Transfer

Multiple Instance Reinforcement Learning for Efficient Weakly-Supervised Detection in Images

A Comparison of learning algorithms on the Arcade Learning Environment

Where do goals come from? A Generic Approach to Autonomous Goal-System Development

Domain-Independent Optimistic Initialization for Reinforcement Learning

Selecting Near-Optimal Approximate State Representations in Reinforcement Learning

Probabilistic inverse reinforcement learning in unknown environments

Efficient Learning and Planning with Compressed Predictive States

Classification-based Approximate Policy Iteration: Experiments and Extended Discussions

Personalized Medical Treatments Using Novel Reinforcement Learning Algorithms

Optimal Demand Response Using Device Based Reinforcement Learning

Reinforcement and Imitation Learning via Interactive No-Regret Learning

Proximal Reinforcement Learning: A New Theory of Sequential Decision Making in Primal-Dual Spaces

Comparison of Multi-agent and Single-agent Inverse Learning on a Simulated Soccer Example

A General Framework for Interacting Bayes-Optimally with Self-Interested Agents using Arbitrary Parametric Model and Model Prior

Intrinsically Motivated Learning of Visual Motion Perception and Smooth Pursuit

Safe Exploration of State and Action Spaces in Reinforcement Learning

A Multiagent Reinforcement Learning Algorithm with Non-linear Dynamics

Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search

On the definition of a general learning system with user-defined operators

Reinforcement Learning for Matrix Computations: PageRank as an Example

Sequential Transfer in Multi-armed Bandit with Finite Set of Models

Model-Based Policy Gradients with Parameter-Based Exploration by Least-Squares Conditional Density Estimation

Policy Search: Any Local Optimum Enjoys a Global Performance Guarantee

Fast Reinforcement Learning for Energy-Efficient Wireless Communications

Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems

Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning

On Improving Energy Efficiency within Green Femtocell Networks: A Hierarchical Reinforcement Learning Approach

Monte-Carlo utility estimates for Bayesian reinforcement learning

The Importance of Clipping in Neurocontrol by Direct Gradient Descent on the Cost-to-Go Function and in Adaptive Dynamic Programming

Online Regret Bounds for Undiscounted Continuous Reinforcement Learning

Multi-class Generalized Binary Search for Active Inverse Reinforcement Learning

Efficient Sample Reuse in Policy Gradients with Parameter-based Exploration

The Optimal Reward Baseline for Gradient-Based Reinforcement Learning

The Thing That We Tried Didn't Work Very Well : Deictic Representation in Reinforcement Learning

A New Automatic Method to Adjust Parameters for Object Recognition

$QD$-Learning: A Collaborative Distributed Strategy for Multi-Agent Reinforcement Learning Through Consensus + Innovations

Modeling transition dynamics in MDPs with RKHS embeddings of conditional distributions

Value Function Approximation in Noisy Environments Using Locally Smoothed Regularized Approximate Linear Programs

Improving Energy Efficiency in Femtocell Networks: A Hierarchical Reinforcement Learning Framework

Design of Spectrum Sensing Policy for Multi-user Multi-band Cognitive Radio Network

The Divergence of Reinforcement Learning Algorithms with Value-Iteration and Function Approximation

A Multi-Agents Architecture to Learn Vision Operators and their Parameters

Agnostic System Identification for Model-Based Reinforcement Learning

Statistical Linear Estimation with Penalized Estimators: an Application to Reinforcement Learning

On the Sample Complexity of Reinforcement Learning with a Generative Model

Apprenticeship Learning using Inverse Reinforcement Learning and Gradient Methods

Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting

Path Integral Policy Improvement with Covariance Matrix Adaptation

Continuous Inverse Optimal Control with Locally Optimal Examples

Exploring compact reinforcement-learning representations with linear regression

REGAL: A Regularization based Algorithm for Reinforcement Learning in Weakly Communicating MDPs

A Bayesian Sampling Approach to Exploration in Reinforcement Learning

Distributed Cooperative Q-learning for Power Allocation in Cognitive Femtocell Networks

Variance-Based Rewards for Approximate Bayesian Reinforcement Learning

Fast Reinforcement Learning with Large Action Sets using Error-Correcting Output Codes for MDP Factorization

On the Performance of Maximum Likelihood Inverse Reinforcement Learning

Learning in embodied action-perception loops through exploration

A Reinforcement Learning Model Using Neural Networks for Music Sight Reading Learning Problem

Robust Bayesian reinforcement learning through tight lower bounds

Reinforcement learning based sensing policy optimization for energy efficient cognitive radio networks

Risk-Sensitive Reinforcement Learning Applied to Control under Constraints

Potential-Based Shaping and Q-Value Initialization are Equivalent

Learning Equilibria with Partial Information in Decentralized Wireless Networks

Efficient Reinforcement Learning Using Recursive Least-Squares Methods

Optimizing Dialogue Management with Reinforcement Learning: Experiments with the NJFun System

Reducing Commitment to Tasks with Off-Policy Hierarchical Reinforcement Learning

The Local Optimality of Reinforcement Learning by Value Gradients, and its Relationship to Policy Gradient Learning

A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

Optimism in Reinforcement Learning and Kullback-Leibler Divergence

Complexity of stochastic branch and bound methods for belief tree search in Bayesian reinforcement learning

Optimistic Simulated Exploration as an Incentive for Real Exploration

On the Possibility of Learning in Reactive Environments with Arbitrary Dependence

Reinforcement Learning with Linear Function Approximation and LQ control Converges

Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence

Bounds on sample size for policy evaluation in Markov environments

Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition

PINNup: Robust neural network wavefield solutions using frequency upscaling and neuron splitting

EBSD Grain Knowledge Graph Representation Learning for Material Structure-Property Prediction

On Brightness Agnostic Adversarial Examples Against Face Recognition Systems

An Automatic System to Monitor the Physical Distance and Face Mask Wearing of Construction Workers in COVID-19 Pandemic

Physics-Augmented Learning: A New Paradigm Beyond Physics-Informed Learning

Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling

Compound eye inspired flat lensless imaging with spatially-coded Voronoi-Fresnel phase

An Adaptive Deep Learning Framework for Day-ahead Forecasting of Photovoltaic Power Generation

Using neural networks to solve the 2D Poisson equation for electric field computation in plasma fluid simulations

Probabilistic modeling of lake surface water temperature using a Bayesian spatio-temporal graph convolutional neural network

OpenRooms: An End-to-End Open Framework for Photorealistic Indoor Scene Datasets

Copula-based synthetic data augmentation for machine-learning emulators

Physics perception in sloshing scenes with guaranteed thermodynamic consistency

SIMstack: A Generative Shape and Instance Model for Unordered Object Stacks

Physics-informed Convolutional Neural Networks for Temperature Field Prediction of Heat Source Layout without Labeled Data

mGNN: Generalizing the Graph Neural Networks to the Multilayer Case

A Predictive Visual Analytics System for Studying Neurodegenerative Disease based on DTI Fiber Tracts

Ground material classification and for UAV-based photogrammetric 3D data A 2D-3D Hybrid Approach

Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy

Efficient, Interpretable Atomistic Graph Neural Network Representation for Angle-dependent Properties and its Application to Optical Spectroscopy Prediction

End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction

Learning Dynamics from Noisy Measurements using Deep Learning with a Runge-Kutta Constraint

A Skeleton-Driven Neural Occupancy Representation for Articulated Hands

Federated Feature Selection for Cyber-Physical Systems of Systems

Towards Fine-grained 3D Face Dense Registration: An Optimal Dividing and Diffusing Method

WiSoSuper: Benchmarking Super-Resolution Methods on Wind and Solar Data

Quantifying Model Predictive Uncertainty with Perturbation Theory

Cross-Subject Statistical Shift Estimation for Generalized Electroencephalography-based Mental Workload Assessment

Cramér-Rao bound-informed training of neural networks for quantitative MRI

NudgeSeg: Zero-Shot Object Segmentation by Repeated Physical Interaction

Single Image Dehazing with An Independent Detail-Recovery Network

A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation

Short-term traffic prediction using physics-aware neural networks

Adaptive Reliability Analysis for Multi-fidelity Models using a Collective Learning Strategy

Revisiting the Characteristics of Stochastic Gradient Noise and Dynamics

Teaching Cameras to Feel: Estimating Tactile Physical Properties of Surfaces From Images

When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?

Incremental Learning Techniques for Online Human Activity Recognition

Learning in Sinusoidal Spaces with Physics-Informed Neural Networks

Statistical Mechanics of Deep Linear Neural Networks: The Back-Propagating Kernel Renormalization

MM-Deacon: Multimodal molecular domain embedding analysis via contrastive learning

Graph Learning for Cognitive Digital Twins in Manufacturing Systems

DeepPhysics: a physics aware deep learning framework for real-time simulation

Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI

Pedestrian Trajectory Prediction with Convolutional Neural Networks

An Online Algorithm for Maximum-Likelihood Quantum State Tomography

Decoupling Long- and Short-Term Patterns in Spatiotemporal Inference

Conditionally Parameterized, Discretization-Aware Neural Networks for Mesh-Based Modeling of Physical Systems

Federated Learning of Molecular Properties in a Heterogeneous Setting

FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack

Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed Hermite-Spline CNNs

YouRefIt: Embodied Reference Understanding with Language and Gesture

Automatic Symmetry Discovery with Lie Algebra Convolutional Network

Data-Driven Theory-guided Learning of Partial Differential Equations using SimultaNeous Basis Function Approximation and Parameter Estimation (SNAPE)

Leveraging Recent Advances in Deep Learning for Audio-Visual Emotion Recognition

A machine-learning framework for daylight and visual comfort assessment in early design stages

CLAIMED: A CLAssification-Incorporated Minimum Energy Design to explore a multivariate response surface with feasibility constraints

Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling

Learning Indoor Inverse Rendering with 3D Spatially-Varying Lighting

Vision-based system identification and 3D keypoint discovery using dynamics constraints

Physical Adversarial Attacks on an Aerial Imagery Object Detector

A physics-informed variational DeepONet for predicting the crack path in brittle materials

PQ-Transformer: Jointly Parsing 3D Objects and Layouts from Point Clouds

Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling

Adaptive network reliability analysis: Methodology and applications to power grid

Remaining Useful Life Estimation of Hard Disk Drives using Bidirectional LSTM Networks

DynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction

CPF: Learning a Contact Potential Field to Model the Hand-Object Interaction

Physics-based machine learning for modeling stochastic IP3-dependent calcium dynamics

Hybrid modeling of the human cardiovascular system using NeuralFMUs

Nonparametric posterior learning for emission tomography with multimodal data

Inverse design of 3d molecular structures with conditional generative neural networks

PIP: Physical Interaction Prediction via Mental Imagery with Span Selection

TENET: Temporal CNN with Attention for Anomaly Detection in Automotive Cyber-Physical Systems

NeuralFMU: Towards Structural Integration of FMUs into Neural Networks

DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks

GNisi: A graph network for reconstructing Ising models from multivariate binarized data

Application of the Singular Spectrum Analysis on electroluminescence images of thin-film photovoltaic modules

Bayesian Optimisation for Sequential Experimental Design with Applications in Additive Manufacturing

ISCL: Interdependent Self-Cooperative Learning for Unpaired Image Denoising

Wave-Informed Matrix Factorization with Global Optimality Guarantees

How Can Increased Randomness in Stochastic Gradient Descent Improve Generalization?

Memorizing without overfitting: Bias, variance, and interpolation in over-parameterized models

Disentangling Alzheimer's disease neurodegeneration from typical brain aging using machine learning

A comparison of combined data assimilation and machine learning methods for offline and online model error correction

ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations

Backdoor Attacks Against Deep Learning Systems in the Physical World

Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models

ConvNets for Counting: Object Detection of Transient Phenomena in Steelpan Drums

Detect the Interactions that Matter in Matter: Geometric Attention for Many-Body Systems

Data-Driven Wind Turbine Wake Modeling via Probabilistic Machine Learning

Learning Interpretable Representations of Entanglement in Quantum Optics Experiments using Deep Generative Models

Physics-Informed Deep Learning: A Promising Technique for System Reliability Assessment

Estimating permeability of 3D micro-CT images by physics-informed CNNs based on DNS

Wildfire smoke plume segmentation using geostationary satellite imagery

Stochastic Physics-Informed Neural Networks (SPINN): A Moment-Matching Framework for Learning Hidden Physics within Stochastic Differential Equations

Segmentation of turbulent computational fluid dynamics simulations with unsupervised ensemble learning

Characterizing possible failure modes in physics-informed neural networks

Model of the Weak Reset Process in HfOx Resistive Memory for Deep Learning Frameworks

Heterogeneous relational message passing networks for molecular dynamics simulations

Combining machine learning and data assimilation to forecast dynamical systems from noisy partial observations

Physics-integrated hybrid framework for model form error identification in nonlinear dynamical systems

RP2K: A Large-Scale Retail Product Dataset for Fine-Grained Image Classification

Machine Learning for Naval Architecture, Ocean and Marine Engineering

Acceleration Method for Learning Fine-Layered Optical Neural Networks

DPA: Learning Robust Physical Adversarial Camouflages for Object Detectors

Mutually improved endoscopic image synthesis and landmark detection in unpaired image-to-image translation

Physics-Incorporated Convolutional Recurrent Neural Networks for Source Identification and Forecasting of Dynamical Systems

Multitask 3D CBCT-to-CT Translation and Organs-at-Risk Segmentation Using Physics-Based Data Augmentation

Deformation Driven Seq2Seq Longitudinal Tumor and Organs-at-Risk Prediction for Radiotherapy

Rapidly and accurately estimating brain strain and strain rate across head impact types with transfer learning and data fusion

Improving Transferability of Adversarial Patches on Face Recognition with Generative Models

Airplane Type Identification Based on Mask RCNN and Drone Images

Investigation of Nonlinear Model Order Reduction of the Quasigeostrophic Equations through a Physics-Informed Convolutional Autoencoder

A Convolutional Neural Network-based Approach to Field Reconstruction

Sub-millisecond Video Synchronization of Multiple Android Smartphones

Unsupervised Reservoir Computing for Solving Ordinary Differential Equations

Physically Plausible Pose Refinement using Fully Differentiable Forces

EDEN: Deep Feature Distribution Pooling for Saimaa Ringed Seals Pattern Matching

GrADE: A graph based data-driven solver for time-dependent nonlinear partial differential equations

MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-View Stereo

CoPhy-PGNN: Learning Physics-guided Neural Networks with Competing Loss Functions for Solving Eigenvalue Problems

Deep-RBF Networks for Anomaly Detection in Automotive Cyber-Physical Systems

MFNets: Data efficient all-at-once learning of multifidelity surrogates as directed networks of information sources

C5T5: Controllable Generation of Organic Molecules with Transformers

Molecular Design Based on Artificial Neural Networks, Integer Programming and Grid Neighbor Search

Deep Bayesian Image Set Classification: A Defence Approach against Adversarial Attacks

Rainfall-runoff prediction using a Gustafson-Kessel clustering based Takagi-Sugeno Fuzzy model

Holistic 3D Scene Understanding from a Single Image with Implicit Representation

Geometry-based Distance Decomposition for Monocular 3D Object Detection

Reservoir Computing with Diverse Timescales for Prediction of Multiscale Dynamics

A Multiple-View Geometric Model for Specularity Prediction on Non-Uniformly Curved Surfaces

Low-Rank Dynamic Mode Decomposition: An Exact and Tractable Solution

PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier

Estimation of Convex Polytopes for Automatic Discovery of Charge State Transitions in Quantum Dot Arrays

Am I fit for this physical activity? Neural embedding of physical conditioning from inertial sensors

Flood Segmentation on Sentinel-1 SAR Imagery with Semi-Supervised Learning

Local Latin Hypercube Refinement for Multi-objective Design Uncertainty Optimization

Adversarial domain adaptation to reduce sample bias of a high energy physics classifier

Rescaling CNN through Learnable Repetition of Network Parameters

Spatially-Adaptive Image Restoration using Distortion-Guided Networks

Network-wide link travel time and station waiting time estimation using automatic fare collection data: A computational graph approach

Scarce Data Driven Deep Learning of Drones via Generalized Data Distribution Space

Deep Photo Scan: Semi-Supervised Learning for dealing with the real-world degradation in Smartphone Photo Scanning

Higgs Boson Classification: Brain-inspired BCPNN Learning with StreamBrain

Network Generalization Prediction for Safety Critical Tasks in Novel Operating Domains

A Physics Informed Neural Network Approach to Solution and Identification of Biharmonic Equations of Elasticity

Patch Attack Invariance: How Sensitive are Patch Attacks to 3D Pose?

Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather

Improving Molecular Design by Stochastic Iterative Target Augmentation

Improving the trustworthiness of image classification models by utilizing bounding-box annotations

Pattern Inversion as a Pattern Recognition Method for Machine Learning

Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch Attacks

Targeted Physical-World Attention Attack on Deep Learning Models in Road Sign Recognition

Using Machine Learning to Predict Engineering Technology Students' Success with Computer Aided Design

ST-PCNN: Spatio-Temporal Physics-Coupled Neural Networks for Dynamics Forecasting

FrequentNet: A Novel Interpretable Deep Learning Model for Image Classification

Manifold-aware Synthesis of High-resolution Diffusion from Structural Imaging

When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes

Known Operator Learning and Hybrid Machine Learning in Medical Imaging -- A Review of the Past, the Present, and the Future

A Generalizable Model-and-Data Driven Approach for Open-Set RFF Authentication

An Extensible Benchmark Suite for Learning to Simulate Physical Systems

DRINet: A Dual-Representation Iterative Learning Network for Point Cloud Segmentation

Pedestrian Trajectory Prediction using Context-Augmented Transformer Networks

From Synthetic to Real: Image Dehazing Collaborating with Unlabeled Real Data

The Impact of Machine Learning on 2D/3D Registration for Image-guided Interventions: A Systematic Review and Perspective

Terabyte-scale supervised 3D training and benchmarking dataset of the mouse kidney

Ensemble Slice Sampling: Parallel, black-box and gradient-free inference for correlated & multimodal distributions

Classifying action correctness in physical rehabilitation exercises

Machine learning approach to force reconstruction in photoelastic materials

Robust Binary Neural Network Operation from 233 K to 398 K via Gate Stack and Bias Optimization of Ferroelectric FinFET Synapses

Forward-Looking Sonar Patch Matching: Modern CNNs, Ensembling, and Uncertainty

Enhancing Environmental Enforcement with Near Real-Time Monitoring: Likelihood-Based Detection of Structural Expansion of Intensive Livestock Farms

High-fidelity Prediction of Megapixel Longitudinal Phase-space Images of Electron Beams using Encoder-Decoder Neural Networks

Data-driven model for hydraulic fracturing design optimization. Part II: Inverse problem

CERL: A Unified Optimization Framework for Light Enhancement with Realistic Noise

Multi-objective optimization and explanation for stroke risk assessment in Shanxi province

Personalized Stress Monitoring using Wearable Sensors in Everyday Settings

Physics-Informed Machine Learning Method for Large-Scale Data Assimilation Problems

Lithography Hotspot Detection via Heterogeneous Federated Learning with Local Adaptation

Improving Variational Autoencoder based Out-of-Distribution Detection for Embedded Real-time Applications

Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization

ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction

MLMOD Package: Machine Learning Methods for Data-Driven Modeling in LAMMPS

Structure and Performance of Fully Connected Neural Networks: Emerging Complex Network Properties

ReLearn: A Robust Machine Learning Framework in Presence of Missing Data for Multimodal Stress Detection from Physiological Signals

Learning second order coupled differential equations that are subject to non-conservative forces

Learning the shape of female breasts: an open-access 3D statistical shape model of the female breast built from 110 breast scans

SPINN: Sparse, Physics-based, and partially Interpretable Neural Networks for PDEs

On Board Volcanic Eruption Detection through CNNs and Satellite Multispectral Imagery

Assessment of Deep Learning-based Heart Rate Estimation using Remote Photoplethysmography under Different Illuminations

Machine Learning based CVD Virtual Metrology in Mass Produced Semiconductor Process

Towards Adversarial Patch Analysis and Certified Defense against Crowd Counting

Optimal Thompson Sampling strategies for support-aware CVaR bandits

Physics-Enforced Modeling for Insertion Loss of Transmission Lines by Deep Neural Networks

Restricted Boltzmann Machine and Deep Belief Network: Tutorial and Survey

State, global and local parameter estimation using local ensemble Kalman filters: applications to online machine learning of chaotic dynamics

Physics-constrained Deep Learning for Robust Inverse ECG Modeling

Anomalous diffusion dynamics of learning in deep neural networks

Predictive Monitoring with Logic-Calibrated Uncertainty for Cyber-Physical Systems

DeepPlastic: A Novel Approach to Detecting Epipelagic Bound Plastic Using Deep Visual Models

Training multi-objective/multi-task collocation physics-informed neural network with student/teachers transfer learnings

Forecasting the outcome of spintronic experiments with Neural Ordinary Differential Equations

A novel meta-learning initialization method for physics-informed neural networks

Discovering Sparse Interpretable Dynamics from Partial Observations

Adversarial Robustness Guarantees for Random Deep Neural Networks

A deep learning approach for inverse design of the metasurface for dual-polarized waves

Personalized Federated Learning over non-IID Data for Indoor Localization

Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference

Rethinking the limiting dynamics of SGD: modified loss, phase space oscillations, and anomalous diffusion

Accelerating deep neural networks for efficient scene understanding in automotive cyber-physical systems

Exploring the efficacy of neural networks for trajectory compression and the inverse problem

Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes

Model Uncertainty and Correctability for Directed Graphical Models

A comparative study of stochastic and deep generative models for multisite precipitation synthesis

Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems

Uncertainty Prediction for Machine Learning Models of Material Properties

Variational Integrator Graph Networks for Learning Energy Conserving Dynamical Systems

Solving inverse problems with deep neural networks driven by sparse signal decomposition in a physics-based dictionary

Towards an Interpretable Latent Space in Structured Models for Video Prediction

A Robust Deep Learning Workflow to Predict Multiphase Flow Behavior during Geological CO2 Sequestration Injection and Post-Injection Periods

Lidar Light Scattering Augmentation (LISA): Physics-based Simulation of Adverse Weather Conditions for 3D Object Detection

Extreme Precipitation Seasonal Forecast Using a Transformer Neural Network

Interpreting Criminal Charge Prediction and Its Algorithmic Bias via Quantum-Inspired Complex Valued Networks

A Physics-Informed Deep Learning Paradigm for Car-Following Models

Adaptive Machine Learning for Time-Varying Systems: Low Dimensional Latent Space Tuning

MSR-Net: Multi-Scale Relighting Network for One-to-One Relighting

A Deep Generative Artificial Intelligence system to decipher species coexistence patterns

Explainable artificial intelligence for mechanics: physics-informing neural networks for constitutive models

Training deep cross-modality conversion models with a small amount of data and its application to MVCT to kVCT conversion

Self-Attentive Ensemble Transformer: Representing Ensemble Interactions in Neural Networks for Earth System Models

Universal Multilayer Network Exploration by Random Walk with Restart

MotionRNN: A Flexible Model for Video Prediction with Spacetime-Varying Motions

Parsimony-Enhanced Sparse Bayesian Learning for Robust Discovery of Partial Differential Equations

IowaRain: A Statewide Rain Event Dataset Based on Weather Radars and Quantitative Precipitation Estimation

Probabilistic partition of unity networks: clustering based deep approximation

Solution of Physics-based Bayesian Inverse Problems with Deep Generative Priors

New Methods and Datasets for Group Anomaly Detection From Fundamental Physics

HybrUR: A Hybrid Physical-Neural Solution for Unsupervised Underwater Image Restoration

On Robustness of Lane Detection Models to Physical-World Adversarial Attacks in Autonomous Driving

Connectivity Matters: Neural Network Pruning Through the Lens of Effective Sparsity

Physics-Informed Graph Learning for Robust Fault Location in Distribution Systems

Physics-Informed Deep Reversible Regression Model for Temperature Field Reconstruction of Heat-Source Systems

Effects of boundary conditions in fully convolutional networks for learning spatio-temporal dynamics

Rayleigh-Gauss-Newton optimization with enhanced sampling for variational Monte Carlo

Combinatorial Optimization with Physics-Inspired Graph Neural Networks

Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks

A Functional Perspective on Learning Symmetric Functions with Neural Networks

Shared Data and Algorithms for Deep Learning in Fundamental Physics

Fast Gravitational Approach for Rigid Point Set Registration with Ordinary Differential Equations

A Fully Bayesian Gradient-Free Supervised Dimension Reduction Method using Gaussian Processes

A Multi-task Two-stream Spatiotemporal Convolutional Neural Network for Convective Storm Nowcasting

Discovering conservation laws from trajectories via machine learning

Semantic Segmentation of Periocular Near-Infra-Red Eye Images Under Alcohol Effects

Probabilistic Graphical Models and Tensor Networks: A Hybrid Framework

Attentive Neural Processes and Batch Bayesian Optimization for Scalable Calibration of Physics-Informed Digital Twins

Inconspicuous Adversarial Patches for Fooling Image Recognition Systems on Mobile Devices

O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learning

The Implications of the No-Free-Lunch Theorems for Meta-induction

PhysiNet: A Combination of Physics-based Model and Neural Network Model for Digital Twins

DONet: Learning Category-Level 6D Object Pose and Size Estimation from Depth Observation

Machine Learning Detection Algorithm for Large Barkhausen Jumps in Cluttered Environment

PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs

Advanced Stationary and Non-Stationary Kernel Designs for Domain-Aware Gaussian Processes

Transient Stability Analysis with Physics-Informed Neural Networks

Unsupervised embedding of trajectories captures the latent structure of mobility

A hybrid model-based and learning-based approach for classification using limited number of training samples

Unified Shape and SVBRDF Recovery using Differentiable Monte Carlo Rendering

Geometric learning of the conformational dynamics of molecules using dynamic graph neural networks

Receiver operating characteristic (ROC) movies, universal ROC (UROC) curves, and coefficient of predictive ability (CPA)

Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design

Relationship between pulmonary nodule malignancy and surrounding pleurae, airways and vessels: a quantitative study using the public LIDC-IDRI dataset

GAN-MDF: A Method for Multi-fidelity Data Fusion in Digital Twins

Few-Shot Bearing Fault Diagnosis Based on Model-Agnostic Meta-Learning

FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging

Self-Supervised Learning for 3D Medical Image Analysis using 3D SimCLR and Monte Carlo Dropout

Unsupervised Domain Adaptation in Semantic Segmentation Based on Pixel Alignment and Self-Training

Semi-supervised Contrastive Learning for Label-efficient Medical Image Segmentation

Positional Contrastive Learning for Volumetric Medical Image Segmentation

Inter Extreme Points Geodesics for Weakly Supervised Image Segmentation

mDALU: Multi-Source Domain Adaptation and Label Unification with Partial Datasets

Using Soft Labels to Model Uncertainty in Medical Image Segmentation

Towards to Robust and Generalized Medical Image Segmentation Framework

Enforcing Mutual Consistency of Hard Regions for Semi-supervised Medical Image Segmentation

Parameter Decoupling Strategy for Semi-supervised 3D Left Atrium Segmentation

Background-Foreground Segmentation for Interior Sensing in Automotive Industry

EdgeFlow: Achieving Practical Interactive Segmentation with Edge-Guided Flow

Efficient Hybrid Transformer: Learning Global-local Context for Urban Sence Segmentation

Semi-supervised Meta-learning with Disentanglement for Domain-generalised Medical Image Segmentation

Neural Architecture Search in operational context: a remote sensing case-study

Patch-based medical image segmentation using Quantum Tensor Networks

Combo Loss: Handling Input and Output Imbalance in Multi-Organ Segmentation

POPCORN: Progressive Pseudo-labeling with Consistency Regularization and Neighboring

HCDG: A Hierarchical Consistency Framework for Domain Generalization on Medical Image Segmentation

UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer

Attention-Based 3D Seismic Fault Segmentation Training by a Few 2D Slice Labels

From Contexts to Locality: Ultra-high Resolution Image Segmentation via Locality-aware Contextual Correlation

A Critical Connectivity Radius for Segmenting Randomly-Generated, High Dimensional Data Points

Autonomous Removal of Perspective Distortion of Elevator Button Images based on Corner Detection

Box-Adapt: Domain-Adaptive Medical Image Segmentation using Bounding BoxSupervision

ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentation

Re-using Adversarial Mask Discriminators for Test-time Training under Distribution Shifts

Mining Contextual Information Beyond Image for Semantic Segmentation

PoissonSeg: Semi-Supervised Few-Shot Medical Image Segmentation via Poisson Learning

Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation

Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels

Multi-task Federated Learning for Heterogeneous Pancreas Segmentation

Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation

SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation

Multi-Slice Dense-Sparse Learning for Efficient Liver and Tumor Segmentation

Real-Time Multi-Modal Semantic Fusion on Unmanned Aerial Vehicles

Hierarchical Random Walker Segmentation for Large Volumetric Biomedical Images

Few-Shot Segmentation with Global and Local Contrastive Learning

AASeg: Attention Aware Network for Real Time Semantic Segmentation

Contrastive Semi-Supervised Learning for 2D Medical Image Segmentation

Efficient and Generic Interactive Segmentation Framework to Correct Mispredictions during Clinical Evaluation of Medical Images

Hidden Markov Modeling for Maximum Likelihood Neuron Reconstruction

Improving Aleatoric Uncertainty Quantification in Multi-Annotated Medical Image Segmentation with Normalizing Flows

Recurrent Mask Refinement for Few-Shot Medical Image Segmentation

Transductive image segmentation: Self-training and effect of uncertainty estimation

Visual Boundary Knowledge Translation for Foreground Segmentation

Iterative, Deep, and Unsupervised Synthetic Aperture Sonar Image Segmentation

Comprehensive Validation of Automated Whole Body Skeletal Muscle, Adipose Tissue, and Bone Segmentation from 3D CT images for Body Composition Analysis: Towards Extended Body Composition

Crosslink-Net: Double-branch Encoder Segmentation Network via Fusing Vertical and Horizontal Convolutions

Superpixel-guided Iterative Learning from Noisy Labels for Medical Image Segmentation

Weighted Intersection over Union (wIoU): A New Evaluation Metric for Image Segmentation

Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation

LeViT-UNet: Make Faster Encoders with Transformer for Medical Image Segmentation

A Weighted Difference of Anisotropic and Isotropic Total Variation for Relaxed Mumford-Shah Color and Multiphase Image Segmentation

Learning from Partially Overlapping Labels: Image Segmentation under Annotation Shift

TransClaw U-Net: Claw U-Net with Transformers for Medical Image Segmentation

Privacy Preserving Domain Adaptation for Semantic Segmentation of Medical Images

A Spatial Guided Self-supervised Clustering Network for Medical Image Segmentation

Anatomy of Domain Shift Impact on U-Net Layers in MRI Segmentation

Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation

TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation

Medical Matting: A New Perspective on Medical Segmentation with Uncertainty

Flexibly Regularized Mixture Models and Application to Image Segmentation

Semi-supervised Left Atrium Segmentation with Mutual Consistency Training

Medical Transformer: Gated Axial-Attention for Medical Image Segmentation

Label noise in segmentation networks : mitigation must deal with bias

Quality-Aware Memory Network for Interactive Volumetric Image Segmentation

A Deep Learning Object Detection Method for an Efficient Clusters Initialization

CHASE: Robust Visual Tracking via Cell-Level Differentiable Neural Architecture Search

Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation

Unsupervised Image Segmentation by Mutual Information Maximization and Adversarial Regularization

Segmenting two-dimensional structures with strided tensor networks

Segmentation with Multiple Acceptable Annotations: A Case Study of Myocardial Segmentation in Contrast Echocardiography

Information-Theoretic Segmentation by Inpainting Error Maximization

Multi-Compound Transformer for Accurate Biomedical Image Segmentation

ComBiNet: Compact Convolutional Bayesian Neural Network for Image Segmentation

Semantics-aware Multi-modal Domain Translation:From LiDAR Point Clouds to Panoramic Color Images

Attention Toward Neighbors: A Context Aware Framework for High Resolution Image Segmentation

Boosting Semi-supervised Image Segmentation with Global and Local Mutual Information Regularization

Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentation

Transformer Meets Convolution: A Bilateral Awareness Net-work for Semantic Segmentation of Very Fine Resolution Ur-ban Scene Images

Automatic Head Overcoat Thickness Measure with NASNet-Large-Decoder Net

Distilling effective supervision for robust medical image segmentation with noisy labels

Large-scale image segmentation based on distributed clustering algorithms

How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

Guided interactive image segmentation using machine learning and color based data set clustering

Knowledge distillation from multi-modal to mono-modal segmentation networks

Trilateral Attention Network for Real-time Medical Image Segmentation

Optimal Latent Vector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation

Bayesian dense inverse searching algorithm for real-time stereo matching in minimally invasive surgery

DS-TransUNet:Dual Swin Transformer U-Net for Medical Image Segmentation

Self-Ensembling Contrastive Learning for Semi-Supervised Medical Image Segmentation

GSVNet: Guided Spatially-Varying Convolution for Fast Semantic Segmentation on Video

Weakly Supervised Volumetric Image Segmentation with Deformed Templates

Few-shot segmentation of medical images based on meta-learning with implicit gradients

Semi-Supervised Domain Adaptation via Adaptive and Progressive Feature Alignment

Points2Polygons: Context-Based Segmentation from Weak Labels Using Adversarial Networks

Attention-Guided Supervised Contrastive Learning for Semantic Segmentation

nnDetection: A Self-configuring Method for Medical Object Detection

A Thorough View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy

DAAIN: Detection of Anomalous and Adversarial Input using Normalizing Flows

CFPNet-M: A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation

High-Resolution Segmentation of Tooth Root Fuzzy Edge Based on Polynomial Curve Fitting with Landmark Detection

Learning Fuzzy Clustering for SPECT/CT Segmentation via Convolutional Neural Networks

Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions

Learning Uncertainty For Safety-Oriented Semantic Segmentation In Autonomous Driving

Gaussian Dynamic Convolution for Efficient Single-Image Segmentation

Full Page Handwriting Recognition via Image to Sequence Extraction

Uma implementação do jogo Pedra, Papel e Tesoura utilizando Visao Computacional

Deep Active Contours Using Locally Controlled Distance Vector Flow

SemSegLoss: A python package of loss functions for semantic segmentation

Finding an Unsupervised Image Segmenter in Each of Your Deep Generative Models

Voxel-level Siamese Representation Learning for Abdominal Multi-Organ Segmentation

CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation

GeoSim: Realistic Video Simulation via Geometry-Aware Composition for Self-Driving

Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentation

VICE: Visual Identification and Correction of Neural Circuit Errors

Boundary-Aware Segmentation Network for Mobile and Web Applications

MDA-Net: Multi-Dimensional Attention-Based Neural Network for 3D Image Segmentation

A Characteristic Function-based Algorithm for Geodesic Active Contours

Geodesic Paths for Image Segmentation with Implicit Region-based Homogeneity Enhancement

Impact of individual rater style on deep learning uncertainty in medical imaging segmentation

Bayesian Logistic Shape Model Inference: application to cochlea image segmentation

Encoder Fusion Network with Co-Attention Embedding for Referring Image Segmentation

Combining Supervised and Un-supervised Learning for Automatic Citrus Segmentation

Computer vision for liquid samples in hospitals and medical labs using hierarchical image segmentation and relations prediction

A Generalized Asymmetric Dual-front Model for Active Contours and Image Segmentation

Beyond pixel-wise supervision for segmentation: A few global shape descriptors might be surprisingly good!

CASSOD-Net: Cascaded and Separable Structures of Dilated Convolution for Embedded Vision Systems and Applications

Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation

Every Annotation Counts: Multi-label Deep Supervision for Medical Image Segmentation

Benefits of Linear Conditioning with Metadata for Image Segmentation

MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning

GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement

ObjectAug: Object-level Data Augmentation for Semantic Image Segmentation

DatasetGAN: Efficient Labeled Data Factory with Minimal Human Effort

Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentation

Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalization

Spatially Varying Label Smoothing: Capturing Uncertainty from Expert Annotations

Ensemble Learning based on Classifier Prediction Confidence and Comprehensive Learning Particle Swarm Optimisation for polyp localisation

Two layer Ensemble of Deep Learning Models for Medical Image Segmentation

Deep ensembles based on Stochastic Activation Selection for Polyp Segmentation

Pneumothorax Segmentation: Deep Learning Image Segmentation to predict Pneumothorax

Deep Tiered Image Segmentation For Detecting Internal Ice Layers in Radar Imagery

Hierarchical Image Peeling: A Flexible Scale-space Filtering Framework

Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation

MeanShift++: Extremely Fast Mode-Seeking With Applications to Segmentation and Object Tracking

FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation

Topology-Preserving 3D Image Segmentation Based On Hyperelastic Regularization

Task-agnostic Out-of-Distribution Detection Using Kernel Density Estimation

Boundary IoU: Improving Object-Centric Image Segmentation Evaluation

DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation

Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers

DCNAS: Densely Connected Neural Architecture Search for Semantic Image Segmentation

Instance segmentation with the number of clusters incorporated in embedding learning

Learning to Segment from Scribbles using Multi-scale Adversarial Attention Gates

Learning Deformable Image Registration from Optimization: Perspective, Modules, Bilevel Training and Beyond

Test-Time Training for Deformable Multi-Scale Image Registration

Learning Versatile Neural Architectures by Propagating Network Codes

Deep Neural Networks Learn Meta-Structures to Segment Fluorescence Microscopy Images

A Location-Sensitive Local Prototype Network for Few-Shot Medical Image Segmentation

Contrastive Registration for Unsupervised Medical Image Segmentation

Margin Preserving Self-paced Contrastive Learning Towards Domain Adaptation for Medical Image Segmentation

Adapt Everywhere: Unsupervised Adaptation of Point-Clouds and Entropy Minimisation for Multi-modal Cardiac Image Segmentation

Image Segmentation Methods for Non-destructive testing Applications

Towards Learning Food Portion From Monocular Images With Cross-Domain Feature Adaptation

Semi-supervised Learning for Aggregated Multilayer Graphs Using Diffuse Interface Methods and Fast Matrix Vector Products

PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation

FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space

Principal component-based image segmentation: a new approach to outline in vitro cell colonies

Semi-supervised Medical Image Segmentation through Dual-task Consistency

Morphological Operation Residual Blocks: Enhancing 3D Morphological Feature Representation in Convolutional Neural Networks for Semantic Segmentation of Medical Images

CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation

K-means Segmentation Based-on Lab Color Space for Embryo Egg Detection

Unsupervised Domain Adaptation Network with Category-Centric Prototype Aligner for Biomedical Image Segmentation

Uncertainty guided semi-supervised segmentation of retinal layers in OCT images

Generative Synthetic Augmentation using Label-to-Image Translation for Nuclei Image Segmentation

Medical Image Segmentation with Limited Supervision: A Review of Deep Network Models

MixSearch: Searching for Domain Generalized Medical Image Segmentation Architectures

Semantically Meaningful Class Prototype Learning for One-Shot Image Semantic Segmentation

EMDS-5: Environmental Microorganism Image Dataset Fifth Version for Multiple Image Analysis Tasks

Analyzing Overfitting under Class Imbalance in Neural Networks for Image Segmentation

Using the Split Bregman Algorithm to Solve the Self-repelling Snake Model

Image Compositing for Segmentation of Surgical Tools without Manual Annotations

Uncertainty-based method for improving poorly labeled segmentation datasets

L-SNet: from Region Localization to Scale Invariant Medical Image Segmentation

Self-paced and self-consistent co-training for semi-supervised image segmentation

TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

MudrockNet: Semantic Segmentation of Mudrock SEM Images through Deep Learning

Co-Seg: An Image Segmentation Framework Against Label Corruption

Resolution enhancement in the recovery of underdrawings via style transfer by generative adversarial deep neural networks

Utilizing Uncertainty Estimation in Deep Learning Segmentation of Fluorescence Microscopy Images with Missing Markers

Mask-based Data Augmentation for Semi-supervised Semantic Segmentation

Network-Agnostic Knowledge Transfer for Medical Image Segmentation

DSAL: Deeply Supervised Active Learning from Strong and Weak Labelers for Biomedical Image Segmentation

Personal Fixations-Based Object Segmentation with Object Localization and Boundary Preservation

U-Noise: Learnable Noise Masks for Interpretable Image Segmentation

PaddleSeg: A High-Efficient Development Toolkit for Image Segmentation

Affinity Fusion Graph-based Framework for Natural Image Segmentation

Rethinking Interactive Image Segmentation: Feature Space Annotation

Map-Guided Curriculum Domain Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation

Boundary-Aware Geometric Encoding for Semantic Segmentation of Point Clouds

Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentation

Deep Class-Specific Affinity-Guided Convolutional Network for Multimodal Unpaired Image Segmentation

RatLesNetv2: A Fully Convolutional Network for Rodent Brain Lesion Segmentation

ICMSC: Intra- and Cross-modality Semantic Consistency for Unsupervised Domain Adaptation on Hip Joint Bone Segmentation

Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty

DA-RefineNet:A Dual Input Whole Slide Image Segmentation Algorithm Based on Attention

Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation

CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks

Pyramid-Focus-Augmentation: Medical Image Segmentation with Step-Wise Focus

Few-shot Medical Image Segmentation using a Global Correlation Network with Discriminative Embedding

Artist, Style And Year Classification Using Face Recognition And Clustering With Convolutional Neural Networks

Morphological Network: How Far Can We Go with Morphological Neurons?

Towards Robust Medical Image Segmentation on Small-Scale Data with Incomplete Labels

PGL: Prior-Guided Local Self-supervised Learning for 3D Medical Image Segmentation

Multi-feature driven active contour segmentation model for infrared image with intensity inhomogeneity

A comparative study of semi- and self-supervised semantic segmentation of biomedical microscopy data

High-level Prior-based Loss Functions for Medical Image Segmentation: A Survey

Segmentation overlapping wear particles with few labelled data and imbalance sample

DoDNet: Learning to segment multi-organ and tumors from multiple partially labeled datasets

Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation

Dilated Convolutions with Lateral Inhibitions for Semantic Image Segmentation

Enforcing Perceptual Consistency on Generative Adversarial Networks by Using the Normalised Laplacian Pyramid Distance

ROAM: Random Layer Mixup for Semi-Supervised Learning in Medical Imaging

w-Net: Dual Supervised Medical Image Segmentation Model with Multi-Dimensional Attention and Cascade Multi-Scale Convolution

A Simple Probabilistic Method for Deep Classification under Input-Dependent Label Noise

Interpretable and synergistic deep learning for visual explanation and statistical estimations of segmentation of disease features from medical images

Disentangle, align and fuse for multimodal and semi-supervised image segmentation

Global Image Segmentation Process using Machine Learning algorithm & Convolution Neural Network method for Self- Driving Vehicles

Distribution-aware Margin Calibration for Medical Image Segmentation

Recyclable Waste Identification Using CNN Image Recognition and Gaussian Clustering

Contrastive learning of global and local features for medical image segmentation with limited annotations

Volumetric Medical Image Segmentation: A 3D Deep Coarse-to-fine Framework and Its Adversarial Examples

Disentangling Human Error from the Ground Truth in Segmentation of Medical Images

A Teacher-Student Framework for Semi-supervised Medical Image Segmentation From Mixed Supervision

What is Wrong with Continual Learning in Medical Image Segmentation?

Gastric histopathology image segmentation using a hierarchical conditional random field

Weakly-supervised Learning For Catheter Segmentation in 3D Frustum Ultrasound

Human Perception-based Evaluation Criterion for Ultra-high Resolution Cell Membrane Segmentation

HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network

PP-LinkNet: Improving Semantic Segmentation of High Resolution Satellite Imagery with Multi-stage Training

DoFE: Domain-oriented Feature Embedding for Generalizable Fundus Image Segmentation on Unseen Datasets

Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation

MetaBox+: A new Region Based Active Learning Method for Semantic Segmentation using Priority Maps

Depth-wise layering of 3d images using dense depth maps: a threshold based approach

Deep Learning for Earth Image Segmentation based on Imperfect Polyline Labels with Annotation Errors

RefVOS: A Closer Look at Referring Expressions for Video Object Segmentation

Semantic Segmentation With Multi Scale Spatial Attention For Self Driving Cars

Content-based Propagation of User Markings for Interactive Segmentation of Patterned Images

A Survey on Deep Learning Methods for Semantic Image Segmentation in Real-Time

Interactive Learning for Semantic Segmentation in Earth Observation

Segmentations-Leak: Membership Inference Attacks and Defenses in Semantic Image Segmentation

A Topological Loss Function for Deep-Learning based Image Segmentation using Persistent Homology

UXNet: Searching Multi-level Feature Aggregation for 3D Medical Image Segmentation

LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation

Random Style Transfer based Domain Generalization Networks Integrating Shape and Spatial Information

Contour Sparse Representation with SDD Features for Object Recognition

Deep Neural Network for 3D Surface Segmentation based on Contour Tree Hierarchy

Mask-guided sample selection for Semi-Supervised Instance Segmentation

MCU-Net: A framework towards uncertainty representations for decision support system patient referrals in healthcare contexts

Universal Semantic Segmentation for Fisheye Urban Driving Images

PC-U Net: Learning to Jointly Reconstruct and Segment the Cardiac Walls in 3D from CT Data

TapLab: A Fast Framework for Semantic Video Segmentation Tapping into Compressed-Domain Knowledge

Domain Adaptive Medical Image Segmentation via Adversarial Learning of Disease-Specific Spatial Patterns

ATSO: Asynchronous Teacher-Student Optimization for Semi-Supervised Medical Image Segmentation

Polarimetric SAR Image Semantic Segmentation with 3D Discrete Wavelet Transform and Markov Random Field

Uncertainty quantification in medical image segmentation with normalizing flows

State-of-The-Art Fuzzy Active Contour Models for Image Segmentation

Large Scale Image Segmentation with Structured Loss based Deep Learning for Connectome Reconstruction

End-to-End Trainable Deep Active Contour Models for Automated Image Segmentation: Delineating Buildings in Aerial Imagery

Greenhouse Segmentation on High-Resolution Optical Satellite Imagery using Deep Learning Techniques

Globally Optimal Segmentation of Mutually Interacting Surfaces using Deep Learning

Shape-aware Semi-supervised 3D Semantic Segmentation for Medical Images

Unsupervised Learning of Image Segmentation Based on Differentiable Feature Clustering

Superpixel-Guided Label Softening for Medical Image Segmentation

Anisotropic Mesh Adaptation for Image Segmentation Based on Mumford-Shah Functional

An Uncertainty-based Human-in-the-loop System for Industrial Tool Wear Analysis

Tackling the Problem of Limited Data and Annotations in Semantic Segmentation

On uncertainty estimation in active learning for image segmentation

Dual-Teacher: Integrating Intra-domain and Inter-domain Teachers for Annotation-efficient Cardiac Segmentation

Towards Unsupervised Learning for Instrument Segmentation in Robotic Surgery with Cycle-Consistent Adversarial Networks

Superpixel Segmentation using Dynamic and Iterative Spanning Forest

A Multi-scale CNN-CRF Framework for Environmental Microorganism Image Segmentation

Medical Image Segmentation via Unsupervised Convolutional Neural Network

Complex Network Construction for Interactive Image Segmentation using Particle Competition and Cooperation: A New Approach

Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling

Robust Semantic Segmentation in Adverse Weather Conditions by means of Fast Video-Sequence Segmentation

Kullback-Leibler Divergence-Based Fuzzy $C$-Means Clustering Incorporating Morphological Reconstruction and Wavelet Frames for Image Segmentation

Automated Pavement Crack Segmentation Using U-Net-based Convolutional Neural Network

Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation

Interactive Deep Refinement Network for Medical Image Segmentation

Region-of-interest guided Supervoxel Inpainting for Self-supervision

Post-DAE: Anatomically Plausible Segmentation via Post-Processing with Denoising Autoencoders

Large-scale detection and categorization of oil spills from SAR images with deep learning

Road surface detection and differentiation considering surface damages

Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation

Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition

Cross-denoising Network against Corrupted Labels in Medical Image Segmentation with Domain Shift

Learning pose variations within shape population by constrained mixtures of factor analyzers

Multi-organ Segmentation over Partially Labeled Datasets with Multi-scale Feature Abstraction

Bayesian optimization for modular black-box systems with switching costs

Deep Semantic Segmentation of Natural and Medical Images: A Review

Critical Assessment of Transfer Learning for Medical Image Segmentation with Fully Convolutional Neural Networks

Super-BPD: Super Boundary-to-Pixel Direction for Fast Image Segmentation

WaveSNet: Wavelet Integrated Deep Networks for Image Segmentation

Evolution of Image Segmentation using Deep Convolutional Neural Network: A Survey

Deep Learning-Based Automated Image Segmentation for Concrete Petrographic Analysis

Improving Calibration and Out-of-Distribution Detection in Medical Image Segmentation with Convolutional Neural Networks

Traditional Method Inspired Deep Neural Network for Edge Detection

Multi-task deep learning for image segmentation using recursive approximation tasks

Gleason Grading of Histology Prostate Images through Semantic Segmentation via Residual U-Net

Convex Shape Prior for Deep Neural Convolution Network based Eye Fundus Images Segmentation

ECG-DelNet: Delineation of Ambulatory Electrocardiograms with Mixed Quality Labeling Using Neural Networks

Transformation Consistent Self-ensembling Model for Semi-supervised Medical Image Segmentation

SimPropNet: Improved Similarity Propagation for Few-shot Image Segmentation

ACCL: Adversarial constrained-CNN loss for weakly supervised medical image segmentation

Importance Driven Continual Learning for Segmentation Across Domains

A Spatially Constrained Deep Convolutional Neural Network for Nerve Fiber Segmentation in Corneal Confocal Microscopic Images using Inaccurate Annotations

C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation

Color Image Segmentation using Adaptive Particle Swarm Optimization and Fuzzy C-means

A generic ensemble based deep convolutional neural network for semi-supervised medical image segmentation

Generator evaluator-selector net for panoptic image segmentation and splitting unfamiliar objects into parts

Semi-supervised few-shot learning for medical image segmentation

CNN in CT Image Segmentation: Beyound Loss Function for Expoliting Ground Truth Images

Fair Latency-Aware Metric for real-time video segmentation networks

Real-Time High-Performance Semantic Image Segmentation of Urban Street Scenes

C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds

A Fast Fully Octave Convolutional Neural Network for Document Image Segmentation

Automated Design of Deep Learning Methods for Biomedical Image Segmentation

RSS-Net: Weakly-Supervised Multi-Class Semantic Segmentation with FMCW Radar

Improving land cover segmentation across satellites using domain adaptation

BiLingUNet: Image Segmentation by Modulating Top-Down and Bottom-Up Visual Processing with Referring Expressions

Gen-LaneNet: A Generalized and Scalable Approach for 3D Lane Detection

LT-Net: Label Transfer by Learning Reversible Voxel-wise Correspondence for One-shot Medical Image Segmentation

Deep Learning for Automatic Tracking of Tongue Surface in Real-time Ultrasound Videos, Landmarks instead of Contours

EDC3: Ensemble of Deep-Classifiers using Class-specific Copula functions to Improve Semantic Image Segmentation

Deep Learning for Ranking Response Surfaces with Applications to Optimal Stopping Problems

Out-of-Distribution Detection in Multi-Label Datasets using Latent Space of $β$-VAE

PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation

StructBoost: Boosting Methods for Predicting Structured Output Variables

Improving Learning Effectiveness For Object Detection and Classification in Cluttered Backgrounds

Towards Interpretable Semantic Segmentation via Gradient-weighted Class Activation Mapping

Semi-Supervised Semantic Image Segmentation with Self-correcting Networks

MixModule: Mixed CNN Kernel Module for Medical Image Segmentation

A Variational Image Segmentation Model based on Normalized Cut with Adaptive Similarity and Spatial Regularization

3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training

Robust Multimodal Brain Tumor Segmentation via Feature Disentanglement and Gated Fusion

Neural arbitrary style transfer for portrait images using the attention mechanism

Calibrated Surrogate Maximization of Linear-fractional Utility in Binary Classification

Multi-scale self-guided attention for medical image segmentation

Building Networks for Image Segmentation using Particle Competition and Cooperation

Residual-Sparse Fuzzy $C$-Means Clustering Incorporating Morphological Reconstruction and Wavelet frames

Liver Segmentation in Abdominal CT Images via Auto-Context Neural Network and Self-Supervised Contour Attention

Simple Interactive Image Segmentation using Label Propagation through kNN graphs

Constrained Dominant sets and Its applications in computer vision

Deep Convolutional Neural Networks with Spatial Regularization, Volume and Star-shape Priori for Image Segmentation

One-pass Multi-task Networks with Cross-task Guided Attention for Brain Tumor Segmentation

Segmentação de imagens utilizando competição e cooperação entre partículas

Unsupervised Community Detection with a Potts Model Hamiltonian, an Efficient Algorithmic Solution, and Applications in Digital Pathology

Efficient 2D neuron boundary segmentation with local topological constraints

Training Generative Adversarial Networks from Incomplete Observations using Factorised Discriminators

Robust Submodular Minimization with Applications to Cooperative Modeling

Observer variation-aware medical image segmentation by combining deep learning and surrogate-assisted genetic algorithms

Volume Preserving Image Segmentation with Entropic Regularization Optimal Transport and Its Applications in Deep Learning

Hierarchical Modeling of Multidimensional Data in Regularly Decomposed Spaces: Synthesis and Perspective

Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation

Self-Learning AI Framework for Skin Lesion Image Segmentation and Classification

Reducing the Model Variance of a Rectal Cancer Segmentation Network

Generalizing Deep Models for Overhead Image Segmentation Through Getis-Ord Gi* Pooling

Detecting Deepfake-Forged Contents with Separable Convolutional Neural Network and Image Segmentation

What Else Can Fool Deep Learning? Addressing Color Constancy Errors on Deep Neural Network Performance

Computing Valid p-values for Image Segmentation by Selective Inference

End-to-end Training of CNN-CRF via Differentiable Dual-Decomposition

PI-RCNN: An Efficient Multi-sensor 3D Object Detector with Point-based Attentive Cont-conv Fusion Module

End to End Trainable Active Contours via Differentiable Rendering

Transform the Set: Memory Attentive Generation of Guided and Unguided Image Collages

Pixel Level Data Augmentation for Semantic Image Segmentation using Generative Adversarial Networks

Thickened 2D Networks for Efficient 3D Medical Image Segmentation

Identify the cells' nuclei based on the deep learning neural network

An Approach for Adaptive Automatic Threat Recognition Within 3D Computed Tomography Images for Baggage Security Screening

Cost-efficient segmentation of electron microscopy images using active learning

Exploiting Clinically Available Delineations for CNN-based Segmentation in Radiotherapy Treatment Planning

FaultNet: Faulty Rail-Valves Detection using Deep Learning and Computer Vision

One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation

Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory & Practice

Semi-Supervised Medical Image Segmentation via Learning Consistency under Transformations

Gated CRF Loss for Weakly Supervised Semantic Image Segmentation

Domain Generalization via Model-Agnostic Learning of Semantic Features

PT-ResNet: Perspective Transformation-Based Residual Network for Semantic Road Image Segmentation

Deeply Self-Supervised Contour Embedded Neural Network Applied to Liver Segmentation

Encoder-Decoder based CNN and Fully Connected CRFs for Remote Sensed Image Segmentation

'Squeeze & Excite' Guided Few-Shot Segmentation of Volumetric Images

End-to-End Defect Detection in Automated Fiber Placement Based on Artificially Generated Data

Post-mortem Iris Recognition with Deep-Learning-based Image Segmentation

End-to-End Deep Convolutional Active Contours for Image Segmentation

NeurReg: Neural Registration and Its Application to Image Segmentation

Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation

SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth

Biomedical Image Segmentation by Retina-like Sequential Attention Mechanism Using Only A Few Training Images

From Active Contours to Minimal Geodesic Paths: New Solutions to Active Contours Problems by Eikonal Equations

Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation

Spatio-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data

Neural Style Transfer Improves 3D Cardiovascular MR Image Segmentation on Inconsistent Data

Extremely Weak Supervised Image-to-Image Translation for Semantic Segmentation

Risk-Aware Planning by Confidence Estimation using Deep Learning-Based Perception

Phase Collaborative Network for Two-Phase Medical Image Segmentation

Image Segmentation using Multi-Threshold technique by Histogram Sampling

End-to-End Boundary Aware Networks for Medical Image Segmentation

Mumford-Shah Loss Functional for Image Segmentation with Deep Learning

CC-Net: Image Complexity Guided Network Compression for Biomedical Image Segmentation

Automatic Image Pixel Clustering based on Mussels Wandering Optimiz

Extreme Augmentation : Can deep learning based medical image segmentation be trained using a single manually delineated scan?

LadderNet: Multi-path networks based on U-Net for medical image segmentation

ACE-Net: Biomedical Image Segmentation with Augmented Contracting and Expansive Paths

Computing the Spatial Probability of Inclusion inside Partial Contours for Computer Vision Applications

Fine-Grained Segmentation Networks: Self-Supervised Segmentation for Improved Long-Term Visual Localization

Boundary-weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation

SFSegNet: Parse Freehand Sketches using Deep Fully Convolutional Networks

DDSL: Deep Differentiable Simplex Layer for Learning Geometric Signals

Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation

Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentation

The Chan-Vese Model with Elastica and Landmark Constraints for Image Segmentation

SkrGAN: Sketching-rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis

AttentionBoost: Learning What to Attend by Boosting Fully Convolutional Networks

Leveraging Domain Knowledge to Improve Microscopy Image Segmentation with Lifted Multicuts

Massively Parallel Benders Decomposition for Correlation Clustering

A novel framework of the fuzzy c-means distances problem based weighted distance

Deep Learning architectures for generalized immunofluorescence based nuclear image segmentation

Multi-Task Attention-Based Semi-Supervised Learning for Medical Image Segmentation

Pick-and-Learn: Automatic Quality Evaluation for Noisy-Labeled Image Segmentation

Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation

Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentation

DeepAtlas: Joint Semi-Supervised Learning of Image Registration and Segmentation

ET-Net: A Generic Edge-aTtention Guidance Network for Medical Image Segmentation

One-stage Shape Instantiation from a Single 2D Image to 3D Point Cloud

Incremental Class Discovery for Semantic Segmentation with RGBD Sensing

Brain Segmentation from k-space with End-to-end Recurrent Attention Network

Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation

Stereo-based terrain traversability analysis using normal-based segmentation and superpixel surface analysis

Hyperspectral Image Classification with Deep Metric Learning and Conditional Random Field

A Divide-and-Conquer Approach towards Understanding Deep Networks

Automatic 3D bi-ventricular segmentation of cardiac images by a shape-refined multi-task deep learning approach

Deep Active Learning for Axon-Myelin Segmentation on Histology Data

Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction

A General Framework for Complex Network-Based Image Segmentation

Semi-Bagging Based Deep Neural Architecture to Extract Text from High Entropy Images

Consistent estimation of the max-flow problem: Towards unsupervised image segmentation

A Regularized Convolutional Neural Network for Semantic Image Segmentation

Task Decomposition and Synchronization for Semantic Biomedical Image Segmentation

A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation

Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation

From Patch to Image Segmentation using Fully Convolutional Networks -- Application to Retinal Images

A sparse annotation strategy based on attention-guided active learning for 3D medical image segmentation

Scalable Neural Architecture Search for 3D Medical Image Segmentation

When Unseen Domain Generalization is Unnecessary? Rethinking Data Augmentation

PAN: Projective Adversarial Network for Medical Image Segmentation

Semantic-guided Encoder Feature Learning for Blurry Boundary Delineation

MAVNet: an Effective Semantic Segmentation Micro-Network for MAV-based Tasks

Handling Inter-Annotator Agreement for Automated Skin Lesion Segmentation

Learning Shape Representation on Sparse Point Clouds for Volumetric Image Segmentation

VoteNet: A Deep Learning Label Fusion Method for Multi-Atlas Segmentation

A 2D dilated residual U-Net for multi-organ segmentation in thoracic CT

Harvesting Information from Captions for Weakly Supervised Semantic Segmentation

Automated Segmentation of Cervical Nuclei in Pap Smear Images using Deformable Multi-path Ensemble Model

Open Source Presentation Attack Detection Baseline for Iris Recognition

Semantic Segmentation of Video Sequences with Convolutional LSTMs

Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial Attacks

Small Target Detection for Search and Rescue Operations using Distributed Deep Learning and Synthetic Data Generation

Skin Cancer Segmentation and Classification with NABLA-N and Inception Recurrent Residual Convolutional Networks

The iterative convolution-thresholding method (ICTM) for image segmentation

Bidirectional Learning for Domain Adaptation of Semantic Segmentation

XNet: A convolutional neural network (CNN) implementation for medical X-Ray image segmentation suitable for small datasets

A Distance Map Regularized CNN for Cardiac Cine MR Image Segmentation

Road Crack Detection Using Deep Convolutional Neural Network and Adaptive Thresholding

Fast Single Image Dehazing via Multilevel Wavelet Transform based Optimization

Region homogeneity in the Logarithmic Image Processing framework: application to region growing algorithms

Super Resolution Convolutional Neural Network Models for Enhancing Resolution of Rock Micro-CT Images

Adaptive Weighting Multi-Field-of-View CNN for Semantic Segmentation in Pathology

Interactive Full Image Segmentation by Considering All Regions Jointly

3D Quantum Cuts for Automatic Segmentation of Porous Media in Tomography Images

Machine Vision Guided 3D Medical Image Compression for Efficient Transmission and Accurate Segmentation in the Clouds

Adaptive Morphological Reconstruction for Seeded Image Segmentation

Data augmentation using learned transformations for one-shot medical image segmentation

Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation

Deep Convolutional Encoder-Decoders with Aggregated Multi-Resolution Skip Connections for Skin Lesion Segmentation

Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networks

Geometry in Active Learning for Binary and Multi-class Image Segmentation

Graph Cut Segmentation Methods Revisited with a Quantum Algorithm

Feature Fusion Encoder Decoder Network For Automatic Liver Lesion Segmentation

CUSUM Filter for Brain Segmentation on DSC Perfusion MR Head Scans with Abnormal Brain Anatomy

Interactive segmentation of medical images through fully convolutional neural networks

Efficient Smoothing of Dilated Convolutions for Image Segmentation

SuperPatchMatch: an Algorithm for Robust Correspondences using Superpixel Patches

Optimal Transport for Multi-source Domain Adaptation under Target Shift

FreeLabel: A Publicly Available Annotation Tool based on Freehand Traces

Learning-Based Cost Functions for 3D and 4D Multi-Surface Multi-Object Segmentation of Knee MRI: Data from the Osteoarthritis Initiative

Multi-stream 3D FCN with Multi-scale Deep Supervision for Multi-modality Isointense Infant Brain MR Image Segmentation

Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data

CE-Net: Context Encoder Network for 2D Medical Image Segmentation

Mixture Modeling of Global Shape Priors and Autoencoding Local Intensity Priors for Left Atrium Segmentation

The Method of Multimodal MRI Brain Image Segmentation Based on Differential Geometric Features

Fine-Grained Semantic Segmentation of Motion Capture Data using Dilated Temporal Fully-Convolutional Networks

FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference

HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation

SPDA: Superpixel-based Data Augmentation for Biomedical Image Segmentation

Salient object detection on hyperspectral images using features learned from unsupervised segmentation task

Class-independent sequential full image segmentation, using a convolutional net that finds a segment within an attention region, given a pointer pixel within this segment

3D RoI-aware U-Net for Accurate and Efficient Colorectal Tumor Segmentation

Optimal Surface Segmentation with Convex Priors in Irregularly Sampled Space

MultiResUNet : Rethinking the U-Net Architecture for Multimodal Biomedical Image Segmentation

Super-realtime facial landmark detection and shape fitting by deep regression of shape model parameters

FocusNet: An attention-based Fully Convolutional Network for Medical Image Segmentation

Learning Metric Graphs for Neuron Segmentation In Electron Microscopy Images

Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks

Explicit topological priors for deep-learning based image segmentation using persistent homology

Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI

Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study

Joint shape learning and segmentation for medical images using a minimalistic deep network

Unsupervised Automated Event Detection using an Iterative Clustering based Segmentation Approach

UltraCompression: Framework for High Density Compression of Ultrasound Volumes using Physics Modeling Deep Neural Networks

Cascade Decoder: A Universal Decoding Method for Biomedical Image Segmentation

Unsupervised domain adaptation for medical imaging segmentation with self-ensembling

Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples

Image Recognition of Tea Leaf Diseases Based on Convolutional Neural Network

Interactive Image Segmentation using Label Propagation through Complex Networks

Iris Recognition with Image Segmentation Employing Retrained Off-the-Shelf Deep Neural Networks

Impact of Ground Truth Annotation Quality on Performance of Semantic Image Segmentation of Traffic Conditions

Annotation-cost Minimization for Medical Image Segmentation using Suggestive Mixed Supervision Fully Convolutional Networks

Studying the Plasticity in Deep Convolutional Neural Networks using Random Pruning

Holistic Decomposition Convolution for Effective Semantic Segmentation of 3D MR Images

The algorithm of formation of a training set for an artificial neural network for image segmentation

A Gentle Introduction to Deep Learning in Medical Image Processing

Unsupervised Meta-learning of Figure-Ground Segmentation via Imitating Visual Effects

Fast and Accurate 3D Medical Image Segmentation with Data-swapping Method

SwipeCut: Interactive Segmentation with Diversified Seed Proposals

Pixel Objectness: Learning to Segment Generic Objects Automatically in Images and Videos

Accelerated Inference in Markov Random Fields via Smooth Riemannian Optimization

Asymmetric Loss Functions and Deep Densely Connected Networks for Highly Imbalanced Medical Image Segmentation: Application to Multiple Sclerosis Lesion Detection

NFFT meets Krylov methods: Fast matrix-vector products for the graph Laplacian of fully connected networks

Deep Neural Networks Motivated by Partial Differential Equations

A New Ensemble Learning Framework for 3D Biomedical Image Segmentation

Exclusive Independent Probability Estimation using Deep 3D Fully Convolutional DenseNets: Application to IsoIntense Infant Brain MRI Segmentation

Automatically Segmenting the Left Atrium from Cardiac Images Using Successive 3D U-Nets and a Contour Loss

"Double-DIP": Unsupervised Image Decomposition via Coupled Deep-Image-Priors

Enhancing Label-Driven Deep Deformable Image Registration with Local Distance Metrics for State-of-the-Art Cardiac Motion Tracking

MDU-Net: Multi-scale Densely Connected U-Net for biomedical image segmentation

Brain Tumor Segmentation using an Ensemble of 3D U-Nets and Overall Survival Prediction using Radiomic Features

SUSAN: Segment Unannotated image Structure using Adversarial Network

On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent

Foreground Clustering for Joint Segmentation and Localization in Videos and Images

Marginal Weighted Maximum Log-likelihood for Efficient Learning of Perturb-and-Map models

Stack-U-Net: Refinement Network for Image Segmentation on the Example of Optic Disc and Cup

Semi-Supervised Multi-Organ Segmentation via Deep Multi-Planar Co-Training

Automatic Brain Structures Segmentation Using Deep Residual Dilated U-Net

Deep feature transfer between localization and segmentation tasks

Deep Learning Approach for Building Detection in Satellite Multispectral Imagery

RA-UNet: A hybrid deep attention-aware network to extract liver and tumor in CT scans

Novel approach to locate region of interest in mammograms for Breast cancer

Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning

CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation

Fast Graph-Cut Based Optimization for Practical Dense Deformable Registration of Volume Images

Saliency guided deep network for weakly-supervised image segmentation

A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation

A Novel Extension to Fuzzy Connectivity for Body Composition Analysis: Applications in Thigh, Brain, and Whole Body Tissue Segmentation

A Novel Domain Adaptation Framework for Medical Image Segmentation

Image Segmentation using Unsupervised Watershed Algorithm with an Over-segmentation Reduction Technique

Deep Geodesic Learning for Segmentation and Anatomical Landmarking

Dark Model Adaptation: Semantic Image Segmentation from Daytime to Nighttime

A Fully Convolutional Two-Stream Fusion Network for Interactive Image Segmentation

Learning Discriminators as Energy Networks in Adversarial Learning

Deep Learning for End-to-End Atrial Fibrillation Recurrence Estimation

Multi-Level Contextual Network for Biomedical Image Segmentation

Effective Cloud Detection and Segmentation using a Gradient-Based Algorithm for Satellite Imagery; Application to improve PERSIANN-CCS

nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation

Unsupervised Image to Sequence Translation with Canvas-Drawer Networks

3D Segmentation with Exponential Logarithmic Loss for Highly Unbalanced Object Sizes

Mask Editor : an Image Annotation Tool for Image Segmentation Tasks

Searching for Efficient Multi-Scale Architectures for Dense Image Prediction

Unbiasing Semantic Segmentation For Robot Perception using Synthetic Data Feature Transfer

Computation of Total Kidney Volume from CT images in Autosomal Dominant Polycystic Kidney Disease using Multi-Task 3D Convolutional Neural Networks

Retinal Vessel Segmentation under Extreme Low Annotation: A Generative Adversarial Network Approach

Image Segmentation with Pseudo-marginal MCMC Sampling and Nonparametric Shape Priors

Iris Recognition with a Database of Iris Images Obtained in Visible Light Using Smartphone Camera

Understanding Neural Pathways in Zebrafish through Deep Learning and High Resolution Electron Microscope Data

Document Image Classification with Intra-Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks

TreeSegNet: Adaptive Tree CNNs for Subdecimeter Aerial Image Segmentation

Segmentation of Microscopy Data for finding Nuclei in Divergent Images

Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

Multi-level Activation for Segmentation of Hierarchically-nested Classes

Weakly-Supervised Learning-Based Feature Localization in Confocal Laser Endomicroscopy Glioma Images

Holographic Visualisation of Radiology Data and Automated Machine Learning-based Medical Image Segmentation

An Iterative Boundary Random Walks Algorithm for Interactive Image Segmentation

Dilated Convolutions in Neural Networks for Left Atrial Segmentation in 3D Gadolinium Enhanced-MRI

A 3D Coarse-to-Fine Framework for Volumetric Medical Image Segmentation

Neural Multi-Atlas Label Fusion: Application to Cardiac MR Images

A Network Structure to Explicitly Reduce Confusion Errors in Semantic Segmentation

Efficient Yet Deep Convolutional Neural Networks for Semantic Segmentation

A Data-driven Prior on Facet Orientation for Semantic Mesh Labeling

Feature Fusion through Multitask CNN for Large-scale Remote Sensing Image Segmentation

Skin Lesion Segmentation Using Atrous Convolution via DeepLab v3

A post-processing method to improve the white matter hyperintensity segmentation accuracy for randomly-initialized U-net

Segmentation of Drosophila Heart in Optical Coherence Microscopy Images Using Convolutional Neural Networks

Conditional Random Fields as Recurrent Neural Networks for 3D Medical Imaging Segmentation

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

Near Real-time Hippocampus Segmentation Using Patch-based Canonical Neural Network

Learning to Segment Medical Images with Scribble-Supervision Alone

Deep Learning Hyperspectral Image Classification Using Multiple Class-based Denoising Autoencoders, Mixed Pixel Training Augmentation, and Morphological Operations

Efficient identification, localization and quantification of grapevine inflorescences in unprepared field images using Fully Convolutional Networks

Boosted Training of Convolutional Neural Networks for Multi-Class Segmentation

Visual Explanations From Deep 3D Convolutional Neural Networks for Alzheimer's Disease Classification

H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes

SynNet: Structure-Preserving Fully Convolutional Networks for Medical Image Synthesis

Combining Pyramid Pooling and Attention Mechanism for Pelvic MR Image Semantic Segmentaion

Towards safe deep learning: accurately quantifying biomarker uncertainty in neural network predictions

Fully Automatic Myocardial Segmentation of Contrast Echocardiography Sequence Using Random Forests Guided by Shape Model

Unsupervised Cross-Modality Domain Adaptation of ConvNets for Biomedical Image Segmentations with Adversarial Loss

Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data

Kid-Net: Convolution Networks for Kidney Vessels Segmentation from CT-Volumes

CompNet: Complementary Segmentation Network for Brain MRI Extraction

Task Driven Generative Modeling for Unsupervised Domain Adaptation: Application to X-ray Image Segmentation

NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines

Retinal Optic Disc Segmentation using Conditional Generative Adversarial Network

Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks

Contextual Hourglass Networks for Segmentation and Density Estimation

On the Effect of Inter-observer Variability for a Reliable Estimation of Uncertainty of Medical Image Segmentation

Performance Evaluation of Deep Learning Networks for Semantic Segmentation of Traffic Stereo-Pair Images

BoxNet: Deep Learning Based Biomedical Image Segmentation Using Boxes Only Annotation

Learn the new, keep the old: Extending pretrained models with new anatomy and images

Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

Peekaboo - Where are the Objects? Structure Adjusting Superpixels

Semantic Binary Segmentation using Convolutional Networks without Decoders

Complex Relations in a Deep Structured Prediction Model for Fine Image Segmentation

Convexity Shape Prior for Level Set based Image Segmentation Method

Knowledge-based Fully Convolutional Network and Its Application in Segmentation of Lung CT Images

Quickshift++: Provably Good Initializations for Sample-Based Mean Shift

Consensus Based Medical Image Segmentation Using Semi-Supervised Learning And Graph Cuts

Interactive Medical Image Segmentation via Point-Based Interaction and Sequential Patch Learning

On the iterative refinement of densely connected representation levels for semantic segmentation

Hybrid Forests for Left Ventricle Segmentation using only the first slice label

Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs

Stacked U-Nets: A No-Frills Approach to Natural Image Segmentation

Segmentation of Scanning Tunneling Microscopy Images Using Variational Methods and Empirical Wavelets

Matlab Implementation of Machine Vision Algorithm on Ballast Degradation Evaluation

Derivate-based Component-Trees for Multi-Channel Image Segmentation

A Multilinear Tongue Model Derived from Speech Related MRI Data of the Human Vocal Tract

Towards integrating spatial localization in convolutional neural networks for brain image segmentation

Unsupervised Segmentation of 3D Medical Images Based on Clustering and Deep Representation Learning

Unsupervised Pathology Image Segmentation Using Representation Learning with Spherical K-means

Assessment of Breast Cancer Histology using Densely Connected Convolutional Networks

The Lovász-Softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks

Training Multi-organ Segmentation Networks with Sample Selection by Relaxed Upper Confident Bound

Application of Superpixels to Segment Several Landmarks in Running Rodents

Image Segmentation Using Subspace Representation and Sparse Decomposition

A Multi-Layer Approach to Superpixel-based Higher-order Conditional Random Field for Semantic Image Segmentation

Compassionately Conservative Balanced Cuts for Image Segmentation

Ω-Net (Omega-Net): Fully Automatic, Multi-View Cardiac MR Detection, Orientation, and Segmentation with Deep Neural Networks

An application of cascaded 3D fully convolutional networks for medical image segmentation

Adaptive strategy for superpixel-based region-growing image segmentation

Combining Multi-level Contexts of Superpixel using Convolutional Neural Networks to perform Natural Scene Labeling

Quantization of Fully Convolutional Networks for Accurate Biomedical Image Segmentation

Combination of Hidden Markov Random Field and Conjugate Gradient for Brain Image Segmentation

Driving Scene Perception Network: Real-time Joint Detection, Depth Estimation and Semantic Segmentation

IEOPF: An Active Contour Model for Image Segmentation with Inhomogeneities Estimated by Orthogonal Primary Functions

Long-term Visual Localization using Semantically Segmented Images

Simultaneous Traffic Sign Detection and Boundary Estimation using Convolutional Neural Network

Left Ventricle Segmentation in Cardiac MR Images Using Fully Convolutional Network

Computer-Aided Knee Joint Magnetic Resonance Image Segmentation - A Survey

Generative ScatterNet Hybrid Deep Learning (G-SHDL) Network with Structural Priors for Semantic Image Segmentation

Image Inpainting for High-Resolution Textures using CNN Texture Synthesis

Automatic segmenting teeth in X-ray images: Trends, a novel data set, benchmarking and future perspectives

Improved Image Segmentation via Cost Minimization of Multiple Hypotheses

An Iterative Spanning Forest Framework for Superpixel Segmentation

Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans

Self-Learning to Detect and Segment Cysts in Lung CT Images without Manual Annotation

TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation

Fully Convolutional Multi-scale Residual DenseNets for Cardiac Segmentation and Automated Cardiac Diagnosis using Ensemble of Classifiers

A Computer Vision Pipeline for Automated Determination of Cardiac Structure and Function and Detection of Disease by Two-Dimensional Echocardiography

A First Derivative Potts Model for Segmentation and Denoising Using ILP

A fully automated framework for lung tumour detection, segmentation and analysis

Semantic Segmentation via Highly Fused Convolutional Network with Multiple Soft Cost Functions

Automated image segmentation for detecting cell spreading for metastasizing assessments of cancer development

Integrating semi-supervised label propagation and random forests for multi-atlas based hippocampus segmentation

Camera-trap images segmentation using multi-layer robust principal component analysis

Conditional Random Field and Deep Feature Learning for Hyperspectral Image Segmentation

Classification With an Edge: Improving Semantic Image Segmentation with Boundary Detection

Track, then Decide: Category-Agnostic Vision-based Multi-Object Tracking

Image Segmentation to Distinguish Between Overlapping Human Chromosomes

Partial Labeled Gastric Tumor Segmentation via patch-based Reiterative Learning

Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation

A semi-supervised fuzzy GrowCut algorithm to segment and classify regions of interest of mammographic images

Splenomegaly Segmentation using Global Convolutional Kernels and Conditional Generative Adversarial Networks

Automatic Spine Segmentation using Convolutional Neural Network via Redundant Generation of Class Labels for 3D Spine Modeling

Clickstream analysis for crowd-based object segmentation with confidence

Automatic Color Image Segmentation Using a Square Elemental Region-Based Seeded Region Growing and Merging Method

Efficient and Invariant Convolutional Neural Networks for Dense Prediction

Curve-Structure Segmentation from Depth Maps: A CNN-based Approach and Its Application to Exploring Cultural Heritage Objects

Fast Recurrent Fully Convolutional Networks for Direct Perception in Autonomous Driving

DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images

3D Randomized Connection Network with Graph-based Label Inference

A deep learning model integrating FCNNs and CRFs for brain tumor segmentation

Feature Sensitive Label Fusion with Random Walker for Atlas-based Image Segmentation

Medical Image Segmentation Based on Multi-Modal Convolutional Neural Network: Study on Image Fusion Schemes

Segmentation-by-Detection: A Cascade Network for Volumetric Medical Image Segmentation

The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation

A Connection between Feed-Forward Neural Networks and Probabilistic Graphical Models

SEGMENT3D: A Web-based Application for Collaborative Segmentation of 3D images used in the Shoot Apical Meristem

Improved Workflow for Unsupervised Multiphase Image Segmentation

Historical Document Image Segmentation with LDA-Initialized Deep Neural Networks

A Finite Element Computational Framework for Active Contours on Graphs

Interactive Medical Image Segmentation using Deep Learning with Image-specific Fine-tuning

An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation

Texture Fuzzy Segmentation using Skew Divergence Adaptive Affinity Functions

FPGA based Parallelized Architecture of Efficient Graph based Image Segmentation Algorithm

Possibilistic Fuzzy Local Information C-Means for Sonar Image Segmentation

Improving Dermoscopic Image Segmentation with Enhanced Convolutional-Deconvolutional Networks

DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation

UI-Net: Interactive Artificial Neural Networks for Iterative Image Segmentation Based on a User Model

Dynamic Multiscale Tree Learning Using Ensemble Strong Classifiers for Multi-label Segmentation of Medical Images with Lesions

Seeded Laplaican: An Eigenfunction Solution for Scribble Based Interactive Image Segmentation

A Type II Fuzzy Entropy Based Multi-Level Image Thresholding Using Adaptive Plant Propagation Algorithm

Image Segmentation by Iterative Inference from Conditional Score Estimation

Training Group Orthogonal Neural Networks with Privileged Information

Iterative Deep Convolutional Encoder-Decoder Network for Medical Image Segmentation

Slack and Margin Rescaling as Convex Extensions of Supermodular Functions

Importance of Image Enhancement Techniques in Color Image Segmentation: A Comprehensive and Comparative Study

Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs

Automatic Model Based Dataset Generation for Fast and Accurate Crop and Weeds Detection

Towards Instance Segmentation with Object Priority: Prominent Object Detection and Recognition

Line Profile Based Segmentation Algorithm for Touching Corn Kernels

Multi-Planar Deep Segmentation Networks for Cardiac Substructures from MRI and CT

Universal Adversarial Perturbations Against Semantic Image Segmentation

Fashioning with Networks: Neural Style Transfer to Design Clothes

2D-3D Fully Convolutional Neural Networks for Cardiac MR Segmentation

A Novel Approach for Image Segmentation based on Histograms computed from Hue-data

A Locally Adapting Technique for Boundary Detection using Image Segmentation

Fast, Simple Calcium Imaging Segmentation with Fully Convolutional Networks

SegAN: Adversarial Network with Multi-scale $L_1$ Loss for Medical Image Segmentation

Subspace Learning in The Presence of Sparse Structured Outliers and Noise

Adversarial training and dilated convolutions for brain MRI segmentation

On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task

Robust Regression For Image Binarization Under Heavy Noises and Nonuniform Background

Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data

Robust Video-Based Eye Tracking Using Recursive Estimation of Pupil Characteristics

Tversky loss function for image segmentation using 3D fully convolutional deep networks

Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation

$ν$-net: Deep Learning for Generalized Biventricular Cardiac Mass and Function Parameters

Automatic Localization of Deep Stimulation Electrodes Using Trajectory-based Segmentation Approach

A dynamic graph-cuts method with integrated multiple feature maps for segmenting kidneys in ultrasound images

Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks

Optimal Multi-Object Segmentation with Novel Gradient Vector Flow Based Shape Priors

CardiacNET: Segmentation of Left Atrium and Proximal Pulmonary Veins from MRI Using Multi-View CNN

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Convolutional Random Walk Networks for Semantic Image Segmentation

Exploring Context with Deep Structured models for Semantic Segmentation

Convolutional Oriented Boundaries: From Image Segmentation to High-Level Tasks

New region force for variational models in image segmentation and high dimensional data clustering

Deep Learning for Medical Image Processing: Overview, Challenges and Future

Object proposal generation applying the distance dependent Chinese restaurant process

Deep Learning for Multi-Task Medical Image Segmentation in Multiple Modalities

Comparison of Different Methods for Tissue Segmentation in Histopathological Whole-Slide Images

Domain Adaptation for Visual Applications: A Comprehensive Survey

Evaluation of Classifiers for Image Segmentation: Applications for Eucalypt Forest Inventory

Prior-based Hierarchical Segmentation Highlighting Structures of Interest

Perturb-and-MPM: Quantifying Segmentation Uncertainty in Dense Multi-Label CRFs

Label Refinement Network for Coarse-to-Fine Semantic Segmentation

k-Means Clustering and Ensemble of Regressions: An Algorithm for the ISIC 2017 Skin Lesion Segmentation Challenge

Robust and fully automated segmentation of mandible from CT scans

Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation

An Efficient Decomposition Framework for Discriminative Segmentation with Supermodular Losses

An Adversarial Regularisation for Semi-Supervised Training of Structured Output Neural Networks

Learning Multi-level Region Consistency with Dense Multi-label Networks for Semantic Segmentation

Constrained Deep Weak Supervision for Histopathology Image Segmentation

FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics

Efficiently Computing Piecewise Flat Embeddings for Data Clustering and Image Segmentation

Deep Learning and Its Applications to Machine Health Monitoring: A Survey

Segmentation of large images based on super-pixels and community detection in graphs

An Efficient Algorithm for the Piecewise-Smooth Model with Approximately Explicit Solutions

Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes

Fine-grained Recurrent Neural Networks for Automatic Prostate Segmentation in Ultrasound Images

Implicit Modeling -- A Generalization of Discriminative and Generative Approaches

Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs

Efficient Convolutional Neural Network with Binary Quantization Layer

ResFeats: Residual Network Based Features for Image Classification

Scale-constrained Unsupervised Evaluation Method for Multi-scale Image Segmentation

MCMC Shape Sampling for Image Segmentation with Nonparametric Shape Priors

Icon: An Interactive Approach to Train Deep Neural Networks for Segmentation of Neuronal Structures

A Model of Virtual Carrier Immigration in Digital Images for Region Segmentation

Natural Scene Image Segmentation Based on Multi-Layer Feature Extraction

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Image Segmentation Based on the Self-Balancing Mechanism in Virtual 3D Elastic Mesh

Convex Histogram-Based Joint Image Segmentation with Regularized Optimal Transport Cost

Active Mean Fields for Probabilistic Image Segmentation: Connections with Chan-Vese and Rudin-Osher-Fatemi Models

Towards the effectiveness of Deep Convolutional Neural Network based Fast Random Forest Classifier

Interactive Image Segmentation From A Feedback Control Perspective

The Importance of Skip Connections in Biomedical Image Segmentation

Automated Segmentation of Retinal Layers from Optical Coherent Tomography Images Using Geodesic Distance

Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation

Image segmentation based on histogram of depth and an application in driver distraction detection

Utilizing Large Scale Vision and Text Datasets for Image Segmentation from Referring Expressions

A 4D Light-Field Dataset and CNN Architectures for Material Recognition

VoxResNet: Deep Voxelwise Residual Networks for Volumetric Brain Segmentation

Play and Learn: Using Video Games to Train Computer Vision Models

SSHMT: Semi-supervised Hierarchical Merge Tree for Electron Microscopy Image Segmentation

An efficient iterative thresholding method for image segmentation

Gaze2Segment: A Pilot Study for Integrating Eye-Tracking Technology into Medical Image Segmentation

A combined Approach Based on Fuzzy Classification and Contextual Region Growing to Image Segmentation

Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation

Screen Content Image Segmentation Using Sparse Decomposition and Total Variation Minimization

Adaptable Precomputation for Random Walker Image Segmentation and Registration

Screen Content Image Segmentation Using Robust Regression and Sparse Decomposition

Incorporating prior knowledge in medical image segmentation: a survey

Can we unify monocular detectors for autonomous driving by using the pixel-wise semantic segmentation of CNNs?

Disjunctive Normal Level Set: An Efficient Parametric Implicit Method

Detection and Tracking of Liquids with Fully Convolutional Networks

V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

Color-based Segmentation of Sky/Cloud Images From Ground-based Cameras

Deep Learning Convolutional Networks for Multiphoton Microscopy Vasculature Segmentation

DeepSaliency: Multi-Task Deep Neural Network Model for Salient Object Detection

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Efficient piecewise training of deep structured models for semantic segmentation

Better Image Segmentation by Exploiting Dense Semantic Predictions

An Interactive Medical Image Segmentation Framework Using Iterative Refinement

Unsupervised Image Segmentation using the Deffuant-Weisbuch Model from Social Dynamics

Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform

The use of deep learning in image segmentation, classification and detection

Jansen-MIDAS: a multi-level photomicrograph segmentation software based on isotropic undecimated wavelets

A Formal Evaluation of PSNR as Quality Measurement Parameter for Image Segmentation Algorithms

Bridging Category-level and Instance-level Semantic Image Segmentation

Bacterial foraging optimization based brain magnetic resonance image segmentation

Image segmentation with superpixel-based covariance descriptors in low-rank representation

Fast Semantic Image Segmentation with High Order Context and Guided Filtering

Fuzzy Clustering Based Segmentation Of Vertebrae in T1-Weighted Spinal MR Images

On Image segmentation using Fractional Gradients-Learning Model Parameters using Approximate Marginal Inference

Joint Segmentation and Deconvolution of Ultrasound Images Using a Hierarchical Bayesian Model based on Generalized Gaussian Priors

Large-scale Binary Quadratic Optimization Using Semidefinite Relaxation and Applications

A Classifier-guided Approach for Top-down Salient Object Detection

ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation

High-performance Semantic Segmentation Using Very Deep Fully Convolutional Networks

Affinity CNN: Learning Pixel-Centric Pairwise Relations for Figure/Ground Embedding

Fully-Automatic Synapse Prediction and Validation on a Large Data Set

Image segmentation of cross-country scenes captured in IR spectrum

Voronoi Region-Based Adaptive Unsupervised Color Image Segmentation

Variational reaction-diffusion systems for semantic segmentation

Kernelized Weighted SUSAN based Fuzzy C-Means Clustering for Noisy Image Segmentation

Robust cDNA microarray image segmentation and analysis technique based on Hough circle transform

A regularization-based approach for unsupervised image segmentation

A hybrid approach based segmentation technique for brain tumor in MRI Images

Integrated Inference and Learning of Neural Factors in Structural Support Vector Machines

Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation

Generating Discriminative Object Proposals via Submodular Ranking

Disaggregation of SMAP L3 Brightness Temperatures to 9km using Kernel Machines

Bayesian nonparametric image segmentation using a generalized Swendsen-Wang algorithm

On distances, paths and connections for hyperspectral image segmentation

Context Driven Label Fusion for segmentation of Subcutaneous and Visceral Fat in CT Volumes

A Parallel Framework for Parametric Maximum Flow Problems in Image Segmentation

Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks

Learning High-level Prior with Convolutional Neural Networks for Semantic Segmentation

LooseCut: Interactive Image Segmentation with Loosely Bounded Boxes

Screen Content Image Segmentation Using Sparse-Smooth Decomposition

TransCut: Transparent Object Segmentation from a Light-Field Image

Regional Active Contours based on Variational level sets and Machine Learning for Image Segmentation

A Markov Random Field and Active Contour Image Segmentation Model for Animal Spots Patterns

Constrained Convolutional Neural Networks for Weakly Supervised Segmentation

Shape Complexes in Continuous Max-Flow Hierarchical Multi-Labeling Problems

Multi-Region Probabilistic Dice Similarity Coefficient using the Aitchison Distance and Bipartite Graph Matching

Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation

Joint Color-Spatial-Directional clustering and Region Merging (JCSD-RM) for unsupervised RGB-D image segmentation

Action recognition in still images by latent superpixel classification

Beyond Semantic Image Segmentation : Exploring Efficient Inference in Video

Forming A Random Field via Stochastic Cliques: From Random Graphs to Fully Connected Random Fields

Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation

Point-wise Map Recovery and Refinement from Functional Correspondence

Comparing the Performance of L*A*B* and HSV Color Spaces with Respect to Color Image Segmentation

A deep-structured fully-connected random field model for structured inference

PISA: Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures with Edge-Preserving Coherence

Deep Learning for Object Saliency Detection and Image Segmentation

Image Segmentation by Size-Dependent Single Linkage Clustering of a Watershed Basin Graph

Segmentation and Restoration of Images on Surfaces by Parametric Active Contours with Topology Changes

Identifying Reliable Annotations for Large Scale Image Segmentation

Image Segmentation and Restoration Using Parametric Contours With Free Endpoints

SegSALSA-STR: A convex formulation to supervised hyperspectral image segmentation using hidden fields and structure tensor regularization

DeepEdge: A Multi-Scale Bifurcated Deep Network for Top-Down Contour Detection

Convex Color Image Segmentation with Optimal Transport Distances

Image Segmentation in Liquid Argon Time Projection Chamber Detector

Shannon, Tsallis and Kaniadakis entropies in bi-level image thresholding

Bi-Level Image Thresholding obtained by means of Kaniadakis Entropy

Screen Content Image Segmentation Using Least Absolute Deviation Fitting

Fusion of Image Segmentation Algorithms using Consensus Clustering

Beyond Pixels: A Comprehensive Survey from Bottom-up to Semantic Image Segmentation and Cosegmentation

Parametric Image Segmentation of Humans with Structural Shape Priors

Unsupervised image segmentation by Global and local Criteria Optimization Based on Bayesian Networks

Handwritten Devanagari Script Segmentation: A non-linear Fuzzy Approach

Meaningful Objects Segmentation from SAR Images via A Multi-Scale Non-Local Active Contour Model

Filter Design and Performance Evaluation for Fingerprint Image Segmentation

Inverse Renormalization Group Transformation in Bayesian Image Segmentations

Globally Optimal Joint Image Segmentation and Shape Matching Based on Wasserstein Modes

Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification

An Automatic Seeded Region Growing for 2D Biomedical Image Segmentation

Application of the Ring Theory in the Segmentation of Digital Images

A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm for Training Structural SVMs with a Costly max-Oracle

An Unsupervised Ensemble-based Markov Random Field Approach to Microscope Cell Image Segmentation

Salient Object Detection: A Discriminative Regional Feature Integration Approach

Quantum Edge Detection for Image Segmentation in Optical Environments

Identifying Synapses Using Deep and Wide Multiscale Recursive Networks

GIMP and Wavelets for Medical Image Processing: Enhancing Images of the Fundus of the Eye

Bayesian image segmentations by Potts prior and loopy belief propagation

Real-Time and Robust Method for Hand Gesture Recognition System Based on Cross-Correlation Coefficient

Clustering Approach Towards Image Segmentation: An Analytical Study

An Enhancement Neighborhood connected Segmentation for 2D-Cellular Image

Near-optimal Keypoint Sampling for Fast Pathological Lung Segmentation

CIDI-Lung-Seg: A Single-Click Annotation Tool for Automatic Delineation of Lungs from CT Scans

A Statistical Modeling Approach to Computer-Aided Quantification of Dental Biofilm

Support vector machine classification of dimensionally reduced structural MRI images for dementia

A multilevel thresholding algorithm using Electromagnetism Optimization

Incorporating Near-Infrared Information into Semantic Image Segmentation

Multi-utility Learning: Structured-output Learning with Multiple Annotation-specific Loss Functions

A Comparison of Nature Inspired Algorithms for Multi-threshold Image Segmentation

Seeking multi-thresholds for image segmentation with Learning Automata

A Multi-threshold Segmentation Approach Based on Artificial Bee Colony Optimization

Image Segmentation Using Frequency Locking of Coupled Oscillators

Variational Image Segmentation Model Coupled with Image Restoration Achievements

Texture Based Image Segmentation of Chili Pepper X-Ray Images Using Gabor Filter

Closed-Form Training of Conditional Random Fields for Large Scale Image Segmentation

A Tiered Move-making Algorithm for General Non-submodular Pairwise Energies

Brain Tumor Detection Based On Mathematical Analysis and Symmetry Information

Spectral Clustering with Jensen-type kernels and their multi-point extensions

Particle methods enable fast and simple approximation of Sobolev gradients in image segmentation

Automatic Estimation of Live Coffee Leaf Infection based on Image Processing Techniques

An Estimation Method of Measuring Image Quality for Compressed Images of Human Face

Study of Efficient Technique Based On 2D Tsallis Entropy For Image Thresholding

A parameterless scale-space approach to find meaningful modes in histograms - Application to image and spectrum segmentation

Clustering using Vector Membership: An Extension of the Fuzzy C-Means Algorithm

Fast image segmentation and restoration using parametric curve evolution with junctions and topology changes

Multi-dimensional Parametric Mincuts for Constrained MAP Inference

Accuracy of MAP segmentation with hidden Potts and Markov mesh prior models via Path Constrained Viterbi Training, Iterated Conditional Modes and Graph Cut based algorithms

Multilevel Threshold Based Gray Scale Image Segmentation using Cuckoo Search

Image segmentation by optimal and hierarchical piecewise constant approximations

A Local Active Contour Model for Image Segmentation with Intensity Inhomogeneity

A Contrario Selection of Optimal Partitions for Image Segmentation

Hybridization of Otsu Method and Median Filter for Color Image Segmentation

A Fast Semidefinite Approach to Solving Binary Quadratic Problems

A Robust Rapid Approach to Image Segmentation with Optimal Thresholding and Watershed Transform

Spatial Fuzzy C Means PET Image Segmentation of Neurodegenerative Disorder

Automatic symmetry based cluster approach for anomalous brain identification in PET scan image : An Analysis

Iterative graph cuts for image segmentation with a nonlinear statistical shape prior

A Fast Learning Algorithm for Image Segmentation with Max-Pooling Convolutional Networks

Hybrid Image Segmentation using Discerner Cluster in FCM and Histogram Thresholding

Penalty Constraints and Kernelization of M-Estimation Based Fuzzy C-Means

GMM-Based Hidden Markov Random Field for Color Image and 3D Volume Segmentation

HMRF-EM-image: Implementation of the Hidden Markov Random Field Model and its Expectation-Maximization Algorithm

Artificial Neural Network Fuzzy Inference System (ANFIS) For Brain Tumor Detection

Segmentation of ultrasound images of thyroid nodule for assisting fine needle aspiration cytology

Resolution Enhancement of Range Images via Color-Image Segmentation

Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials

Enhanced Techniques for PDF Image Segmentation and Text Extraction

Multisegmentation through wavelets: Comparing the efficacy of Daubechies vs Coiflets

Polarimetric SAR Image Segmentation with B-Splines and a New Statistical Model

Efficient Structured Prediction with Latent Variables for General Graphical Models

Dirichlet Process with Mixed Random Measures: A Nonparametric Topic Model for Labeled Data

An Unsupervised Dynamic Image Segmentation using Fuzzy Hopfield Neural Network based Genetic Algorithm

A Simple Unsupervised Color Image Segmentation Method based on MRF-MAP

Non-parametric convolution based image-segmentation of ill-posed objects applying context window approach

The watershed concept and its use in segmentation : a brief history

Conjugate Variables as a Resource in Signal and Image Processing

A Novel Image Segmentation Enhancement Technique based on Active Contour and Topological Alignments

A linear framework for region-based image segmentation and inpainting involving curvature penalization

Visual-hint Boundary to Segment Algorithm for Image Segmentation

Image Segmentation by Discounted Cumulative Ranking on Maximal Cliques

Comparative Study of Statistical Skin Detection Algorithms for Sub-Continental Human Images

Multi-environment model estimation for motility analysis of Caenorhabditis Elegans

A New Approach to Lung Image Segmentation using Fuzzy Possibilistic C-Means Algorithm

A Robust Fuzzy Clustering Technique with Spatial Neighborhood Information for Effective Medical Image Segmentation

Plugin procedure in segmentation and application to hyperspectral image segmentation

The Influence of Intensity Standardization on Medical Image Registration

Threshold Based Indexing of Commercial Shoe Print to Create Reference and Recovery Images

Gradient Based Seeded Region Grow method for CT Angiographic Image Segmentation

A Topological derivative based image segmentation for sign language recognition system using isotropic filter

Scale-Based Gaussian Coverings: Combining Intra and Inter Mixture Models in Image Segmentation

Physical Modeling Techniques in Active Contours for Image Segmentation

Automatic Spatially-Adaptive Balancing of Energy Terms for Image Segmentation

Polynomial time algorithms for bi-criteria, multi-objective and ratio problems in clustering and imaging. Part I: Normalized cut and ratio regions

A Fast Hierarchical Multilevel Image Segmentation Method using Unbiased Estimators

Colour image segmentation by the vector-valued Allen-Cahn phase-field model: a multigrid solution

Bandwidth selection for kernel estimation in mixed multi-dimensional spaces

Medical Image Segmentation and Localization using Deformable Templates

Multilevel Thresholding for Image Segmentation through a Fast Statistical Recursive Algorithm

Paving the Way for Image Understanding: A New Kind of Image Decomposition is Desired

Gradient Vector Flow Models for Boundary Extraction in 2D Images

Field geology with a wearable computer: 1st results of the Cyborg Astrobiologist System

Top-Down Unsupervised Image Segmentation (it sounds like oxymoron, but actually it is not)

Field Geology with a Wearable Computer: First Results of the Cyborg Astrobiologist System

Neural Knitworks: Patched Neural Implicit Representation Networks

Multi-way Clustering and Discordance Analysis through Deep Collective Matrix Tri-Factorization

How much "human-like" visual experience do current self-supervised learning algorithms need to achieve human-level object recognition?

Experience feedback using Representation Learning for Few-Shot Object Detection on Aerial Images

A Survey on Graph-Based Deep Learning for Computational Histopathology

Self-Supervised Video Representation Learning by Video Incoherence Detection

Discovering Novel Customer Features with Recurrent Neural Networks for Personality Based Financial Services

Holistic Semi-Supervised Approaches for EEG Representation Learning

GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction

Dual-Neighborhood Deep Fusion Network for Point Cloud Classification

Long Short View Feature Decomposition via Contrastive Video Representation Learning

Multimodal Representation Learning via Maximization of Local Mutual Information

Automated Feature-Topic Pairing: Aligning Semantic and Embedding Spaces in Spatial Representation Learning

Parameter Efficient Multimodal Transformers for Video Representation Learning

Deep Variational Clustering Framework for Self-labeling of Large-scale Medical Images

Mask Guided Attention For Fine-Grained Patchy Image Classification

The Curse Revisited: a Newly Quantified Concept of Meaningful Distances for Learning from High-Dimensional Noisy Data

KD-VLP: Improving End-to-End Vision-and-Language Pretraining with Object Knowledge Distillation

DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network Data

AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators

Quantifying and Mitigating Privacy Risks of Contrastive Learning

Interest-oriented Universal User Representation via Contrastive Learning

AGRNet: Adaptive Graph Representation Learning and Reasoning for Face Parsing

Semi-Supervised Visual Representation Learning for Fashion Compatibility

A Tutorial on Learning Disentangled Representations in the Imaging Domain

Dense Semantic Contrast for Self-Supervised Visual Representation Learning

Graph Embedding via Diffusion-Wavelets-Based Node Feature Distribution Characterization

VR3Dense: Voxel Representation Learning for 3D Object Detection and Monocular Dense Depth Reconstruction

Network representation learning systematic review: ancestors and current development state

Online Unsupervised Learning of Visual Representations and Categories

Constructing Phrase-level Semantic Labels to Form Multi-Grained Supervision for Image-Text Retrieval

Learning Statistical Representation with Joint Deep Embedded Clustering

Fundamental Limits and Tradeoffs in Invariant Representation Learning

Preservational Learning Improves Self-supervised Medical Image Models by Reconstructing Diverse Contexts

Position-based Hash Embeddings For Scaling Graph Neural Networks

Self-Supervised 3D Hand Pose Estimation from monocular RGB via Contrastive Learning

Graph-MVP: Multi-View Prototypical Contrastive Learning for Multiplex Graphs

On the Fundamental Trade-offs in Learning Invariant Representations

Knowledge Distillation Using Hierarchical Self-Supervision Augmented Distribution

Dual-constrained Deep Semi-Supervised Coupled Factorization Network with Enriched Prior

Learning from Self-Discrepancy via Multiple Co-teaching for Cross-Domain Person Re-Identification

Pointspectrum: Equivariance Meets Laplacian Filtering for Graph Representation Learning

Information Theory-Guided Heuristic Progressive Multi-View Coding

Improving Joint Learning of Chest X-Ray and Radiology Report by Word Region Alignment

LAViTeR: Learning Aligned Visual and Textual Representations Assisted by Image and Caption Generation

Barycenteric distribution alignment and manifold-restricted invertibility for domain generalization

On robustness of generative representations against catastrophic forgetting

Multi-modal Representation Learning for Video Advertisement Content Structuring

Dual Transfer Learning for Event-based End-task Prediction via Pluggable Event to Image Translation

Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic Systems

USCL: Pretraining Deep Ultrasound Image Diagnosis Model through Video Contrastive Representation Learning

Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds

Contrastive Multiview Coding with Electro-optics for SAR Semantic Segmentation

Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning

A manifold learning perspective on representation learning: Learning decoder and representations without an encoder

Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks

Heterogeneous Graph Neural Network with Multi-view Representation Learning

Triplet is All You Need with Random Mappings for Unsupervised Visual Representation Learning

Font Completion and Manipulation by Cycling Between Multi-Modality Representations

Self-Contrastive Learning with Hard Negative Sampling for Self-supervised Point Cloud Learning

Calibrating Class Activation Maps for Long-Tailed Visual Recognition

Deep Dive into Semi-Supervised ELBO for Improving Classification Performance

Rethinking Sampling Strategies for Unsupervised Person Re-identification

Graph Constrained Data Representation Learning for Human Motion Segmentation

Graph-based Incident Aggregation for Large-Scale Online Service Systems

MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving

Drop-DTW: Aligning Common Signal Between Sequences While Dropping Outliers

q-VAE for Disentangled Representation Learning and Latent Dynamical Systems

SparseConvMIL: Sparse Convolutional Context-Aware Multiple Instance Learning for Whole Slide Image Classification

About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data Annotations

Temporal Graph Network Embedding with Causal Anonymous Walks Representations

Temporal Knowledge Consistency for Unsupervised Visual Representation Learning

Tax Evasion Risk Management Using a Hybrid Unsupervised Outlier Detection Method

Self-Supervised Video Representation Learning with Meta-Contrastive Network

TACo: Token-aware Cascade Contrastive Learning for Video-Text Alignment

Exploiting Shared Representations for Personalized Federated Learning

TARA: Training and Representation Alteration for AI Fairness and Domain Generalization

Geometry-Aware Self-Training for Unsupervised Domain Adaptationon Object Point Clouds

Composable Augmentation Encoding for Video Representation Learning

Category-Level 6D Object Pose Estimation via Cascaded Relation and Recurrent Reconstruction Networks

Batch Curation for Unsupervised Contrastive Representation Learning

Contrasting Contrastive Self-Supervised Representation Learning Pipelines

ICE: Inter-instance Contrastive Encoding for Unsupervised Person Re-identification

MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3D CT Lesions

A New Bidirectional Unsupervised Domain Adaptation Segmentation Framework

Self-Supervised Visual Representations Learning by Contrastive Mask Prediction

ASCNet: Self-supervised Video Representation Learning with Appearance-Speed Consistency

Enhancing Self-supervised Video Representation Learning via Multi-level Feature Optimization

DSANet: Dynamic Segment Aggregation Network for Video-Level Representation Learning

Learning by Aligning: Visible-Infrared Person Re-identification using Cross-Modal Correspondences

ACAV100M: Automatic Curation of Large-Scale Datasets for Audio-Visual Video Representation Learning

Clustering augmented Self-Supervised Learning: Anapplication to Land Cover Mapping

Towards Discriminative Representation Learning for Unsupervised Person Re-identification

Efficient Feature Representations for Cricket Data Analysis using Deep Learning based Multi-Modal Fusion Model

Solo-learn: A Library of Self-supervised Methods for Visual Representation Learning

A Broad Study on the Transferability of Visual Representations with Contrastive Learning

Unsupervised Disentanglement without Autoencoding: Pitfalls and Future Directions

Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimization

Billion-Scale Pretraining with Vision Transformers for Multi-Task Visual Representations

Towards Interpretable Deep Networks for Monocular Depth Estimation

DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features

Representation Learning for Remote Sensing: An Unsupervised Sensor Fusion Approach

Learning Deep Multimodal Feature Representation with Asymmetric Multi-layer Fusion

DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning

Skeleton Cloud Colorization for Unsupervised 3D Action Representation Learning

OVIS: Open-Vocabulary Visual Instance Search via Visual-Semantic Aligned Representation Learning

Unifying Heterogenous Electronic Health Records Systems via Text-Based Code Embedding

Contrastive Representation Learning for Rapid Intraoperative Diagnosis of Skull Base Tumors Imaged Using Stimulated Raman Histology

Missing Data Estimation in Temporal Multilayer Position-aware Graph Neural Network (TMP-GNN)

Hand-Based Person Identification using Global and Part-Aware Deep Feature Representation Learning

Adaptive Normalized Representation Learning for Generalizable Face Anti-Spoofing

Security and Privacy Enhanced Gait Authentication with Random Representation Learning and Digital Lockers

CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation

Semi-weakly Supervised Contrastive Representation Learning for Retinal Fundus Images

Point Discriminative Learning for Unsupervised Representation Learning on 3D Point Clouds

Spectral Graph Convolutional Networks With Lifting-based Adaptive Graph Wavelets

Approximating Attributed Incentive Salience In Large Scale Scenarios. A Representation Learning Approach Based on Artificial Neural Networks

MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal

Self-supervised Audiovisual Representation Learning for Remote Sensing Data

Congested Crowd Instance Localization with Dilated Convolutional Swin Transformer

Fair Representation Learning using Interpolation Enabled Disentanglement

Unsupervised Cross-Modal Distillation for Thermal Infrared Tracking

Learning Instance-level Spatial-Temporal Patterns for Person Re-identification

Object-aware Contrastive Learning for Debiased Scene Representation

Alleviate Representation Overlapping in Class Incremental Learning by Contrastive Class Concentration

Learning Geometry-Guided Depth via Projective Modeling for Monocular 3D Object Detection

Deep Recurrent Semi-Supervised EEG Representation Learning for Emotion Recognition

Learning Attributed Graph Representations with Communicative Message Passing Transformer

Adversarial Stacked Auto-Encoders for Fair Representation Learning

Discriminative-Generative Representation Learning for One-Class Anomaly Detection

Invariant Representation Learning for Treatment Effect Estimation

Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning

Local2Global: Scaling global representation learning on graphs via local training

Visual Representation Learning Does Not Generalize Strongly Within the Same Domain

RewriteNet: Realistic Scene Text Image Generation via Editing Text in Real-world Image

Data Considerations in Graph Representation Learning for Supply Chain Networks

Multimodal Representations Learning and Adversarial Hypergraph Fusion for Early Alzheimer's Disease Prediction

MG-NET: Leveraging Pseudo-Imaging for Multi-Modal Metagenome Analysis

Large-scale graph representation learning with very deep GNNs and self-supervision

Learning a Sensor-invariant Embedding of Satellite Data: A Case Study for Lake Ice Monitoring

CETransformer: Casual Effect Estimation via Transformer Based Representation Learning

Exploring Set Similarity for Dense Self-supervised Representation Learning

Self-Supervised Graph Learning with Proximity-based Views and Channel Contrast

Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal Inference

All the attention you need: Global-local, spatial-channel attention for image retrieval

Class-Agnostic Segmentation Loss and Its Application to Salient Object Detection and Segmentation

Align before Fuse: Vision and Language Representation Learning with Momentum Distillation

MultiBench: Multiscale Benchmarks for Multimodal Representation Learning

Learn from Anywhere: Rethinking Generalized Zero-Shot Learning with Limited Supervision

Domain-Irrelevant Representation Learning for Unsupervised Domain Generalization

Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations

NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale

Generalizing to Unseen Domains: A Survey on Domain Generalization

Exploring intermediate representation for monocular vehicle pose estimation

Geographical Knowledge-driven Representation Learning for Remote Sensing Images

InfoVAEGAN : learning joint interpretable representations by information maximization and maximum likelihood

Autoencoder-driven Spiral Representation Learning for Gravitational Wave Surrogate Modelling

Object-Centric Representation Learning for Video Question Answering

Neural Mixture Models with Expectation-Maximization for End-to-end Deep Clustering

Size-Invariant Graph Representations for Graph Classification Extrapolations

Semi-TCL: Semi-Supervised Track Contrastive Representation Learning

Learning Disentangled Representation Implicitly via Transformer for Occluded Person Re-Identification

An Ensemble Noise-Robust K-fold Cross-Validation Selection Method for Noisy Labels

Learning Domain Invariant Representations for Generalizable Person Re-Identification

A Self-Supervised Gait Encoding Approach with Locality-Awareness for 3D Skeleton Based Person Re-Identification

How Incomplete is Contrastive Learning? An Inter-intra Variant Dual Representation Method for Self-supervised Video Recognition

Autoencoding Slow Representations for Semi-supervised Data Efficient Regression

Structure by Architecture: Disentangled Representations without Regularization

Unsupervised Activity Segmentation by Joint Representation Learning and Online Clustering

Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspective

BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly Detection

SPI-GAN: Towards Single-Pixel Imaging through Generative Adversarial Network

Blind Image Super-Resolution via Contrastive Representation Learning

Generalization and Robustness Implications in Object-Centric Learning

Deep auxiliary learning for visual localization using colorization task

Graph Self Supervised Learning: the BT, the HSIC, and the VICReg

Color Variants Identification in Fashion e-commerce via Contrastive Self-Supervised Representation Learning

Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images

A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning

Contrastive Semantic Similarity Learning for Image Captioning Evaluation with Intrinsic Auto-encoder

Open-Set Representation Learning through Combinatorial Embedding

Generating the Graph Gestalt: Kernel-Regularized Graph Representation Learning

Benchmarking Unsupervised Object Representations for Video Sequences

Contrastive Attraction and Contrastive Repulsion for Representation Learning

Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis

Improving Prediction of Low-Prior Clinical Events with Simultaneous General Patient-State Representation Learning

Understanding Dynamics of Nonlinear Representation Learning and Its Application

A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning

Interpretable Network Representation Learning with Principal Component Analysis

Learning to Amend Facial Expression Representation via De-albino and Affinity

Decomposed Mutual Information Estimation for Contrastive Representation Learning

Unsupervised Learning of Depth and Depth-of-Field Effect from Natural Images with Aperture Rendering Generative Adversarial Networks

Winner Team Mia at TextVQA Challenge 2021: Vision-and-Language Representation Learning with Pre-trained Sequence-to-Sequence Model

Transformer-based unsupervised patient representation learning based on medical claims for risk stratification and analysis

From Canonical Correlation Analysis to Self-supervised Graph Neural Networks

Bootstrap Representation Learning for Segmentation on Medical Volumes and Sequences

Unsupervised Object-Level Representation Learning from Scene Images

Towards Solving Inefficiency of Self-supervised Representation Learning

Give Me Your Trained Model: Domain Adaptive Semantic Segmentation without Source Data

Multi-layered Semantic Representation Network for Multi-label Image Classification

ConvDySAT: Deep Neural Representation Learning on Dynamic Graphs via Self-Attention and Convolutional Neural Networks

TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?

TCIC: Theme Concepts Learning Cross Language and Vision for Image Captioning

Crop-Transform-Paste: Self-Supervised Learning for Visual Tracking

DiGS : Divergence guided shape implicit neural representation for unoriented point clouds

Radar Camera Fusion via Representation Learning in Autonomous Driving

Graph Context Encoder: Graph Feature Inpainting for Graph Generation and Self-supervised Pretraining

Equivariance-bridged SO(2)-Invariant Representation Learning using Graph Convolutional Network

Investigating the Role of Negatives in Contrastive Representation Learning

Message Passing in Graph Convolution Networks via Adaptive Filter Banks

Efficient Self-supervised Vision Transformers for Representation Learning

MoDist: Motion Distillation for Self-supervised Video Representation Learning

Latent Correlation-Based Multiview Learning and Self-Supervision: A Unifying Perspective

Unsupervised Path Representation Learning with Curriculum Negative Sampling

MHNF: Multi-hop Heterogeneous Neighborhood information Fusion graph representation learning

Towards a Unified Framework for Fair and Stable Graph Representation Learning

Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease

Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction

Watching Too Much Television is Good: Self-Supervised Audio-Visual Representation Learning from Movies and TV Shows

Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness

Multivariate Business Process Representation Learning utilizing Gramian Angular Fields and Convolutional Neural Networks

End-to-End Learning of Keypoint Representations for Continuous Control from Images

Capsule Attention for Multimodal EEG-EOG Representation Learning with Application to Driver Vigilance Estimation

Cross-Modal Attention Consistency for Video-Audio Unsupervised Learning

Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement

Graph Inference Representation: Learning Graph Positional Embeddings with Anchor Path Encoding

Provable Adaptation across Multiway Domains via Representation Learning

Robust Representation Learning via Perceptual Similarity Metrics

Asymptotics of representation learning in finite Bayesian neural networks

A Framework to Enhance Generalization of Deep Metric Learning methods using General Discriminative Feature Learning and Class Adversarial Neural Networks

AugNet: End-to-End Unsupervised Visual Representation Learning with Image Augmentation

Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Learn your ABCs: Approximate Bijective Correspondence for isolating factors of variation

Multi-Dataset Benchmarks for Masked Identification using Contrastive Representation Learning

Generative Models as a Data Source for Multiview Representation Learning

Hangul Fonts Dataset: a Hierarchical and Compositional Dataset for Investigating Learned Representations

Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data with Competing Risks

No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data

Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs

Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian Approach

Benchmarking Representation Learning for Natural World Image Collections

Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style

Online Limited Memory Neural-Linear Bandits with Likelihood Matching

Multi-output Gaussian Processes for Uncertainty-aware Recommender Systems

Variational Leakage: The Role of Information Complexity in Privacy Leakage

Self-Supervised Learning of Domain Invariant Features for Depth Estimation

Self-supervised Graph-level Representation Learning with Local and Global Structure

Category Contrast for Unsupervised Domain Adaptation in Visual Tasks

Unified Representation Learning for Efficient Medical Image Analysis

Multi-task Transformation Learning for Robust Out-of-Distribution Detection

Unsupervised Discovery, Control, and Disentanglement of Semantic Attributes with Applications to Anomaly Detection

Efficient Iterative Amortized Inference for Learning Symmetric and Disentangled Multi-Object Representations

Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning

Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization

Local Disentanglement in Variational Auto-Encoders Using Jacobian $L_1$ Regularization

Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations

Matching in Selective and Balanced Representation Space for Treatment Effects Estimation

Aligning Pretraining for Detection via Object-Level Contrastive Learning

The Surprising Power of Graph Neural Networks with Random Node Initialization

RGBT Tracking via Multi-Adapter Network with Hierarchical Divergence Loss

Domain-Adversarial and Conditional State Space Model for Imitation Learning

Self-Supervised Learning of Remote Sensing Scene Representations Using Contrastive Multiview Coding

3D Hand Pose Estimation via Regularized Graph Representation Learning

GMAIR: Unsupervised Object Detection Based on Spatial Attention and Gaussian Mixture

Learning Representation over Dynamic Graph using Aggregation-Diffusion Mechanism

Hierarchical Representation Learning for Markov Decision Processes

Aggregated Learning: A Vector-Quantization Approach to Learning Neural Network Classifiers

A Novel Graph-Theoretic Deep Representation Learning Method for Multi-Label Remote Sensing Image Retrieval

Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation

Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation

Beyond Max-Margin: Class Margin Equilibrium for Few-shot Object Detection

Graph Consistency Based Mean-Teaching for Unsupervised Domain Adaptive Person Re-Identification

CLRGaze: Contrastive Learning of Representations for Eye Movement Signals

On the benefits of representation regularization in invariance based domain generalization

Transformer-Based Deep Image Matching for Generalizable Person Re-identification

Invariant Representation Learning for Infant Pose Estimation with Small Data

SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization

Unsupervised Adversarially-Robust Representation Learning on Graphs

FReTAL: Generalizing Deepfake Detection using Knowledge Distillation and Representation Learning

Self-supervised Detransformation Autoencoder for Representation Learning in Open Set Recognition

SSAN: Separable Self-Attention Network for Video Representation Learning

CARLS: Cross-platform Asynchronous Representation Learning System

Provable Representation Learning for Imitation with Contrastive Fourier Features

SB-GCN: Structured BREP Graph Convolutional Network for Automatic Mating of CAD Assemblies

A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms

Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images

Deep High-Resolution Representation Learning for Cross-Resolution Person Re-identification

Self-Supervised Graph Representation Learning via Topology Transformations

HIN-RNN: A Graph Representation Learning Neural Network for Fraudster Group Detection With No Handcrafted Features

Unsupervised Visual Representation Learning by Online Constrained K-Means

Comprehensible Convolutional Neural Networks via Guided Concept Learning

Multi-modal Understanding and Generation for Medical Images and Text via Vision-Language Pre-Training

Heterogeneous Graph Representation Learning with Relation Awareness

Dynamic Class Queue for Large Scale Face Recognition In the Wild

SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism

Deep Clustering and Representation Learning with Geometric Structure Preservation

Self-Supervised Visual Learning by Variable Playback Speeds Prediction of a Video

Be Causal: De-biasing Social Network Confounding in Recommendation

Content-adaptive Representation Learning for Fast Image Super-resolution

Negational Symmetry of Quantum Neural Networks for Binary Pattern Classification

Do We Really Need to Learn Representations from In-domain Data for Outlier Detection?

Prototype Guided Federated Learning of Visual Feature Representations

In-bed Pressure-based Pose Estimation using Image Space Representation Learning

Scaling-Translation-Equivariant Networks with Decomposed Convolutional Filters

Finding a Needle in a Haystack: Tiny Flying Object Detection in 4K Videos using a Joint Detection-and-Tracking Approach

TCL: Transformer-based Dynamic Graph Modelling via Contrastive Learning

SelfAugment: Automatic Augmentation Policies for Self-Supervised Learning

CheXseen: Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays

Disentangled Variational Information Bottleneck for Multiview Representation Learning

Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing

Maximizing Mutual Information Across Feature and Topology Views for Learning Graph Representations

Contrastive Learning of Image Representations with Cross-Video Cycle-Consistency

Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs

Unsupervised Representation Learning from Pathology Images with Multi-directional Contrastive Predictive Coding

Home Action Genome: Cooperative Compositional Action Understanding

Representation Learning via Global Temporal Alignment and Cycle-Consistency

VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning

NEU: A Meta-Algorithm for Universal UAP-Invariant Feature Representation

Conformer: Local Features Coupling Global Representations for Visual Recognition

Highly Efficient Representation and Active Learning Framework for Imbalanced Data and its Application to COVID-19 X-Ray Classification

Unsupervised Visual Representation Learning by Tracking Patches in Video

Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing

MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering

Subspace Representation Learning for Few-shot Image Classification

Robust and Generalizable Visual Representation Learning via Random Convolutions

UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks

Representation Learning using Graph Autoencoders with Residual Connections

MARL: Multimodal Attentional Representation Learning for Disease Prediction

3D Human Action Representation Learning via Cross-View Consistency Pursuit

Black-box Gradient Attack on Graph Neural Networks: Deeper Insights in Graph-based Attack and Defense

A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning

Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning

Robust Ultra-wideband Range Error Mitigation with Deep Learning at the Edge

Using Radio Archives for Low-Resource Speech Recognition: Towards an Intelligent Virtual Assistant for Illiterate Users

Joint Representation Learning and Novel Category Discovery on Single- and Multi-modal Data

Unlocking the Full Potential of Small Data with Diverse Supervision

Multimodal Contrastive Training for Visual Representation Learning

Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks

How Well Self-Supervised Pre-Training Performs with Streaming Data?

Eccentric Regularization: Minimizing Hyperspherical Energy without explicit projection

Distilling Audio-Visual Knowledge by Compositional Contrastive Learning

Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Learning

Graph Learning for Combinatorial Optimization: A Survey of State-of-the-Art

Shadow Neural Radiance Fields for Multi-view Satellite Photogrammetry

Temporal Consistency Loss for High Resolution Textured and Clothed 3DHuman Reconstruction from Monocular Video

Contrastive Learning Improves Model Robustness Under Label Noise

An efficient manifold density estimator for all recommendation systems

When Contrastive Learning Meets Active Learning: A Novel Graph Active Learning Paradigm with Self-Supervision

Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks

Variational Co-embedding Learning for Attributed Network Clustering

Self-Supervised Representation Learning for RGB-D Salient Object Detection

Probing Negative Sampling Strategies to Learn GraphRepresentations via Unsupervised Contrastive Learning

CUPID: Adaptive Curation of Pre-training Data for Video-and-Language Representation Learning

Self-supervised Representation Learning with Relative Predictive Coding

Representation Learning for Networks in Biology and Medicine: Advancements, Challenges, and Opportunities

Multi-view Graph Contrastive Representation Learning for Drug-Drug Interaction Prediction

A Graph VAE and Graph Transformer Approach to Generating Molecular Graphs

GATSBI: Generative Agent-centric Spatio-temporal Object Interaction

mSHINE: A Multiple-meta-paths Simultaneous Learning Framework for Heterogeneous Information Network Embedding

Cascaded deep monocular 3D human pose estimation with evolutionary training data

Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions

Seed the Views: Hierarchical Semantic Alignment for Contrastive Representation Learning

Contrastive Learning of Global and Local Audio-Visual Representations

Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification

Strumming to the Beat: Audio-Conditioned Contrastive Video Textures

Delving into Inter-Image Invariance for Unsupervised Visual Representations

Continual Prototype Evolution: Learning Online from Non-Stationary Data Streams

Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting

Topological Regularization for Graph Neural Networks Augmentation

On Equivariant and Invariant Learning of Object Landmark Representations

AU-Expression Knowledge Constrained Representation Learning for Facial Expression Recognition

Self-supervised Video Representation Learning by Context and Motion Decoupling

Multiview Pseudo-Labeling for Semi-supervised Learning from Video

xERTE: Explainable Reasoning on Temporal Knowledge Graphs for Forecasting Future Links

Unsupervised Degradation Representation Learning for Blind Super-Resolution

UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training

Jigsaw Clustering for Unsupervised Visual Representation Learning

Semi-Supervised Domain Adaptation via Selective Pseudo Labeling and Progressive Self-Training

Deep adaptive fuzzy clustering for evolutionary unsupervised representation learning

Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph Analysis

Rotation-Invariant Local-to-Global Representation Learning for 3D Point Cloud

Contrastive Learning of Single-Cell Phenotypic Representations for Treatment Classification

Parameterized Hypercomplex Graph Neural Networks for Graph Classification

Pre-training strategies and datasets for facial representation learning

Prototypical Contrastive Learning of Unsupervised Representations

Progressive Domain Expansion Network for Single Domain Generalization

Unsupervised Hyperbolic Representation Learning via Message Passing Auto-Encoders

Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans

AlignMix: Improving representation by interpolating aligned features

Viewmaker Networks: Learning Views for Unsupervised Representation Learning

SelfGait: A Spatiotemporal Representation Learning Method for Self-supervised Gait Recognition

Contrastive Learning based Hybrid Networks for Long-Tailed Image Classification

Learning View-Disentangled Human Pose Representation by Contrastive Cross-View Mutual Information Maximization

Learning and Evaluating Representations for Deep One-class Classification

Hierarchical Deep CNN Feature Set-Based Representation Learning for Robust Cross-Resolution Face Recognition

Universal Representation Learning from Multiple Domains for Few-shot Classification

Unsupervised Learning of Local Discriminative Representation for Medical Images

Leveraging background augmentations to encourage semantic focus in self-supervised contrastive learning

Health Status Prediction with Local-Global Heterogeneous Behavior Graph

Group-aware Label Transfer for Domain Adaptive Person Re-identification

CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models

Bidirectional Representation Learning from Transformers using Multimodal Electronic Health Record Data to Predict Depression

Improving Transformation Invariance in Contrastive Representation Learning

Catastrophic Forgetting in Deep Graph Networks: an Introductory Benchmark for Graph Classification

Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks

Language-Agnostic Representation Learning of Source Code from Structure and Context

An Unsupervised Sampling Approach for Image-Sentence Matching Using Document-Level Structural Information

ActivationNet: Representation learning to predict contact quality of interacting 3-D surfaces in engineering designs

NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments

UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning

Theory and Evaluation Metrics for Learning Disentangled Representations

Space-Time Crop & Attend: Improving Cross-modal Video Representation Learning

Multi-Objective Interpolation Training for Robustness to Label Noise

i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning

ALADIN: All Layer Adaptive Instance Normalization for Fine-grained Style Similarity

Training GANs with Stronger Augmentations via Contrastive Discriminator

Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding

ScoreGAN: A Fraud Review Detector based on Multi Task Learning of Regulated GAN with Data Augmentation

Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects

Temporal Contrastive Graph Learning for Video Action Recognition and Retrieval

VideoMoCo: Contrastive Video Representation Learning with Temporally Adversarial Examples

Decoupling Global and Local Representations via Invertible Generative Flows

RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning

Boosting ship detection in SAR images with complementary pretraining techniques

COMPAS: Representation Learning with Compositional Part Sharing for Few-Shot Classification

Scaffold Embeddings: Learning the Structure Spanned by Chemical Fragments, Scaffolds and Compounds

On the Transfer of Disentangled Representations in Realistic Settings

Semantic MapNet: Building Allocentric Semantic Maps and Representations from Egocentric Views

A Local Similarity-Preserving Framework for Nonlinear Dimensionality Reduction with Neural Networks

Reframing Neural Networks: Deep Structure in Overcomplete Representations

SimTriplet: Simple Triplet Representation Learning with a Single GPU

Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning

Bio-Inspired Representation Learning for Visual Attention Prediction

Unsupervised Pretraining for Object Detection by Patch Reidentification

Unsupervised Object Keypoint Learning using Local Spatial Predictability

Anomaly Detection Based on Selection and Weighting in Latent Space

Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsing

What Can You Learn from Your Muscles? Learning Visual Representation from Human Interactions

Fairness in TabNet Model by Disentangled Representation for the Prediction of Hospital No-Show

Distributed Dynamic Map Fusion via Federated Learning for Intelligent Networked Vehicles

Variational Structured Attention Networks for Deep Visual Representation Learning

Fully Unsupervised Person Re-identification viaSelective Contrastive Learning

WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning

Enabling Counterfactual Survival Analysis with Balanced Representations

Multi-Model Least Squares-Based Recomputation Framework for Large Data Analysis

Relate and Predict: Structure-Aware Prediction with Jointly Optimized Neural DAG

FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation

CoMatch: Semi-supervised Learning with Contrastive Graph Regularization

Sequential Place Learning: Heuristic-Free High-Performance Long-Term Place Recognition

Dynamic Graph Representation Learning for Video Dialog via Multi-Modal Shuffled Transformers

GEBT: Drawing Early-Bird Tickets in Graph Convolutional Network Training

Self-Supervised Multi-View Learning via Auto-Encoding 3D Transformations

Representation Learning for Sequence Data with Deep Autoencoding Predictive Components

Usable Information and Evolution of Optimal Representations During Training

A Complete Discriminative Tensor Representation Learning for Two-Dimensional Correlation Analysis

Disentangling Geometric Deformation Spaces in Generative Latent Shape Models

Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning

Improve Variational Autoencoder for Text Generationwith Discrete Latent Bottleneck

RGB-D Railway Platform Monitoring and Scene Understanding for Enhanced Passenger Safety

NeuCrowd: Neural Sampling Network for Representation Learning with Crowdsourced Labels

Learning Low-dimensional Manifolds for Scoring of Tissue Microarray Images

Dynamic Connected Neural Decision Classifier and Regressor with Dynamic Softing Pruning

Variationally Regularized Graph-based Representation Learning for Electronic Health Records

Self-Supervised Learning via multi-Transformation Classification for Action Recognition

A Survey of Label-noise Representation Learning: Past, Present and Future

MolCLR: Molecular Contrastive Learning of Representations via Graph Neural Networks

Learning to Noise: Application-Agnostic Data Sharing with Local Differential Privacy

Contrastive Pre-training for Imbalanced Corporate Credit Ratings

OMBA: User-Guided Product Representations for Online Market Basket Analysis

Training Stacked Denoising Autoencoders for Representation Learning

Towards Better Understanding Meta-learning Methods through Multi-task Representation Learning Theory

On the Equivalence of Decoupled Graph Convolution Network and Label Propagation

DAC: Deep Autoencoder-based Clustering, a General Deep Learning Framework of Representation Learning

Relation-aware Graph Attention Model With Adaptive Self-adversarial Training

Adversarial Attack on Network Embeddings via Supervised Network Poisoning

Domain Invariant Representation Learning with Domain Density Transformations

Online Disease Self-diagnosis with Inductive Heterogeneous Graph Convolutional Networks

Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning

Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect

Self-supervised driven consistency training for annotation efficient histopathology image analysis

Multiview Variational Graph Autoencoders for Canonical Correlation Analysis

Representation learning from videos in-the-wild: An object-centric approach

Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning

Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning

Adversarial representation learning for synthetic replacement of private attributes

Near-optimal Representation Learning for Linear Bandits and Linear RL

Towards Generalized and Distributed Privacy-Preserving Representation Learning

Disentangled Representation Learning and Generation with Manifold Optimization

Fast Concept Mapping: The Emergence of Human Abilities in Artificial Neural Networks when Learning Embodied and Self-Supervised

Learning Matching Representations for Individualized Organ Transplantation Allocation

Evaluating the Interpretability of Generative Models by Interactive Reconstruction

A Survey on Concept Factorization: From Shallow to Deep Representation Learning

The Deep Radial Basis Function Data Descriptor (D-RBFDD) Network: A One-Class Neural Network for Anomaly Detection

Self-supervised Video Representation Learning by Uncovering Spatio-temporal Statistics

Moving fast and slow: Analysis of representations and post-processing in speech-driven automatic gesture generation

SeCo: Exploring Sequence Supervision for Unsupervised Representation Learning

Improving Graph Representation Learning by Contrastive Regularization

Graphonomy: Universal Image Parsing via Graph Reasoning and Transfer

COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction

Deep Learning Generalization and the Convex Hull of Training Sets

Improving Few-Shot Learning with Auxiliary Self-Supervised Pretext Tasks

A Joint Representation Learning and Feature Modeling Approach for One-class Recognition

Simple Multi-Resolution Representation Learning for Human Pose Estimation

Self-Adaptive Training: Bridging the Supervised and Self-Supervised Learning

Maximizing Cohesion and Separation in Graph Representation Learning: A Distance-aware Negative Sampling Approach

Attentive Representation Learning with Adversarial Training for Short Text Clustering

Learning over Families of Sets -- Hypergraph Representation Learning for Higher Order Tasks

Distilling Localization for Self-Supervised Representation Learning

The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods

Discovering Discriminative Geometric Features with Self-Supervised Attention for Vehicle Re-Identification and Beyond

Alignment and stability of embeddings: measurement and inference improvement

Physics-informed learning of governing equations from scarce data

Anti-Transfer Learning for Task Invariance in Convolutional Neural Networks for Speech Processing

Variational Embeddings for Community Detection and Node Representation

UniNet: Scalable Network Representation Learning with Metropolis-Hastings Sampling

DIRL: Domain-Invariant Representation Learning for Sim-to-Real Transfer

DICE: Deep Significance Clustering for Outcome-Aware Stratification

Meta-path Free Semi-supervised Learning for Heterogeneous Networks

Partial Domain Adaptation Using Selective Representation Learning For Class-Weight Computation

A unified view for unsupervised representation learning with density ratio estimation: Maximization of mutual information, nonlinear ICA and nonlinear subspace estimation

Reprogramming Language Models for Molecular Representation Learning

Deep Learning for Person Re-identification: A Survey and Outlook

CircleGAN: Generative Adversarial Learning across Spherical Circles

Towards Non-I.I.D. and Invisible Data with FedNAS: Federated Deep Learning via Neural Architecture Search

Self-supervised Pre-training with Hard Examples Improves Visual Representations

node2coords: Graph Representation Learning with Wasserstein Barycenters

One-shot Representational Learning for Joint Biometric and Device Authentication

Small Data Challenges in Big Data Era: A Survey of Recent Progress on Unsupervised and Semi-Supervised Methods

Representation Learning of Reconstructed Graphs Using Random Walk Graph Convolutional Network

Hybrid Micro/Macro Level Convolution for Heterogeneous Graph Learning

TSGCNet: Discriminative Geometric Feature Learning with Two-Stream GraphConvolutional Network for 3D Dental Model Segmentation

On self-supervised multi-modal representation learning: An application to Alzheimer's disease

Unsupervised Deep Representation Learning and Few-Shot Classification of PolSAR Images

Learning Multi-Modal Nonlinear Embeddings: Performance Bounds and an Algorithm

Molecular CT: Unifying Geometry and Representation Learning for Molecules at Different Scales

Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19

P4Contrast: Contrastive Learning with Pairs of Point-Pixel Pairs for RGB-D Scene Understanding

Private-Shared Disentangled Multimodal VAE for Learning of Hybrid Latent Representations

A Novel Framework for Spatio-Temporal Prediction of Environmental Data Using Deep Learning

Deep Multi-attribute Graph Representation Learning on Protein Structures

Online Bag-of-Visual-Words Generation for Unsupervised Representation Learning

Biomedical Knowledge Graph Refinement and Completion using Graph Representation Learning and Top-K Similarity Measure

A Holistically-Guided Decoder for Deep Representation Learning with Applications to Semantic Segmentation and Object Detection

Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification

Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion

Automated 3D cephalometric landmark identification using computerized tomography

Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks

Linear Disentangled Representations and Unsupervised Action Estimation

Self-Supervised Representation Learning for Detection of ACL Tear Injury in Knee MR Videos

Guiding Graph Embeddings using Path-Ranking Methods for Error Detection innoisy Knowledge Graphs

A Meta-Learning Approach for Graph Representation Learning in Multi-Task Settings

Unsupervised deep learning for individualized brain functional network identification

CommPOOL: An Interpretable Graph Pooling Framework for Hierarchical Graph Representation Learning

Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning

Modality to Modality Translation: An Adversarial Representation Learning and Graph Fusion Network for Multimodal Fusion

Graph-Based Generative Representation Learning of Semantically and Behaviorally Augmented Floorplans

Art Style Classification with Self-Trained Ensemble of AutoEncoding Transformations

Self-Supervised Visual Representation Learning from Hierarchical Grouping

Neural Contextual Bandits with Deep Representation and Shallow Exploration

DyERNIE: Dynamic Evolution of Riemannian Manifold Embeddings for Temporal Knowledge Graph Completion

BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images

About contrastive unsupervised representation learning for classification and its convergence

Towards Good Practices in Self-supervised Representation Learning

Consistent Representation Learning for High Dimensional Data Analysis

Two-Level Adversarial Visual-Semantic Coupling for Generalized Zero-shot Learning

A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research

Center-wise Local Image Mixture For Contrastive Representation Learning

Beyond Single Instance Multi-view Unsupervised Representation Learning

Molecular representation learning with language models and domain-relevant auxiliary tasks

Can Temporal Information Help with Contrastive Self-Supervised Learning?

Collaborative Attention Mechanism for Multi-View Action Recognition

Unsupervised learning of disentangled representations in deep restricted kernel machines with orthogonality constraints

CellSegmenter: unsupervised representation learning and instance segmentation of modular images

Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation

SEA: Sentence Encoder Assembly for Video Retrieval by Textual Queries

Boosting Contrastive Self-Supervised Learning with False Negative Cancellation

CoKe: Localized Contrastive Learning for Robust Keypoint Detection

Balance Regularized Neural Network Models for Causal Effect Estimation

Extendable and invertible manifold learning with geometry regularized autoencoders

Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning

PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding

Representation Learning with Statistical Independence to Mitigate Bias

Causality-aware counterfactual confounding adjustment for feature representations learned by deep models

FILDNE: A Framework for Incremental Learning of Dynamic Networks Embeddings

Hybrid Consistency Training with Prototype Adaptation for Few-Shot Learning

Heterogeneous Contrastive Learning: Encoding Spatial Information for Compact Visual Representations

Representation learning for improved interpretability and classification accuracy of clinical factors from EEG

Back to the Future: Cycle Encoding Prediction for Self-supervised Contrastive Video Representation Learning

Can Semantic Labels Assist Self-Supervised Visual Representation Learning?

Temporally Coherent Embeddings for Self-Supervised Video Representation Learning

Deep Representation Learning of Patient Data from Electronic Health Records (EHR): A Systematic Review

Robust Facial Landmark Detection by Cross-order Cross-semantic Deep Network

Prototypical Contrast and Reverse Prediction: Unsupervised Skeleton Based Action Recognition

On the Benefits of Early Fusion in Multimodal Representation Learning

Relation-weighted Link Prediction for Disease Gene Identification

Tensor-based Intrinsic Subspace Representation Learning for Multi-view Clustering

Unsupervised Video Representation Learning by Bidirectional Feature Prediction

EGAD: Evolving Graph Representation Learning with Self-Attention and Knowledge Distillation for Live Video Streaming Events

Distill2Vec: Dynamic Graph Representation Learning with Knowledge Distillation

Self-Supervised Relational Reasoning for Representation Learning

Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere

Learning Generalizable Physiological Representations from Large-scale Wearable Data

Self-Supervised Learning for Large-Scale Unsupervised Image Clustering

K-Core based Temporal Graph Convolutional Network for Dynamic Graphs

GraphAIR: Graph Representation Learning with Neighborhood Aggregation and Interaction

Node-Centric Graph Learning from Data for Brain State Identification

Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators

Physical-Virtual Collaboration Modeling for Intra-and Inter-Station Metro Ridership Prediction

Meta-learning Transferable Representations with a Single Target Domain

MARNet: Multi-Abstraction Refinement Network for 3D Point Cloud Analysis

COOT: Cooperative Hierarchical Transformer for Video-Text Representation Learning

ControlVAE: Tuning, Analytical Properties, and Performance Analysis

Self-supervised Representation Learning for Evolutionary Neural Architecture Search

Multimodal and self-supervised representation learning for automatic gesture recognition in surgical robotics

Automatic Chronic Degenerative Diseases Identification Using Enteric Nervous System Images

Representation Learning for Integrating Multi-domain Outcomes to Optimize Individualized Treatments

Measure Inducing Classification and Regression Trees for Functional Data

Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data

GripNet: Graph Information Propagation on Supergraph for Heterogeneous Graphs

WaveTransform: Crafting Adversarial Examples via Input Decomposition

Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning

A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices

InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs

Cycle-Contrast for Self-Supervised Video Representation Learning

Quantifying Learnability and Describability of Visual Concepts Emerging in Representation Learning

ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA

Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modelling

Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation

Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?

Out-of-Sample Representation Learning for Multi-Relational Graphs

Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection

ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction

Zero-Shot Learning from scratch (ZFS): leveraging local compositional representations

Large-Scale Adversarial Training for Vision-and-Language Representation Learning

On the Theory of Transfer Learning: The Importance of Task Diversity

DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation

BayReL: Bayesian Relational Learning for Multi-omics Data Integration

Functional Regularization for Representation Learning: A Unified Theoretical Perspective

Semantics-Guided Representation Learning with Applications to Visual Synthesis

AAG: Self-Supervised Representation Learning by Auxiliary Augmentation with GNT-Xent Loss

Correlation-aware Deep Generative Model for Unsupervised Anomaly Detection

Graphite: GRAPH-Induced feaTure Extraction for Point Cloud Registration

Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational Data

Double Robust Representation Learning for Counterfactual Prediction

For self-supervised learning, Rationality implies generalization, provably

Learning by Sampling and Compressing: Efficient Graph Representation Learning with Extremely Limited Annotations

MS$^2$L: Multi-Task Self-Supervised Learning for Skeleton Based Action Recognition

FairMixRep : Self-supervised Robust Representation Learning for Heterogeneous Data with Fairness constraints

TriNE: Network Representation Learning for Tripartite Heterogeneous Networks

DotSCN: Group Re-identification via Domain-Transferred Single and Couple Representation Learning

Graph Regularized Nonnegative Tensor Ring Decomposition for Multiway Representation Learning

Locality Preserving Dense Graph Convolutional Networks with Graph Context-Aware Node Representations

A Cross-Level Information Transmission Network for Predicting Phenotype from New Genotype: Application to Cancer Precision Medicine

Learning to Profile: User Meta-Profile Network for Few-Shot Learning

End-to-end Autonomous Driving Perception with Sequential Latent Representation Learning

Learning disentangled representations with the Wasserstein Autoencoder

PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning

Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling

3D Human Motion Estimation via Motion Compression and Refinement

CO2: Consistent Contrast for Unsupervised Visual Representation Learning

Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness

MIX'EM: Unsupervised Image Classification using a Mixture of Embeddings

DynamicVAE: Decoupling Reconstruction Error and Disentangled Representation Learning

Representation Learning on Visual-Symbolic Graphs for Video Understanding

Training general representations for remote sensing using in-domain knowledge

Unsupervised Feature Learning for Event Data: Direct vs Inverse Problem Formulation

Temporal Context Aggregation for Video Retrieval with Contrastive Learning

HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training

Cross-Task Representation Learning for Anatomical Landmark Detection

Deep Adversarial Transition Learning using Cross-Grafted Generative Stacks

G-SimCLR : Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling

Representation Learning from Limited Educational Data with Crowdsourced Labels

Learning to Identify Physical Parameters from Video Using Differentiable Physics

Polyp-artifact relationship analysis using graph inductive learned representations

Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning

Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring

Spectral Analysis Network for Deep Representation Learning and Image Clustering

An unsupervised deep learning framework via integrated optimization of representation learning and GMM-based modeling

Learning and Reasoning with the Graph Structure Representation in Robotic Surgery

Bootstrap your own latent: A new approach to self-supervised Learning

Ordinal-Content VAE: Isolating Ordinal-Valued Content Factors in Deep Latent Variable Models

Unsupervised Wasserstein Distance Guided Domain Adaptation for 3D Multi-Domain Liver Segmentation

A Simple and General Graph Neural Network with Stochastic Message Passing

Don't miss the Mismatch: Investigating the Objective Function Mismatch for Unsupervised Representation Learning

MLM: A Benchmark Dataset for Multitask Learning with Multiple Languages and Modalities

Self-supervised Video Representation Learning by Pace Prediction

CAGNN: Cluster-Aware Graph Neural Networks for Unsupervised Graph Representation Learning

A Comparison of Pre-trained Vision-and-Language Models for Multimodal Representation Learning across Medical Images and Reports

Unsupervised Feature Learning by Autoencoder and Prototypical Contrastive Learning for Hyperspectral Classification

Improved Bilevel Model: Fast and Optimal Algorithm with Theoretical Guarantee

Temporal Continuity Based Unsupervised Learning for Person Re-Identification

LaDDer: Latent Data Distribution Modelling with a Generative Prior

Decontextualized learning for interpretable hierarchical representations of visual patterns

Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning"

Projective Latent Interventions for Understanding and Fine-tuning Classifiers

FedMVT: Semi-supervised Vertical Federated Learning with MultiView Training

Unsupervised Multi-Modal Representation Learning for Affective Computing with Multi-Corpus Wearable Data

Multi-View Self-Attention for Interpretable Drug-Target Interaction Prediction

Info3D: Representation Learning on 3D Objects using Mutual Information Maximization and Contrastive Learning

Joint Modeling of Chest Radiographs and Radiology Reports for Pulmonary Edema Assessment

Mutual Information-driven Subject-invariant and Class-relevant Deep Representation Learning in BCI

Explainable Recommender Systems via Resolving Learning Representations

Unsupervised Image Classification for Deep Representation Learning

Hop Sampling: A Simple Regularized Graph Learning for Non-Stationary Environments

RFNet: Riemannian Fusion Network for EEG-based Brain-Computer Interfaces

Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening

Shifu2: A Network Representation Learning Based Model for Advisor-advisee Relationship Mining

Apparel-invariant Feature Learning for Apparel-changed Person Re-identification

Self-supervised Contrastive Video-Speech Representation Learning for Ultrasound

LEEP: A New Measure to Evaluate Transferability of Learned Representations

Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework

Informative Dropout for Robust Representation Learning: A Shape-bias Perspective

Self-supervised Temporal Discriminative Learning for Video Representation Learning

Label-Efficient Learning on Point Clouds using Approximate Convex Decompositions

Semi-Supervised Representation Learning based on Probabilistic Labeling

BSD-GAN: Branched Generative Adversarial Network for Scale-Disentangled Representation Learning and Image Synthesis

Predicting What You Already Know Helps: Provable Self-Supervised Learning

Distribution-induced Bidirectional Generative Adversarial Network for Graph Representation Learning

Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases

Unsupervised Hierarchical Graph Representation Learning by Mutual Information Maximization

Multi-Object Representation Learning with Iterative Variational Inference

Towards Robust Learning with Different Label Noise Distributions

Label-Consistency based Graph Neural Networks for Semi-supervised Node Classification

Federated Self-Supervised Learning of Multi-Sensor Representations for Embedded Intelligence

Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space

Real-World Multi-Domain Data Applications for Generalizations to Clinical Settings

Investigating Object Compositionality in Generative Adversarial Networks

METEOR: Learning Memory and Time Efficient Representations from Multi-modal Data Streams

$\mathtt{MedGraph:}$ Structural and Temporal Representation Learning of Electronic Medical Records

Unsupervised Deep Representation Learning for Real-Time Tracking

Edge-aware Graph Representation Learning and Reasoning for Face Parsing

Interpretable Foreground Object Search As Knowledge Distillation

Learning Object Relation Graph and Tentative Policy for Visual Navigation

Video Representation Learning by Recognizing Temporal Transformations

Unsupervised Heterogeneous Coupling Learning for Categorical Representation

Learning latent representations across multiple data domains using Lifelong VAEGAN

Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting

Unsupervised Representation Learning by Predicting Random Distances

Robust Hierarchical Graph Classification with Subgraph Attention

Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference

Meta-Learning GNN Initializations for Low-Resource Molecular Property Prediction

VisualEchoes: Spatial Image Representation Learning through Echolocation

Neural Wireframe Renderer: Learning Wireframe to Image Translations

TUDataset: A collection of benchmark datasets for learning with graphs

Deep Representation Learning and Clustering of Traffic Scenarios

Temporal Distinct Representation Learning for Action Recognition

Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration

PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer

Software Engineering Event Modeling using Relative Time in Temporal Knowledge Graphs

Disentangled Variational Autoencoder based Multi-Label Classification with Covariance-Aware Multivariate Probit Model

Adversarial Self-Supervised Learning for Semi-Supervised 3D Action Recognition

Anomaly Detection-Based Unknown Face Presentation Attack Detection

Representation Learning via Adversarially-Contrastive Optimal Transport

Interpretation of Deep Temporal Representations by Selective Visualization of Internally Activated Nodes

JGR-P2O: Joint Graph Reasoning based Pixel-to-Offset Prediction Network for 3D Hand Pose Estimation from a Single Depth Image

Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions

AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes

COALA: Co-Aligned Autoencoders for Learning Semantically Enriched Audio Representations

Multi-Manifold Learning for Large-scale Targeted Advertising System

README: REpresentation learning by fairness-Aware Disentangling MEthod

A Novel Random Forest Dissimilarity Measure for Multi-View Learning

Nested Subspace Arrangement for Representation of Relational Data

A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces

Decoder-free Robustness Disentanglement without (Additional) Supervision

Towards Better Understanding of Disentangled Representations via Mutual Information

A Simple Framework for Contrastive Learning of Visual Representations

Automatic Shortcut Removal for Self-Supervised Representation Learning

Unsupervised Learning of Video Representations via Dense Trajectory Clustering

Unsupervised Video Decomposition using Spatio-temporal Iterative Inference

A New Modal Autoencoder for Functionally Independent Feature Extraction

Time-varying Graph Representation Learning via Higher-Order Skip-Gram with Negative Sampling

Uncertainty in Neural Relational Inference Trajectory Reconstruction

Understanding Negative Sampling in Graph Representation Learning

Why bigger is not always better: on finite and infinite neural networks

Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View

An Improved Semi-Supervised VAE for Learning Disentangled Representations

Hierarchical Inter-Message Passing for Learning on Molecular Graphs

Lightweight Multi-View 3D Pose Estimation through Camera-Disentangled Representation

Video Playback Rate Perception for Self-supervisedSpatio-Temporal Representation Learning

Graph Pooling with Node Proximity for Hierarchical Representation Learning

Quantifying Challenges in the Application of Graph Representation Learning

Simple and Effective Graph Autoencoders with One-Hop Linear Models

Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction

Learning to Observe: Approximating Human Perceptual Thresholds for Detection of Suprathreshold Image Transformations

Robust Locality-Aware Regression for Labeled Data Classification

Multi-view Low-rank Preserving Embedding: A Novel Method for Multi-view Representation

Dynamic Spatial-Temporal Representation Learning for Traffic Flow Prediction

Adaptive Graph Representation Learning for Video Person Re-identification

Similarity-based Classification: Connecting Similarity Learning to Binary Classification

G5: A Universal GRAPH-BERT for Graph-to-Graph Transfer and Apocalypse Learning

Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement

Neural Physicist: Learning Physical Dynamics from Image Sequences

Unsupervised Graph Representation by Periphery and Hierarchical Information Maximization

Privacy Adversarial Network: Representation Learning for Mobile Data Privacy

Understanding Graph Neural Networks from Graph Signal Denoising Perspectives

On Mutual Information in Contrastive Learning for Visual Representations

Multi-modal Self-Supervision from Generalized Data Transformations

Improving k-Means Clustering Performance with Disentangled Internal Representations

MHVAE: a Human-Inspired Deep Hierarchical Generative Model for Multimodal Representation Learning

Representation Bayesian Risk Decompositions and Multi-Source Domain Adaptation

Can Giraffes Become Birds? An Evaluation of Image-to-image Translation for Data Generation

Local Motion Planner for Autonomous Navigation in Vineyards with a RGB-D Camera-Based Algorithm and Deep Learning Synergy

Multi-Margin based Decorrelation Learning for Heterogeneous Face Recognition

RGBD-GAN: Unsupervised 3D Representation Learning From Natural Image Datasets via RGBD Image Synthesis

Adversarial Attack on Hierarchical Graph Pooling Neural Networks

RankPose: Learning Generalised Feature with Rank Supervision for Head Pose Estimation

An analysis on the use of autoencoders for representation learning: fundamentals, learning task case studies, explainability and challenges

Detailed 2D-3D Joint Representation for Human-Object Interaction

Sketch-BERT: Learning Sketch Bidirectional Encoder Representation from Transformers by Self-supervised Learning of Sketch Gestalt

Unsupervised Severe Weather Detection Via Joint Representation Learning Over Textual and Weather Data

Progressive growing of self-organized hierarchical representations for exploration

Learning to Align Multi-Camera Domains using Part-Aware Clustering for Unsupervised Video Person Re-Identification

Walking the Tightrope: An Investigation of the Convolutional Autoencoder Bottleneck

Supervision and Source Domain Impact on Representation Learning: A Histopathology Case Study

A Showcase of the Use of Autoencoders in Feature Learning Applications

Watching the World Go By: Representation Learning from Unlabeled Videos

Interpreting Rate-Distortion of Variational Autoencoder and Using Model Uncertainty for Anomaly Detection

Mutual Information Gradient Estimation for Representation Learning

DIABLO: Dictionary-based Attention Block for Deep Metric Learning

Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models

Learning Robust Data Representation: A Knowledge Flow Perspective

AutoHR: A Strong End-to-end Baseline for Remote Heart Rate Measurement with Neural Searching

Shape-Oriented Convolution Neural Network for Point Cloud Analysis

Convolutional Embedded Networks for Population Scale Clustering and Bio-ancestry Inferencing

Are You A Risk Taker? Adversarial Learning of Asymmetric Cross-Domain Alignment for Risk Tolerance Prediction

Disentangled Human Body Embedding Based on Deep Hierarchical Neural Network

A Cyclically-Trained Adversarial Network for Invariant Representation Learning

Controlling Computation versus Quality for Neural Sequence Models

Contrastive Video Representation Learning via Adversarial Perturbations

MxPool: Multiplex Pooling for Hierarchical Graph Representation Learning

VehicleNet: Learning Robust Visual Representation for Vehicle Re-identification

Multimodal Deep Learning for Mental Disorders Prediction from Audio Speech Samples

Efficient Deep Representation Learning by Adaptive Latent Space Sampling

Deep Representation Learning on Long-tailed Data: A Learnable Embedding Augmentation Perspective

FairNN- Conjoint Learning of Fair Representations for Fair Decisions

Unsupervised Representation Learning with Minimax Distance Measures

Real-world Person Re-Identification via Degradation Invariance Learning

Identifying Sparse Low-Dimensional Structures in Markov Chains: A Nonnegative Matrix Factorization Approach

Fingerprint Presentation Attack Detection: A Sensor and Material Agnostic Approach

Clustering based Contrastive Learning for Improving Face Representations

Adversarial-Prediction Guided Multi-task Adaptation for Semantic Segmentation of Electron Microscopy Images

Cross-domain Face Presentation Attack Detection via Multi-domain Disentangled Representation Learning

Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip

DeepGS: Deep Representation Learning of Graphs and Sequences for Drug-Target Binding Affinity Prediction

Towards Interpretable Sparse Graph Representation Learning with Laplacian Pooling

Towards Achieving Adversarial Robustness by Enforcing Feature Consistency Across Bit Planes

Mapping individual differences in cortical architecture using multi-view representation learning

Depth Selection for Deep ReLU Nets in Feature Extraction and Generalization

Look-into-Object: Self-supervised Structure Modeling for Object Recognition

Gossip and Attend: Context-Sensitive Graph Representation Learning

DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised Representation Learning

Temporal Network Representation Learning via Historical Neighborhoods Aggregation

Towards Shape Biased Unsupervised Representation Learning for Domain Generalization

Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds

Automatic Generation of Chinese Handwriting via Fonts Style Representation Learning

Learning Relational Representations with Auto-encoding Logic Programs

Momentum Contrast for Unsupervised Visual Representation Learning

Modal Regression based Structured Low-rank Matrix Recovery for Multi-view Learning

Neural Transfer Learning for Cry-based Diagnosis of Perinatal Asphyxia

Semantics-Aligned Representation Learning for Person Re-identification

Learning Shape Representations for Clothing Variations in Person Re-Identification

SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition

Self-trained Deep Ordinal Regression for End-to-End Video Anomaly Detection

Deep High-Resolution Representation Learning for Visual Recognition

HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation

A Comparative Study for Unsupervised Network Representation Learning

BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition

Deep Inverse Feature Learning: A Representation Learning of Error

Inverse Feature Learning: Feature learning based on Representation Learning of Error

SCALOR: Generative World Models with Scalable Object Representations

Examining the Use of Temporal-Difference Incremental Delta-Bar-Delta for Real-World Predictive Knowledge Architectures

Contrastive estimation reveals topic posterior information to linear models

Self-Supervised Graph Representation Learning via Global Context Prediction

Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees

VAE/WGAN-Based Image Representation Learning For Pose-Preserving Seamless Identity Replacement In Facial Images

Semantically-Guided Representation Learning for Self-Supervised Monocular Depth

Towards Universal Representation Learning for Deep Face Recognition

A Sample Complexity Separation between Non-Convex and Convex Meta-Learning

Progressive Learning and Disentanglement of Hierarchical Representations

Provable Representation Learning for Imitation Learning via Bi-level Optimization

A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark

Neural Bayes: A Generic Parameterization Method for Unsupervised Representation Learning

Deep Network Classification by Scattering and Homotopy Dictionary Learning

Self-labelling via simultaneous clustering and representation learning

Decoupling Representation and Classifier for Long-Tailed Recognition

Learning Robust Representations via Multi-View Information Bottleneck

V4D:4D Convolutional Neural Networks for Video-level Representation Learning

Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells

Towards a Hypothesis on Visual Transformation based Self-Supervision

Matrix Cofactorization for Joint Representation Learning and Supervised Classification -- Application to Hyperspectral Image Analysis

The Power of Graph Convolutional Networks to Distinguish Random Graph Models: Short Version

AnomalyDAE: Dual autoencoder for anomaly detection on attributed networks

Deep Variational Luenberger-type Observer for Stochastic Video Prediction

Learning spatio-temporal representations with temporal squeeze pooling

Semantic Hierarchy Emerges in Deep Generative Representations for Scene Synthesis

Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control

Non-linear Canonical Correlation Analysis: A Compressed Representation Approach

Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning

Dropout Prediction over Weeks in MOOCs via Interpretable Multi-Layer Representation Learning

Deep Self-Supervised Representation Learning for Free-Hand Sketch

Change your singer: a transfer learning generative adversarial framework for song to song conversion

Semi-supervised Grasp Detection by Representation Learning in a Vector Quantized Latent Space

CSNNs: Unsupervised, Backpropagation-free Convolutional Neural Networks for Representation Learning

Tri-graph Information Propagation for Polypharmacy Side Effect Prediction

Putting An End to End-to-End: Gradient-Isolated Learning of Representations

Target-Embedding Autoencoders for Supervised Representation Learning

On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation

Get Rid of Suspended Animation Problem: Deep Diffusive Neural Network on Graph Semi-Supervised Classification

Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications

Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer

Multi-Level Representation Learning for Deep Subspace Clustering

Charting the Right Manifold: Manifold Mixup for Few-shot Learning

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization

Multilayer Collaborative Low-Rank Coding Network for Robust Deep Subspace Discovery

Convolutional Dictionary Pair Learning Network for Image Representation Learning

Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)

Self-supervised GAN: Analysis and Improvement with Multi-class Minimax Game

Are Disentangled Representations Helpful for Abstract Visual Reasoning?

A Fair Comparison of Graph Neural Networks for Graph Classification

Learning Representations by Maximizing Mutual Information in Variational Autoencoders

Phase Transitions for the Information Bottleneck in Representation Learning

Deep Unsupervised Common Representation Learning for LiDAR and Camera Data using Double Siamese Networks

Video Cloze Procedure for Self-Supervised Spatio-Temporal Learning

Improved Structural Discovery and Representation Learning of Multi-Agent Data

Disentangled Representation Learning with Wasserstein Total Correlation

Deep Self-representative Concept Factorization Network for Representation Learning

On the Global Optima of Kernelized Adversarial Representation Learning

Learning Improved Representations by Transferring Incomplete Evidence Across Heterogeneous Tasks

Attribute-Aware Attention Model for Fine-grained Representation Learning

An Attention-based Graph Neural Network for Heterogeneous Structural Learning

Latent-Space Laplacian Pyramids for Adversarial Representation Learning with 3D Point Clouds

Tracing the Propagation Path: A Flow Perspective of Representation Learning on Graphs

Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition

Discriminative Autoencoder for Feature Extraction: Application to Character Recognition

Multimodal Generative Models for Compositional Representation Learning

Analysis of the Optimization Landscapes for Overcomplete Representation Learning

Unsupervised Feature Selection based on Adaptive Similarity Learning and Subspace Clustering

Informative GANs via Structured Regularization of Optimal Transport

Discovery and Separation of Features for Invariant Representation Learning

XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning

Facial Expression Representation Learning by Synthesizing Expression Images

Representation Learning on Unit Ball with 3D Roto-Translational Equivariance

AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration

Simulating Execution Time of Tensor Programs using Graph Neural Networks

A Preliminary Study of Disentanglement With Insights on the Inadequacy of Metrics

On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset

Deep Image-to-Video Adaptation and Fusion Networks for Action Recognition

Doctor2Vec: Dynamic Doctor Representation Learning for Clinical Trial Recruitment

Discriminative Local Sparse Representation by Robust Adaptive Dictionary Pair Learning

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

Unsupervised Representation Learning by Discovering Reliable Image Relations

DeepPFCN: Deep Parallel Feature Consensus Network For Person Re-Identification

AETv2: AutoEncoding Transformations for Self-Supervised Representation Learning by Minimizing Geodesic Distances in Lie Groups

Every Local Minimum Value is the Global Minimum Value of Induced Model in Non-convex Machine Learning

SynSig2Vec: Learning Representations from Synthetic Dynamic Signatures for Real-world Verification

Explicit Disentanglement of Appearance and Perspective in Generative Models

Hyper-SAGNN: a self-attention based graph neural network for hypergraphs

Disentangling Interpretable Generative Parameters of Random and Real-World Graphs

Learning Robust Global Representations by Penalizing Local Predictive Power

Improving Supervised Phase Identification Through the Theory of Information Losses

Improving Cross-Corpus Speech Emotion Recognition with Adversarial Discriminative Domain Generalization (ADDoG)

Progressive Sample Mining and Representation Learning for One-Shot Person Re-identification with Adversarial Samples

Robust contrastive learning and nonlinear ICA in the presence of outliers

Adversarial Fisher Vectors for Unsupervised Representation Learning

RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment

Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking

Intrinsic dimension of data representations in deep neural networks

Neighborhood Watch: Representation Learning with Local-Margin Triplet Loss and Sampling Strategy for K-Nearest-Neighbor Image Classification

Deep causal representation learning for unsupervised domain adaptation

Improving Discrete Latent Representations With Differentiable Approximation Bridges

Improving Graph Attention Networks with Large Margin-based Constraints

Semi-supervised representation learning via dual autoencoders for domain adaptation

Progressive Unsupervised Person Re-identification by Tracklet Association with Spatio-Temporal Regularization

Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning

Learning Visual Dynamics Models of Rigid Objects using Relational Inductive Biases

TCT: A Cross-supervised Learning Method for Multimodal Sequence Representation

Reconstructing Perceived Images from Brain Activity by Visually-guided Cognitive Representation and Adversarial Learning

Drivers Drowsiness Detection using Condition-Adaptive Representation Learning Framework

Enforcing Linearity in DNN succours Robustness and Adversarial Image Generation

Learning Interpretable Disease Self-Representations for Drug Repositioning

Decoupling feature propagation from the design of graph auto-encoders

Graph Embedding VAE: A Permutation Invariant Model of Graph Structure

Learning protein sequence embeddings using information from structure

Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs

Mixed Pooling Multi-View Attention Autoencoder for Representation Learning in Healthcare

Bayesian Neural Decoding Using A Diversity-Encouraging Latent Representation Learning Method

Neighborhood Growth Determines Geometric Priors for Relational Representation Learning

On the Interpretability and Evaluation of Graph Representation Learning

Improving Generalization of Deep Neural Networks by Leveraging Margin Distribution

Representation Learning of EHR Data via Graph-Based Medical Entity Embedding

Rethinking Kernel Methods for Node Representation Learning on Graphs

Semi-Supervised Domain Adaptation with Representation Learning for Semantic Segmentation across Time

High Mutual Information in Representation Learning with Symmetric Variational Inference

Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks

Spread-gram: A spreading-activation schema of network structural learning

Representation Learning with Autoencoders for Electronic Health Records: A Comparative Study

Facial Expression Recognition Using Disentangled Adversarial Learning

Representation Learning with Ordered Relation Paths for Knowledge Graph Completion

Deep Semantic Multimodal Hashing Network for Scalable Multimedia Retrieval

CNN-based RGB-D Salient Object Detection: Learn, Select and Fuse

HyperLearn: A Distributed Approach for Representation Learning in Datasets With Many Modalities

Symmetry-Based Disentangled Representation Learning requires Interaction with Environments

Dual Encoder-Decoder based Generative Adversarial Networks for Disentangled Facial Representation Learning

Weighed Domain-Invariant Representation Learning for Cross-domain Sentiment Analysis

UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial Cross-Task Distillation

Computer Vision and Metrics Learning for Hypothesis Testing: An Application of Q-Q Plot for Normality Test

PedHunter: Occlusion Robust Pedestrian Detector in Crowded Scenes

Semantic and Visual Similarities for Efficient Knowledge Transfer in CNN Training

Distributed representation of patients and its use for medical cost prediction

VideoBERT: A Joint Model for Video and Language Representation Learning

WSOD^2: Learning Bottom-up and Top-down Objectness Distillation for Weakly-supervised Object Detection

Unsupervised speech representation learning using WaveNet autoencoders

Deconfounding age effects with fair representation learning when assessing dementia

Discriminative Video Representation Learning Using Support Vector Classifiers

Improving Disentangled Representation Learning with the Beta Bernoulli Process

A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text

Self-Supervised Representation Learning via Neighborhood-Relational Encoding

Residual or Gate? Towards Deeper Graph Neural Networks for Inductive Graph Representation Learning

Adaptive Structure-constrained Robust Latent Low-Rank Coding for Image Recovery

Communal Domain Learning for Registration in Drifted Image Spaces

Learning Semantic-Specific Graph Representation for Multi-Label Image Recognition

Dynamic Environment Prediction in Urban Scenes using Recurrent Representation Learning

ChainNet: Learning on Blockchain Graphs with Topological Features

Structural Health Monitoring of Cantilever Beam, a Case Study -- Using Bayesian Neural Network AND Deep Learning

Learning Target-oriented Dual Attention for Robust RGB-T Tracking

A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification

To Beta or Not To Beta: Information Bottleneck for DigitaL Image Forensics

Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning

Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization

Unsupervised Learning of Depth and Deep Representation for Visual Odometry from Monocular Videos in a Metric Space

Robust Subspace Discovery by Block-diagonal Adaptive Locality-constrained Representation

Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and Generation

Learning Lightweight Lane Detection CNNs by Self Attention Distillation

Graph Neural Networks for Small Graph and Giant Network Representation Learning: An Overview

Multi-task Self-Supervised Learning for Human Activity Detection

Bayesian semi-supervised learning for uncertainty-calibrated prediction of molecular properties and active learning

Shared Generative Latent Representation Learning for Multi-view Clustering

Semi-Supervised Learning by Disentangling and Self-Ensembling Over Stochastic Latent Space

Product of Orthogonal Spheres Parameterization for Disentangled Representation Learning

Snomed2Vec: Random Walk and Poincaré Embeddings of a Clinical Knowledge Base for Healthcare Analytics

Medical Concept Representation Learning from Claims Data and Application to Health Plan Payment Risk Adjustment

Quantifying Error in the Presence of Confounders for Causal Inference

Learning Representations by Maximizing Mutual Information Across Views

Deep Coupled-Representation Learning for Sparse Linear Inverse Problems with Side Information

Supervise Thyself: Examining Self-Supervised Representations in Interactive Environments

Task-Driven Common Representation Learning via Bridge Neural Network

Connectivity-Optimized Representation Learning via Persistent Homology

Predicting Confusion from Eye-Tracking Data with Recurrent Neural Networks

Boosting Supervision with Self-Supervision for Few-shot Learning

Dynamic Graph Representation Learning via Self-Attention Networks

Network Representation Learning: Consolidation and Renewed Bearing

Learning Spatio-Temporal Representation with Local and Global Diffusion

Autonomous Goal Exploration using Learned Goal Spaces for Visuomotor Skill Acquisition in Robots

Dynamic Network Embedding via Incremental Skip-gram with Negative Sampling

Extracting Visual Knowledge from the Internet: Making Sense of Image Data

Efficient Codebook and Factorization for Second Order Representation Learning

Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity

Representation Learning with Weighted Inner Product for Universal Approximation of General Similarities

Characterizing the Shape of Activation Space in Deep Neural Networks

Unsupervised pre-training helps to conserve views from input distribution

FAVAE: Sequence Disentanglement using Information Bottleneck Principle

Instance-Aware Representation Learning and Association for Online Multi-Person Tracking

Local Label Propagation for Large-Scale Semi-Supervised Learning

Ultrasound Image Representation Learning by Modeling Sonographer Visual Attention

Wyner VAE: Joint and Conditional Generation with Succinct Common Representation Learning

Deep Representation Learning for Road Detection through Siamese Network

Robust Unsupervised Flexible Auto-weighted Local-Coordinate Concept Factorization for Image Clustering

Learning Cross-Domain Representation with Multi-Graph Neural Network

The Journey is the Reward: Unsupervised Learning of Influential Trajectories

OSVNet: Convolutional Siamese Network for Writer Independent Online Signature Verification

Invariant-equivariant representation learning for multi-class data

Can Graph Neural Networks Go "Online"? An Analysis of Pretraining and Inference

Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection

Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness

Federated Multi-task Hierarchical Attention Model for Sensor Analytics

A Wrapped Normal Distribution on Hyperbolic Space for Gradient-Based Learning

PiNet: A Permutation Invariant Graph Neural Network for Graph Classification

Variational Representation Learning for Vehicle Re-Identification

The Missing Data Encoder: Cross-Channel Image Completion\\with Hide-And-Seek Adversarial Network

Deep Generative Model with Beta Bernoulli Process for Modeling and Learning Confounding Factors

A simple yet effective baseline for non-attributed graph classification

Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning

Adversarial Autoencoders for Compact Representations of 3D Point Clouds

Attentive Spatio-Temporal Representation Learning for Diving Classification

Deep Imbalanced Learning for Face Recognition and Attribute Prediction

Semantic Relationships Guided Representation Learning for Facial Action Unit Recognition

ProductNet: a Collection of High-Quality Datasets for Product Representation Learning

Disentangled Representation Learning with Information Maximizing Autoencoder

Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks

XFlow: Cross-modal Deep Neural Networks for Audiovisual Classification

Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization

Learning Spatial Common Sense with Geometry-Aware Recurrent Networks

Self-supervised Spatio-temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics

A Perceptual Prediction Framework for Self Supervised Event Segmentation

Defeats GAN: A Simpler Model Outperforms in Knowledge Representation Learning

Multimodal Representation Learning using Deep Multiset Canonical Correlation

Learning finite-dimensional coding schemes with nonlinear reconstruction maps

Towards Accurate Generative Models of Video: A New Metric & Challenges

High-Level Perceptual Similarity is Enabled by Learning Diverse Tasks

Unsupervised Domain Adaptation using Deep Networks with Cross-Grafted Stacks

AET vs. AED: Unsupervised Representation Learning by Auto-Encoding Transformations rather than Data

Classification of EEG-Based Brain Connectivity Networks in Schizophrenia Using a Multi-Domain Connectome Convolutional Neural Network

Learning Deep Representations with Probabilistic Knowledge Transfer

Large-Margin Multiple Kernel Learning for Discriminative Features Selection and Representation Learning

Multi-Representational Learning for Offline Signature Verification using Multi-Loss Snapshot Ensemble of CNNs

Auto-Encoding Progressive Generative Adversarial Networks For 3D Multi Object Scenes

Learning Feature Relevance Through Step Size Adaptation in Temporal-Difference Learning

End-to-End Efficient Representation Learning via Cascading Combinatorial Optimization

Generalization in Machine Learning via Analytical Learning Theory

Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance

Alternating Synthetic and Real Gradients for Neural Language Modeling

Meta-Learning Update Rules for Unsupervised Representation Learning

A Theoretical Analysis of Contrastive Unsupervised Representation Learning

Deep High-Resolution Representation Learning for Human Pose Estimation

An Effective Hit-or-Miss Layer Favoring Feature Interpretation as Learned Prototypes Deformations

Learning deep representations by mutual information estimation and maximization

Deep Discriminative Representation Learning with Attention Map for Scene Classification

Hierarchical Graph Representation Learning with Differentiable Pooling

Geometry of Deep Generative Models for Disentangled Representations

Learning Compositional Representations of Interacting Systems with Restricted Boltzmann Machines: Comparative Study of Lattice Proteins

Representation Learning for Heterogeneous Information Networks via Embedding Events

BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection

Discovering Underlying Person Structure Pattern with Relative Local Distance for Person Re-identification

Co-Representation Learning For Classification and Novel Class Detection via Deep Networks

Better accuracy with quantified privacy: representations learned via reconstructive adversarial network

Efficient Representation Learning Using Random Walks for Dynamic Graphs

Deep Representation Learning Characterized by Inter-class Separation for Image Clustering

CNN based Multi-Instance Multi-Task Learning for Syndrome Differentiation of Diabetic Patients

DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System

Dropping Convexity for More Efficient and Scalable Online Multiview Learning

MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders

Subspace Match Probably Does Not Accurately Assess the Similarity of Learned Representations

Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems

Volumetric Convolution: Automatic Representation Learning in Unit Ball

Clustering-Oriented Representation Learning with Attractive-Repulsive Loss

Transfer Learning using Representation Learning in Massive Open Online Courses

Multi-focus Image Fusion using dictionary learning and Low-Rank Representation

Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders

Discriminant Patch Representation for RGB-D Face Recognition Using Convolutional Neural Networks

Pre-Trained Convolutional Neural Network Features for Facial Expression Recognition

Evidence Transfer for Improving Clustering Tasks Using External Categorical Evidence

An efficient supervised dictionary learning method for audio signal recognition

Facial Landmark Machines: A Backbone-Branches Architecture with Progressive Representation Learning

Unsupervised Feature Learning of Human Actions as Trajectories in Pose Embedding Manifold

Feed-Forward Neural Networks Need Inductive Bias to Learn Equality Relations

Iterative Reorganization with Weak Spatial Constraints: Solving Arbitrary Jigsaw Puzzles for Unsupervised Representation Learning

Deep Within-Class Covariance Analysis for Robust Audio Representation Learning

Time-Aware and View-Aware Video Rendering for Unsupervised Representation Learning

Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation

Automated Vulnerability Detection in Source Code Using Deep Representation Learning

VIPL-HR: A Multi-modal Database for Pulse Estimation from Less-constrained Face Video

A Differential Topological View of Challenges in Learning with Feedforward Neural Networks

Self-Supervised Video Representation Learning with Space-Time Cubic Puzzles

Unsupervised Multimodal Representation Learning across Medical Images and Reports

Improving Generalization for Abstract Reasoning Tasks Using Disentangled Feature Representations

Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks

Semi-supervised Deep Representation Learning for Multi-View Problems

Identify, locate and separate: Audio-visual object extraction in large video collections using weak supervision

Y^2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences

View Inter-Prediction GAN: Unsupervised Representation Learning for 3D Shapes by Learning Global Shape Memories to Support Local View Predictions

Curiosity Driven Exploration of Learned Disentangled Goal Spaces

Factorised spatial representation learning: application in semi-supervised myocardial segmentation

Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis

Tattoo Image Search at Scale: Joint Detection and Compact Representation Learning

Designing an Effective Metric Learning Pipeline for Speaker Diarization

Weak-supervision for Deep Representation Learning under Class Imbalance

Geometry meets semantics for semi-supervised monocular depth estimation

Reconstruction of Hidden Representation for Robust Feature Extraction

Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier features

Learning Deep Representations for Semantic Image Parsing: a Comprehensive Overview

Unsupervised Learning of Goal Spaces for Intrinsically Motivated Goal Exploration

Trace Quotient with Sparsity Priors for Learning Low Dimensional Image Representations

Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values

Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention

An Ensemble of Transfer, Semi-supervised and Supervised Learning Methods for Pathological Heart Sound Classification

Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition

Target Aware Network Adaptation for Efficient Representation Learning

Detection of Unknown Anomalies in Streaming Videos with Generative Energy-based Boltzmann Models

What Is It Like Down There? Generating Dense Ground-Level Views and Image Features From Overhead Imagery Using Conditional Generative Adversarial Networks

Towards Deep and Representation Learning for Talent Search at LinkedIn

Highly-Economized Multi-View Binary Compression for Scalable Image Clustering

apk2vec: Semi-supervised multi-view representation learning for profiling Android applications

VGAN-Based Image Representation Learning for Privacy-Preserving Facial Expression Recognition

BiasedWalk: Biased Sampling for Representation Learning on Graphs

Multi-view Factorization AutoEncoder with Network Constraints for Multi-omic Integrative Analysis

Learning Discriminative Representation with Signed Laplacian Restricted Boltzmann Machine

Neural-Brane: Neural Bayesian Personalized Ranking for Attributed Network Embedding

Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies

Fine-Grained Representation Learning and Recognition by Exploiting Hierarchical Semantic Embedding

Contemplating Visual Emotions: Understanding and Overcoming Dataset Bias

Learning disentangled representation from 12-lead electrograms: application in localizing the origin of Ventricular Tachycardia

SSIMLayer: Towards Robust Deep Representation Learning via Nonlinear Structural Similarity

Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification

LinkNBed: Multi-Graph Representation Learning with Entity Linkage

InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender Diversity

Representation Learning and Pairwise Ranking for Implicit Feedback in Recommendation Systems

A Generic Approach to Lung Field Segmentation from Chest Radiographs using Deep Space and Shape Learning

Weakly Supervised Representation Learning for Unsynchronized Audio-Visual Events

Domain Adaptation Meets Disentangled Representation Learning and Style Transfer

Unsupervised Learning for Cell-level Visual Representation in Histopathology Images with Generative Adversarial Networks

Learning Personalized Representation for Inverse Problems in Medical Imaging Using Deep Neural Network

Knowledge-Embedded Representation Learning for Fine-Grained Image Recognition

Emergence of Invariance and Disentanglement in Deep Representations

Representation Learning on Graphs with Jumping Knowledge Networks

InfoCatVAE: Representation Learning with Categorical Variational Autoencoders

SATR-DL: Improving Surgical Skill Assessment and Task Recognition in Robot-assisted Surgery with Deep Neural Networks

Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection

Learning Representations and Generative Models for 3D Point Clouds

Pixels, voxels, and views: A study of shape representations for single view 3D object shape prediction

Learning a Discriminative Filter Bank within a CNN for Fine-grained Recognition

GESF: A Universal Discriminative Mapping Mechanism for Graph Representation Learning

An Interpretable Deep Hierarchical Semantic Convolutional Neural Network for Lung Nodule Malignancy Classification

Disentangling by Partitioning: A Representation Learning Framework for Multimodal Sensory Data

Object-Level Representation Learning for Few-Shot Image Classification

Vehicle Instance Segmentation from Aerial Image and Video Using a Multi-Task Learning Residual Fully Convolutional Network

GEN Model: An Alternative Approach to Deep Neural Network Models

Feature Affinity based Pseudo Labeling for Semi-supervised Person Re-identification

Differentiating Objects by Motion: Joint Detection and Tracking of Small Flying Objects

Deep Attentional Structured Representation Learning for Visual Recognition

Unsupervised Representation Learning with Laplacian Pyramid Auto-encoders

Exploring object-centric and scene-centric CNN features and their complementarity for human rights violations recognition in images

Unsupervised learning for concept detection in medical images: a comparative analysis

t-PINE: Tensor-based Predictable and Interpretable Node Embeddings

Large-Scale Unsupervised Deep Representation Learning for Brain Structure

Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation

Deep Co-attention based Comparators For Relative Representation Learning in Person Re-identification

Better and Faster: Knowledge Transfer from Multiple Self-supervised Learning Tasks via Graph Distillation for Video Classification

Competitive Learning Enriches Learning Representation and Accelerates the Fine-tuning of CNNs

Unsupervised Disentangled Representation Learning with Analogical Relations

Fixed-sized representation learning from Offline Handwritten Signatures of different sizes

Learning Sparse Latent Representations with the Deep Copula Information Bottleneck

PM-GANs: Discriminative Representation Learning for Action Recognition Using Partial-modalities

Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images

TIDBD: Adapting Temporal-difference Step-sizes Through Stochastic Meta-descent

Jointly Discovering Visual Objects and Spoken Words from Raw Sensory Input

TVAE: Triplet-Based Variational Autoencoder using Metric Learning

Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation

DNA-GAN: Learning Disentangled Representations from Multi-Attribute Images

A Dataset To Evaluate The Representations Learned By Video Prediction Models

Unsupervised Representation Learning by Predicting Image Rotations

How Much Chemistry Does a Deep Neural Network Need to Know to Make Accurate Predictions?

Deep Component Analysis via Alternating Direction Neural Networks

Wasserstein Distance Guided Representation Learning for Domain Adaptation

Linear-Time Sequence Classification using Restricted Boltzmann Machines

Cross-Paced Representation Learning with Partial Curricula for Sketch-based Image Retrieval

Learning Weighted Representations for Generalization Across Designs

Learning Anonymized Representations with Adversarial Neural Networks

The Role of Information Complexity and Randomization in Representation Learning

Information-Theoretic Representation Learning for Positive-Unlabeled Classification

Learning Image Representations by Completing Damaged Jigsaw Puzzles

Joint Binary Neural Network for Multi-label Learning with Applications to Emotion Classification

Learning Deep Structured Multi-Scale Features using Attention-Gated CRFs for Contour Prediction

Learning Deep Similarity Models with Focus Ranking for Fabric Image Retrieval

Neural Networks Regularization Through Class-wise Invariant Representation Learning

Predictive Learning: Using Future Representation Learning Variantial Autoencoder for Human Action Prediction

Learning Sparse Adversarial Dictionaries For Multi-Class Audio Classification

ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events

GraphGAN: Graph Representation Learning with Generative Adversarial Nets

MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification

3D Shape Classification Using Collaborative Representation based Projections

Deep Representation Learning with Part Loss for Person Re-Identification

Scale out for large minibatch SGD: Residual network training on ImageNet-1K with improved accuracy and reduced time to train

Common Representation Learning Using Step-based Correlation Multi-Modal CNN

Learning Deep Context-aware Features over Body and Latent Parts for Person Re-identification

RUM: network Representation learning throUgh Multi-level structural information preservation

Content-Adaptive Sketch Portrait Generation by Decompositional Representation Learning

Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach

A Framework for Generalizing Graph-based Representation Learning Methods

Learning Edge Representations via Low-Rank Asymmetric Projections

GLAD: Global-Local-Alignment Descriptor for Pedestrian Retrieval

Une véritable approche $\ell_0$ pour l'apprentissage de dictionnaire

Learning Multi-level Features For Sensor-based Human Action Recognition

Acoustic Feature Learning via Deep Variational Canonical Correlation Analysis

Nonparametric Variational Auto-encoders for Hierarchical Representation Learning

Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles

Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro

Discovery of Visual Semantics by Unsupervised and Self-Supervised Representation Learning

Nonnegative Restricted Boltzmann Machines for Parts-based Representations Discovery and Predictive Model Stabilization

Statistical Latent Space Approach for Mixed Data Modelling and Applications

Transitive Invariance for Self-supervised Visual Representation Learning

Style2Vec: Representation Learning for Fashion Items from Style Sets

CNN-Based Joint Clustering and Representation Learning with Feature Drift Compensation for Large-Scale Image Data

A Bayesian Approach to Policy Recognition and State Representation Learning

Revisiting Unreasonable Effectiveness of Data in Deep Learning Era

Representation-Aggregation Networks for Segmentation of Multi-Gigapixel Histology Images

Video Representation Learning and Latent Concept Mining for Large-scale Multi-label Video Classification

Improving Robustness of Feature Representations to Image Deformations using Powered Convolution in CNNs

Traffic scene recognition based on deep cnn and vlad spatial pyramids

Video Question Answering via Attribute-Augmented Attention Network Learning

Procedural Generation of Videos to Train Deep Action Recognition Networks

Discriminative Block-Diagonal Representation Learning for Image Recognition

Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations

Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks

Medical Concept Representation Learning from Electronic Health Records and its Application on Heart Failure Prediction

Learning Continuous Semantic Representations of Symbolic Expressions

Progressive Neural Networks for Transfer Learning in Emotion Recognition

End-to-end Binary Representation Learning via Direct Binary Embedding

Adapting Deep Visuomotor Representations with Weak Pairwise Constraints

Revealing Hidden Potentials of the q-Space Signal in Breast Cancer

Just DIAL: DomaIn Alignment Layers for Unsupervised Domain Adaptation

Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction

End-to-end representation learning for Correlation Filter based tracking

Stochastic Descent Analysis of Representation Learning Algorithms

Deep representation learning for human motion prediction and classification

Self-Supervised Video Representation Learning With Odd-One-Out Networks

GRAM: Graph-based Attention Model for Healthcare Representation Learning

An Information-Theoretic Framework for Fast and Robust Unsupervised Learning via Neural Population Infomax

Clustering-Based Relational Unsupervised Representation Learning with an Explicit Distributed Representation

On the Limits of Learning Representations with Label-Based Supervision

Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation

Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning

A Theoretical Framework for Robustness of (Deep) Classifiers against Adversarial Examples

Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World

Deep Multi-task Representation Learning: A Tensor Factorisation Approach

Information Dropout: Learning Optimal Representations Through Noisy Computation

Triplet Probabilistic Embedding for Face Verification and Clustering

Autoencoder Regularized Network For Driving Style Representation Learning

Structured Dropout for Weak Label and Multi-Instance Learning and Its Application to Score-Informed Source Separation

Image-Text Multi-Modal Representation Learning by Adversarial Backpropagation

A Survey of Inductive Biases for Factorial Representation-Learning

An Overview on Data Representation Learning: From Traditional Feature Learning to Recent Deep Learning

Deep Models for Engagement Assessment With Scarce Label Information

Towards Representation Learning with Tractable Probabilistic Models

Adapting Deep Network Features to Capture Psychological Representations

Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalization

The Curious Robot: Learning Visual Representations via Physical Interactions

Local- and Holistic- Structure Preserving Image Super Resolution via Deep Joint Component Learning

A Distributed Deep Representation Learning Model for Big Image Data Classification

Theory reconstruction: a representation learning view on predicate invention

Walk and Learn: Facial Attribute Representation Learning from Egocentric Video and Contextual Data

Joint Unsupervised Learning of Deep Representations and Image Clusters

Scalable Out-of-Sample Extension of Graph Embeddings Using Deep Neural Networks

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

Cross-Domain Visual Matching via Generalized Similarity Measure and Feature Learning

Common Variable Learning and Invariant Representation Learning using Siamese Neural Networks

DARI: Distance metric And Representation Integration for Person Verification

Deep Ranking for Person Re-identification via Joint Representation Learning

Convergent Learning: Do different neural networks learn the same representations?

The ImageNet Shuffle: Reorganized Pre-training for Video Event Detection

On Deep Multi-View Representation Learning: Objectives and Optimization

Unsupervised Visual Representation Learning by Context Prediction

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

DISC: Deep Image Saliency Computing via Progressive Representation Learning

Window-Object Relationship Guided Representation Learning for Generic Object Detections

Human Curation and Convnets: Powering Item-to-Item Recommendations on Pinterest

Stochastic Optimization for Deep CCA via Nonlinear Orthogonal Iterations

Deep Convolutional Features for Image Based Retrieval and Scene Categorization

CURL: Co-trained Unsupervised Representation Learning for Image Classification

End-to-End Photo-Sketch Generation via Fully Convolutional Representation Learning

Maximum Entropy Linear Manifold for Learning Discriminative Low-dimensional Representation

Representation Learning with Deep Extreme Learning Machines for Efficient Image Set Classification

Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning

Shared Representation Learning for Heterogeneous Face Recognition

Image Representation Learning Using Graph Regularized Auto-Encoders

Learning Deep Representation Without Parameter Inference for Nonlinear Dimensionality Reduction

Constructing Hierarchical Image-tags Bimodal Representations for Word Tags Alternative Choice

Challenges in Representation Learning: A report on three machine learning contests

Horizontal and Vertical Ensemble with Deep Representation for Classification

Paint4Poem: A Dataset for Artistic Visualization of Classical Chinese Poems

ISF-GAN: An Implicit Style Function for High-Resolution Image-to-Image Translation

Imaginative Walks: Generative Random Walk Deviation Loss for Improved Unseen Learning Representation

LDC-VAE: A Latent Distribution Consistency Approach to Variational AutoEncoders

Towards Discovery and Attribution of Open-world GAN Generated Images

Contrastive Counterfactual Visual Explanations With Overdetermination

On the Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars

PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering

$(f,Γ)$-Divergences: Interpolating between $f$-Divergences and Integral Probability Metrics

ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models

Towards Understanding the Generative Capability of Adversarially Robust Classifiers

The State of the Art when using GPUs in Devising Image Generation Methods Using Deep Learning

Just Noticeable Difference for Machine Perception and Generation of Regularized Adversarial Images with Minimal Perturbation

AWGAN: Empowering High-Dimensional Discriminator Output for Generative Adversarial Networks

Towards Learning a Vocabulary of Visual Concepts and Operators using Deep Neural Networks

Exploring DeshuffleGANs in Self-Supervised Generative Adversarial Networks

Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-on and Outfit Editing

Continuous Conditional Generative Adversarial Networks: Novel Empirical Losses and Label Input Mechanisms

Enlisting 3D Crop Models and GANs for More Data Efficient and Generalizable Fruit Detection

Manifold Matching via Deep Metric Learning for Generative Modeling

AttrLostGAN: Attribute Controlled Image Synthesis from Reconfigurable Layout and Style

Heredity-aware Child Face Image Generation with Latent Space Disentanglement

Drop the GAN: In Defense of Patches Nearest Neighbors as Single Image Generative Models

Dual Projection Generative Adversarial Networks for Conditional Image Generation

ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis

Progressive and Selective Fusion Network for High Dynamic Range Imaging

Unsupervised Image Generation with Infinite Generative Adversarial Networks

Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation

Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation

Interpreting Generative Adversarial Networks for Interactive Image Generation

Intelligent Railway Foreign Object Detection: A Semi-supervised Convolutional Autoencoder Based Method

Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving

A universal detector of CNN-generated images using properties of checkerboard artifacts in the frequency domain

Training face verification models from generated face identity data

CRD-CGAN: Category-Consistent and Relativistic Constraints for Diverse Text-to-Image Generation

Subjective evaluation of traditional and learning-based image coding methods

Realistic River Image Synthesis using Deep Generative Adversarial Networks

MOGAN: Morphologic-structure-aware Generative Learning from a Single Image

Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and Translation

Black-Box Diagnosis and Calibration on GAN Intra-Mode Collapse: A Pilot Study

Few Shots Is All You Need: A Progressive Few Shot Learning Approach for Low Resource Handwriting Recognition

DynaDog+T: A Parametric Animal Model for Synthetic Canine Image Generation

SynthTIGER: Synthetic Text Image GEneratoR Towards Better Text Recognition Models

Audio2Head: Audio-driven One-shot Talking-head Generation with Natural Head Motion

ZstGAN: An Adversarial Approach for Unsupervised Zero-Shot Image-to-Image Translation

CORAL: Colored structural representation for bi-modal place recognition

Scene Graph to Image Generation with Contextualized Object Layout Refinement

Generating Annotated High-Fidelity Images Containing Multiple Coherent Objects

Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions

Coupled VAE: Improved Accuracy and Robustness of a Variational Autoencoder

Deep Image Synthesis from Intuitive User Input: A Review and Perspectives

Grid Partitioned Attention: Efficient TransformerApproximation with Inductive Bias for High Resolution Detail Generation

FBC-GAN: Diverse and Flexible Image Synthesis via Foreground-Background Composition

Bi-level Feature Alignment for Versatile Image Translation and Manipulation

DocSynth: A Layout Guided Approach for Controllable Document Image Synthesis

On The Distribution of Penultimate Activations of Classification Networks

S2FGAN: Semantically Aware Interactive Sketch-to-Face Translation

NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation

Fairness for Image Generation with Uncertain Sensitive Attributes

Generative Max-Mahalanobis Classifiers for Image Classification, Generation and More

SDL: New data generation tools for full-level annotated document layout

TiVGAN: Text to Image to Video Generation with Step-by-Step Evolutionary Generator

Dual-Stream Reciprocal Disentanglement Learning for Domain Adaption Person Re-Identification

Where is the disease? Semi-supervised pseudo-normality synthesis from an abnormal image

Blur, Noise, and Compression Robust Generative Adversarial Networks

Leveraging Conditional Generative Models in a General Explanation Framework of Classifier Decisions

Total Generate: Cycle in Cycle Generative Adversarial Networks for Generating Human Faces, Hands, Bodies, and Natural Scenes

Towards interpreting computer vision based on transformation invariant optimization

Closing the Reality Gap with Unsupervised Sim-to-Real Image Translation

Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images

Flow Guided Transformable Bottleneck Networks for Motion Retargeting

Weakly-Supervised Photo-realistic Texture Generation for 3D Face Reconstruction

D2C: Diffusion-Denoising Models for Few-shot Conditional Generation

Toward Accurate and Realistic Outfits Visualization with Attention to Details

AFAN: Augmented Feature Alignment Network for Cross-Domain Object Detection

Enhance Convolutional Neural Networks with Noise Incentive Block

Efficient training for future video generation based on hierarchical disentangled representation of latent variables

High Resolution Solar Image Generation using Generative Adversarial Networks

Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark

Controllable Person Image Synthesis with Spatially-Adaptive Warped Normalization

Pose Invariant Person Re-Identification using Robust Pose-transformation GAN

Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks

Adaptive Weighted Discriminator for Training Generative Adversarial Networks

Testing Deep Learning Models for Image Analysis Using Object-Relevant Metamorphic Relations

CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes

Training Generative Adversarial Networks via stochastic Nash games

An Optical physics inspired CNN approach for intrinsic image decomposition

BodyPressure -- Inferring Body Pose and Contact Pressure from a Depth Image

A Decade Survey of Content Based Image Retrieval using Deep Learning

Decorating Your Own Bedroom: Locally Controlling Image Generation with Generative Adversarial Networks

TransferI2I: Transfer Learning for Image-to-Image Translation from Small Datasets

Directional GAN: A Novel Conditioning Strategy for Generative Networks

GAN Prior Embedded Network for Blind Face Restoration in the Wild

A Good Image Generator Is What You Need for High-Resolution Video Synthesis

TREND: Truncated Generalized Normal Density Estimation of Inception Embeddings for Accurate GAN Evaluation

Learned Spatial Representations for Few-shot Talking-Head Synthesis

Pose-driven Attention-guided Image Generation for Person Re-Identification

DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network

M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection

Data-driven vehicle speed detection from synthetic driving simulator images

Coarse-to-Fine Searching for Efficient Generative Adversarial Networks

Towards Open-World Text-Guided Face Image Generation and Manipulation

HoughNet: Integrating near and long-range evidence for visual detection

Learning Semantic Person Image Generation by Region-Adaptive Normalization

DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific Delta

Automatic Correction of Internal Units in Generative Neural Networks

Event-based Timestamp Image Encoding Network for Human Action Recognition and Anticipation

Deep-Masking Generative Network: A Unified Framework for Background Restoration from Superimposed Images

SIGAN: A Novel Image Generation Method for Solar Cell Defect Segmentation and Augmentation

MUST-GAN: Multi-level Statistics Transfer for Self-driven Person Image Generation

Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning

A Novel Measure to Evaluate Generative Adversarial Networks Based on Direct Analysis of Generated Images

Searching towards Class-Aware Generators for Conditional Generative Adversarial Networks

Geometry-Guided Street-View Panorama Synthesis from Satellite Imagery

CAMPARI: Camera-Aware Decomposed Generative Neural Radiance Fields

Efficient Conditional GAN Transfer with Knowledge Propagation across Classes

Multi-Class Multi-Instance Count Conditioned Adversarial Image Generation

Identity-Aware CycleGAN for Face Photo-Sketch Synthesis and Recognition

Classification of Seeds using Domain Randomization on Self-Supervised Learning Frameworks

PeaceGAN: A GAN-based Multi-Task Learning Method for SAR Target Image Generation with a Pose Estimator and an Auxiliary Classifier

Improving the Fairness of Deep Generative Models without Retraining

TediGAN: Text-Guided Diverse Face Image Generation and Manipulation

Monocular 3D Vehicle Detection Using Uncalibrated Traffic Cameras through Homography

HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color Histograms

Few-Shot Human Motion Transfer by Personalized Geometry and Texture Modeling

Soft-IntroVAE: Analyzing and Improving the Introspective Variational Autoencoder

DF-GAN: Deep Fusion Generative Adversarial Networks for Text-to-Image Synthesis

SETGAN: Scale and Energy Trade-off GANs for Image Applications on Mobile Platforms

Context-Aware Layout to Image Generation with Enhanced Object Appearance

Progressive and Aligned Pose Attention Transfer for Person Image Generation

Biologically Inspired Hexagonal Deep Learning for Hexagonal Image Generation

Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling

Rotation Differential Invariants of Images Generated by Two Fundamental Differential Operators

Unsupervised Image Transformation Learning via Generative Adversarial Networks

Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN

Systematic Analysis and Removal of Circular Artifacts for StyleGAN

Bulk Production Augmentation Towards Explainable Melanoma Diagnosis

Deblurring Processor for Motion-Blurred Faces Based on Generative Adversarial Networks

Railway Anomaly detection model using synthetic defect images generated by CycleGAN

Style and Pose Control for Image Synthesis of Humans from a Single Monocular View

Towards a Neural Graphics Pipeline for Controllable Image Generation

Pose Guided Person Image Generation with Hidden p-Norm Regression

Preventing Posterior Collapse Induced by Oversmoothing in Gaussian VAE

Diverse Single Image Generation with Controllable Global Structure through Self-Attention

Score-Based Generative Modeling through Stochastic Differential Equations

Structure-aware Person Image Generation with Pose Decomposition and Semantic Correlation

ContraGAN: Contrastive Learning for Conditional Image Generation

Self-Supervised 2D Image to 3D Shape Translation with Disentangled Representations

Non-uniform Motion Deblurring with Blurry Component Divided Guidance

Synthetic Glacier SAR Image Generation from Arbitrary Masks Using Pix2Pix Algorithm

A Pipeline for Vision-Based On-Orbit Proximity Operations Using Deep Learning and Synthetic Imagery

Cycle Generative Adversarial Networks Algorithm With Style Transfer For Image Generation

ArrowGAN : Learning to Generate Videos by Learning Arrow of Time

Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed

Guiding GANs: How to control non-conditional pre-trained GANs for conditional image generation

Generative Adversarial Networks in Computer Vision: A Survey and Taxonomy

Correspondence Learning for Controllable Person Image Generation

GuidedStyle: Attribute Knowledge Guided Style Manipulation for Semantic Face Editing

Multi-Head Linear Attention Generative Adversarial Network for Thin Cloud Removal

Self-supervised monocular depth estimation from oblique UAV videos

Combating Mode Collapse in GAN training: An Empirical Analysis using Hessian Eigenvalues

Fake face detection via adaptive manipulation traces extraction network

privGAN: Protecting GANs from membership inference attacks at low cost

Analyzing and Improving Generative Adversarial Training for Generative Modeling and Out-of-Distribution Detection

Intrinsic Temporal Regularization for High-resolution Human Video Synthesis

MorphGAN: One-Shot Face Synthesis GAN for Detecting Recognition Bias

Full-Glow: Fully conditional Glow for more realistic image generation

NightVision: Generating Nighttime Satellite Imagery from Infra-Red Observations

Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction

MPG: A Multi-ingredient Pizza Image Generator with Conditional StyleGANs

CIT-GAN: Cyclic Image Translation Generative Adversarial Network With Application in Iris Presentation Attack Detection

StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation

Attributes Aware Face Generation with Generative Adversarial Networks

Learning geometry-image representation for 3D point cloud generation

Tractable loss function and color image generation of multinary restricted Boltzmann machine

Adaptive Multiplane Image Generation from a Single Internet Picture

Coarse-to-Fine Gaze Redirection with Numerical and Pictorial Guidance

Augmentation-Interpolative AutoEncoders for Unsupervised Few-Shot Image Generation

InfoMax-GAN: Improved Adversarial Image Generation via Information Maximization and Contrastive Learning

Cycle-Consistent Generative Rendering for 2D-3D Modality Translation

Adversarial symmetric GANs: bridging adversarial samples and adversarial networks

Local Anomaly Detection in Videos using Object-Centric Adversarial Learning

Network-to-Network Translation with Conditional Invertible Neural Networks

Two-Stream Appearance Transfer Network for Person Image Generation

CooGAN: A Memory-Efficient Framework for High-Resolution Facial Attribute Editing

MichiGAN: Multi-Input-Conditioned Hair Image Generation for Portrait Editing

Leveraging Visual Question Answering to Improve Text-to-Image Synthesis

Efficient Content-Based Sparse Attention with Routing Transformers

One Model to Reconstruct Them All: A Novel Way to Use the Stochastic Noise in StyleGAN

JGAN: A Joint Formulation of GAN for Synthesizing Images and Labels

LT-GAN: Self-Supervised GAN with Latent Transformation Detection

New Ideas and Trends in Deep Multimodal Content Understanding: A Review

Learning Energy-Based Models as Generative ConvNets via Multi-grid Modeling and Sampling

Towards Understanding Pixel Vulnerability under Adversarial Attacks for Images

LASSR: Effective Super-Resolution Method for Plant Disease Diagnosis

Adversarial score matching and improved sampling for image generation

Warp and Learn: Novel Views Generation for Vehicles and Other Objects

Hyperspectral Unmixing via Nonnegative Matrix Factorization with Handcrafted and Learnt Priors

SESAME: Semantic Editing of Scenes by Adding, Manipulating or Erasing Objects

Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein

MM-Hand: 3D-Aware Multi-Modal Guided Hand Generative Network for 3D Hand Pose Synthesis

MGD-GAN: Text-to-Pedestrian generation through Multi-Grained Discrimination

X-LXMERT: Paint, Caption and Answer Questions with Multi-Modal Transformers

Causal Adversarial Network for Learning Conditional and Interventional Distributions

FakeRetouch: Evading DeepFakes Detection via the Guidance of Deliberate Noise

Understanding the Role of Individual Units in a Deep Neural Network

Adversarial Image Generation and Training for Deep Neural Networks

Disentangled and Controllable Face Image Generation via 3D Imitative-Contrastive Learning

Simulation of an Elevator Group Control Using Generative Adversarial Networks and Related AI Tools

Unified Generative Adversarial Networks for Controllable Image-to-Image Translation

GreyReID: A Two-stream Deep Framework with RGB-grey Information for Person Re-identification

Deep Spatial Transformation for Pose-Guided Person Image Generation and Animation

Anime-to-Real Clothing: Cosplay Costume Generation via Image-to-Image Translation

What makes fake images detectable? Understanding properties that generalize

Learning Canonical Representations for Scene Graph to Image Generation

Person image generation with semantic attention network for person re-identification

FakePolisher: Making DeepFakes More Detection-Evasive by Shallow Reconstruction

Structure-Aware Network for Lane Marker Extraction with Dynamic Vision Sensor

Road Segmentation for Remote Sensing Images using Adversarial Spatial Pyramid Networks

FDFtNet: Facing Off Fake Images using Fake Detection Fine-tuning Network

Block Shuffle: A Method for High-resolution Fast Style Transfer with Limited Memory

Fighting Deepfake by Exposing the Convolutional Traces on Images

Image Generation for Efficient Neural Network Training in Autonomous Drone Racing

GL-GAN: Adaptive Global and Local Bilevel Optimization model of Image Generation

Towards Purely Unsupervised Disentanglement of Appearance and Shape for Person Images Generation

Generative networks as inverse problems with fractional wavelet scattering networks

HoughNet: Integrating near and long-range evidence for bottom-up object detection

Interpreting the Latent Space of GANs via Correlation Analysis for Controllable Concept Manipulation

Generative Modeling by Inclusive Neural Random Fields with Applications in Image Generation and Anomaly Detection

GANwriting: Content-Conditioned Generation of Styled Handwritten Word Images

Controlling Style and Semantics in Weakly-Supervised Image Generation

Incorporating Reinforced Adversarial Learning in Autoregressive Image Generation

Benefiting Deep Latent Variable Models via Learning the Prior and Removing Latent Regularization

Rethinking Image Inpainting via a Mutual Encoder-Decoder with Feature Equalizations

OneGAN: Simultaneous Unsupervised Learning of Conditional Image Generation, Foreground Segmentation, and Fine-Grained Clustering

An Open-source Tool for Hyperspectral Image Augmentation in Tensorflow

PerceptionGAN: Real-world Image Construction from Provided Text through Perceptual Understanding

Method for the generation of depth images for view-based shape retrieval of 3D CAD model from partial point cloud

MetalGAN: Multi-Domain Label-Less Image Synthesis Using cGANs and Meta-Learning

Diffusion-Weighted Magnetic Resonance Brain Images Generation with Generative Adversarial Networks and Variational Autoencoders: A Comparison Study

Fast Mixing of Multi-Scale Langevin Dynamics under the Manifold Hypothesis

A Characteristic Function Approach to Deep Implicit Generative Modeling

Deep Learning based Segmentation of Fish in Noisy Forward Looking MBES Images

DeshuffleGAN: A Self-Supervised GAN to Improve Structure Learning

StrokeCoder: Path-Based Image Generation from Single Examples using Transformers

Speech Fusion to Face: Bridging the Gap Between Human's Vocal Characteristics and Facial Imaging

Adversarial Attacks on Brain-Inspired Hyperdimensional Computing-Based Classifiers

A Robust Attentional Framework for License Plate Recognition in the Wild

RIT-Eyes: Rendering of near-eye images for eye-tracking applications

SegAttnGAN: Text to Image Generation with Segmentation Attention

QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks

deepSELF: An Open Source Deep Self End-to-End Learning Framework

Conditional Image Generation and Manipulation for User-Specified Content

Generating Memorable Images Based on Human Visual Memory Schemas

Disentangled Image Generation Through Structured Noise Injection

Illumination-Invariant Image from 4-Channel Images: The Effect of Near-Infrared Data in Shadow Removal

A Disentangling Invertible Interpretation Network for Explaining Latent Representations

Learning Spatial Relationships between Samples of Patent Image Shapes

Stomach 3D Reconstruction Based on Virtual Chromoendoscopic Image Generation

Evolving the pulmonary nodules diagnosis from classical approaches to deep learning aided decision support: three decades development course and future prospect

AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identification

Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images using a View-based Representation

Cycle In Cycle Generative Adversarial Networks for Keypoint-Guided Image Generation

A recurrent cycle consistency loss for progressive face-to-face synthesis

MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation

Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer

Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator

Bodies at Rest: 3D Human Pose and Shape Estimation from a Pressure Image using Synthetic Data

Object-Centric Image Generation with Factored Depths, Locations, and Appearances

Evading Deepfake-Image Detectors with White- and Black-Box Attacks

Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation

Edge Guided GANs with Semantic Preserving for Semantic Image Synthesis

Image Generation Via Minimizing Fréchet Distance in Discriminator Feature Space

DCDLearn: Multi-order Deep Cross-distance Learning for Vehicle Re-Identification

BachGAN: High-Resolution Image Synthesis from Salient Object Layout

Toward Accurate and Realistic Virtual Try-on Through Shape Matching and Multiple Warps

Progressive Cross-camera Soft-label Learning for Semi-supervised Person Re-identification

Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis

When Relation Networks meet GANs: Relation GANs with Triplet Loss

Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification

BigGAN-based Bayesian reconstruction of natural images from human brain activity

Deep Domain-Adversarial Image Generation for Domain Generalisation

i3PosNet: Instrument Pose Estimation from X-Ray in temporal bone surgery

Distilling portable Generative Adversarial Networks for Image Translation

MsCGAN: Multi-scale Conditional Generative Adversarial Networks for Person Image Generation

Cross-Spectrum Dual-Subspace Pairing for RGB-infrared Cross-Modality Person Re-Identification

Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation

Performance Evaluation of Deep Generative Models for Generating Hand-Written Character Images

Stochastic Conditional Generative Networks with Basis Decomposition

Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators

Cross-Modality Paired-Images Generation for RGB-Infrared Person Re-Identification

Unsupervised Image-generation Enhanced Adaptation for Object Detection in Thermal images

Image Outpainting and Harmonization using Generative Adversarial Networks

Exocentric to Egocentric Image Generation via Parallel Generative Adversarial Network

Unsupervised Domain Adaptation for Cross-sensor Pore Detection in High-resolution Fingerprint Images

Adaptive Loss Function for Super Resolution Neural Networks Using Convex Optimization Techniques

Text-to-Image Generation with Attention Based Recurrent Neural Networks

CDGAN: Cyclic Discriminative Generative Adversarial Networks for Image-to-Image Transformation

A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning

Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis

Spherical Image Generation from a Single Normal Field of View Image by Considering Scene Symmetry

Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling

Similarity-preserving Image-image Domain Adaptation for Person Re-identification

Supervised and Unsupervised Learning of Parameterized Color Enhancement

FHDR: HDR Image Reconstruction from a Single LDR Image using Feedback Network

Jointly Trained Image and Video Generation using Residual Vectors

A Multi-Task Learning & Generation Framework: Valence-Arousal, Action Units & Primary Expressions

An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks

Learning Disentangled Representations via Mutual Information Estimation

cFineGAN: Unsupervised multi-conditional fine-grained image generation

PasteGAN: A Semi-Parametric Method to Generate Image from Scene Graph

Decentralized Learning of Generative Adversarial Networks from Non-iid Data

SSAH: Semi-supervised Adversarial Deep Hashing with Self-paced Hard Sample Generation

Mini Lesions Detection on Diabetic Retinopathy Images via Large Scale CNN Features

Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition

VITON-GAN: Virtual Try-on Image Generator Trained with Adversarial Loss

Collapse Resistant Deep Convolutional GAN for Multi-Object Image Generation

Enhancing VAEs for Collaborative Filtering: Flexible Priors & Gating Mechanisms

Cali-Sketch: Stroke Calibration and Completion for High-Quality Face Image Generation from Poorly-Drawn Sketches

HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models

Improved Precision and Recall Metric for Assessing Generative Models

PT-MMD: A Novel Statistical Framework for the Evaluation of Generative Systems

TRB: A Novel Triplet Representation for Understanding 2D Human Body

Study of Deep Generative Models for Inorganic Chemical Compositions

Image Generation From Small Datasets via Batch Statistics Adaptation

Image Difficulty Curriculum for Generative Adversarial Networks (CuGAN)

Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN

Exploiting video sequences for unsupervised disentangling in generative adversarial networks

Appearance and Pose-Conditioned Human Image Generation using Deformable GANs

A Generative Approach Towards Improved Robotic Detection of Marine Litter

Incremental learning for the detection and classification of GAN-generated images

A Paired Sparse Representation Model for Robust Face Recognition from a Single Sample

IntersectGAN: Learning Domain Intersection for Generating Images with Multiple Attributes

DSRGAN: Explicitly Learning Disentangled Representation of Underlying Structure and Rendering for Image Generation without Tuple Supervision

DISCOMAN: Dataset of Indoor SCenes for Odometry, Mapping And Navigation

Unsupervised Image Translation using Adversarial Networks for Improved Plant Disease Recognition

Conditional Transferring Features: Scaling GANs to Thousands of Classes with 30% Less High-quality Data for Training

Synthetic dataset generation for object-to-model deep learning in industrial applications

Distortion Estimation Through Explicit Modeling of the Refractive Surface

Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction

Variational Conditional GAN for Fine-grained Controllable Image Generation

Self-Paced Video Data Augmentation with Dynamic Images Generated by Generative Adversarial Networks

Use of Neural Signals to Evaluate the Quality of Generative Adversarial Network Performance in Facial Image Generation

Generate, Segment and Refine: Towards Generic Manipulation Segmentation

Semantic filtering through deep source separation on microscopy images

Sequential Adversarial Learning for Self-Supervised Deep Visual Odometry

Lifelong GAN: Continual Learning for Conditional Image Generation

Fully Automated Image De-fencing using Conditional Generative Adversarial Networks

AutoGAN: Neural Architecture Search for Generative Adversarial Networks

VITAL: A Visual Interpretation on Text with Adversarial Learning for Image Labeling

An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation

Discriminative Consistent Domain Generation for Semi-supervised Learning

Coordinate-based Texture Inpainting for Pose-Guided Image Generation

Guided Image Generation with Conditional Invertible Neural Networks

Mean Spectral Normalization of Deep Neural Networks for Embedded Automation

Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network

Copula & Marginal Flows: Disentangling the Marginal from its Joint

Disentangling Latent Factors of Variational Auto-Encoder with Whitening

Generative Guiding Block: Synthesizing Realistic Looking Variants Capable of Even Large Change Demands

When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks

AGAN: Towards Automated Design of Generative Adversarial Networks

SAR Image Change Detection via Spatial Metric Learning with an Improved Mahalanobis Distance

Dynamic PET cardiac and parametric image reconstruction: a fixed-point proximity gradient approach using patch-based DCT and tensor SVD regularization

Joint Learning of Neural Networks via Iterative Reweighted Least Squares

Multi-objects Generation with Amortized Structural Regularization

Style Transfer With Adaptation to the Central Objects of the Scene

Perceptual Embedding Consistency for Seamless Reconstruction of Tilewise Style Transfer

Image-to-Image Translation with Multi-Path Consistency Regularization

Medical Image Analysis using Convolutional Neural Networks: A Review

Semi-supervised learning based on generative adversarial network: a comparison between good GAN and bad GAN approach

Dilated Spatial Generative Adversarial Networks for Ergodic Image Generation

Ink removal from histopathology whole slide images by combining classification, detection and image generation models

Attack Type Agnostic Perceptual Enhancement of Adversarial Images

3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation

Projection image-to-image translation in hybrid X-ray/MR imaging

Spatially Constrained Generative Adversarial Networks for Conditional Image Generation

Unsupervised Person Image Generation with Semantic Parsing Transformation

FTGAN: A Fully-trained Generative Adversarial Networks for Text to Face Generation

Web Applicable Computer-aided Diagnosis of Glaucoma Using Deep Learning

Training Object Detectors on Synthetic Images Containing Reflecting Materials

Paired 3D Model Generation with Conditional Generative Adversarial Networks

Red blood cell image generation for data augmentation using Conditional Generative Adversarial Networks

TGAN: Deep Tensor Generative Adversarial Nets for Large Image Generation

Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation

Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks

Adversarially Approximated Autoencoder for Image Generation and Manipulation

Synthesizing New Retinal Symptom Images by Multiple Generative Models

Learning Disentangled Representations with Reference-Based Variational Autoencoders

Toward Joint Image Generation and Compression using Generative Adversarial Networks

Generative Adversarial Classifier for Handwriting Characters Super-Resolution

SEIGAN: Towards Compositional Image Generation by Simultaneously Learning to Segment, Enhance, and Inpaint

CSGAN: Cyclic-Synthesized Generative Adversarial Networks for Image-to-Image Transformation

Adversarial Pseudo Healthy Synthesis Needs Pathology Factorization

Thinking Outside the Pool: Active Training Image Creation for Relative Attributes

Manifold-valued Image Generation with Wasserstein Generative Adversarial Nets

Non-Adversarial Image Synthesis with Generative Latent Nearest Neighbors

Unsupervised Learning of Object Landmarks through Conditional Image Generation

Visual Object Networks: Image Generation with Disentangled 3D Representation

Towards High Resolution Video Generation with Progressive Growing of Sliced Wasserstein GANs

Shape-conditioned Image Generation by Learning Latent Appearance Representation from Unpaired Data

Identity Preserving Generative Adversarial Network for Cross-Domain Person Re-identification

Generative Adversarial Network Architectures For Image Synthesis Using Capsule Networks

Style and Content Disentanglement in Generative Adversarial Networks

Feature2Mass: Visual Feature Processing in Latent Space for Realistic Labeled Mass Generation

An Interpretable Generative Model for Handwritten Digit Image Synthesis

Embedded polarizing filters to separate diffuse and specular reflection

Improving CNN Training using Disentanglement for Liver Lesion Classification in CT

Generating Photo-Realistic Training Data to Improve Face Recognition Accuracy

FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models

CanvasGAN: A simple baseline for text to image generation by incrementally patching a canvas

AutoLoss: Learning Discrete Schedules for Alternate Optimization

Cylindrical Transform: 3D Semantic Segmentation of Kidneys With Limited Annotated Images

UnrealStereo: Controlling Hazardous Factors to Analyze Stereo Vision

Learning Hierarchical Semantic Image Manipulation through Structured Representations

GridFace: Face Rectification via Learning Local Homography Transformations

MC-GAN: Multi-conditional Generative Adversarial Network for Image Synthesis

Learning Linear Transformations for Fast Arbitrary Style Transfer

Holistic 3D Scene Parsing and Reconstruction from a Single RGB Image

Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes

Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery

False Positive Reduction by Actively Mining Negative Samples for Pulmonary Nodule Detection in Chest Radiographs

Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis

Ranking CGANs: Subjective Control over Semantic Image Attributes

Generative Adversarial Networks with Decoder-Encoder Output Noise

Improved Training of Generative Adversarial Networks Using Representative Features

Stingray Detection of Aerial Images Using Augmented Training Images Generated by A Conditional Generative Model

Composite Functional Gradient Learning of Generative Adversarial Models

CapsGAN: Using Dynamic Routing for Generative Adversarial Networks

Cross Domain Image Generation through Latent Space Exploration with Adversarial Loss

Word Level Font-to-Font Image Translation using Convolutional Recurrent Generative Adversarial Networks

Domain Adaptation Using Adversarial Learning for Autonomous Navigation

Anime Style Space Exploration Using Metric Learning and Generative Adversarial Networks

Capturing human category representations by sampling in deep feature spaces

Generative networks as inverse problems with Scattering transforms

Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification

Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition

High-resolution Deep Convolutional Generative Adversarial Networks

High-resolution medical image synthesis using progressively grown generative adversarial networks

MEGAN: Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation

Unpaired Multi-Domain Image Generation via Regularized Conditional GANs

Tracking in Aerial Hyperspectral Videos using Deep Kernelized Correlation Filters

Fast-converging Conditional Generative Adversarial Networks for Image Synthesis

Adversarial Training of Variational Auto-encoders for High Fidelity Image Generation

Empirically Analyzing the Effect of Dataset Biases on Deep Face Recognition Systems

Weakly Supervised Object Discovery by Generative Adversarial & Ranking Networks

DCAN: Dual Channel-wise Alignment Networks for Unsupervised Scene Adaptation

A Variational U-Net for Conditional Appearance and Shape Generation

Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model

Image Generation and Translation with Disentangled Representations

Random Polyhedral Scenes: An Image Generator for Active Vision System Experiments

Effective deep learning training for single-image super-resolution in endomicroscopy exploiting video-registration-based reconstruction

Two Birds with One Stone: Transforming and Generating Facial Images with Iterative GAN

Constrained Image Generation Using Binarized Neural Networks with Decision Procedures

Generative Cooperative Net for Image Generation and Data Augmentation

Accurate Weakly Supervised Deep Lesion Segmentation on CT Scans: Self-Paced 3D Mask Generation from RECIST

Deep Chain HDRI: Reconstructing a High Dynamic Range Image from a Single Low Dynamic Range Image

GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

Instance Map based Image Synthesis with a Denoising Generative Adversarial Network

Generative Sensing: Transforming Unreliable Sensor Data for Reliable Recognition

Synthetic Medical Images from Dual Generative Adversarial Networks

Conditional Generative Adversarial Networks for Emoji Synthesis with Word Embedding Manipulation

Concept Formation and Dynamics of Repeated Inference in Deep Generative Models

Stochastic reconstruction of an oolitic limestone by generative adversarial networks

Compatibility Family Learning for Item Recommendation and Generation

From source to target and back: symmetric bi-directional adaptive GAN

Pipeline Generative Adversarial Networks for Facial Images Generation with Multiple Attributes

Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via Adversarial Training

GazeGAN - Unpaired Adversarial Image Generation for Gaze Estimation

Chinese Typeface Transformation with Hierarchical Adversarial Network

Adversarial Generation of Training Examples: Applications to Moving Vehicle License Plate Recognition

Stabilizing Training of Generative Adversarial Networks through Regularization

Artificial Generation of Big Data for Improving Image Classification: A Generative Adversarial Network Approach on SAR Data

Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Stylization and Texture Synthesis

Instance Normalization: The Missing Ingredient for Fast Stylization

CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training

ARIGAN: Synthetic Arabidopsis Plants using Generative Adversarial Network

Adversarial nets with perceptual losses for text-to-image synthesis

Temporal Generative Adversarial Nets with Singular Value Clipping

Systematic Testing of Convolutional Neural Networks for Autonomous Driving

LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation

MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network

Megapixel Size Image Creation using Generative Adversarial Networks

Generative Adversarial Trainer: Defense to Adversarial Perturbations with GAN

From optimal transport to generative modeling: the VEGAN cookbook

Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation

GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data

Auto-painter: Cartoon Image Generation from Sketch by Using Conditional Generative Adversarial Networks

A Unified Approach of Multi-scale Deep and Hand-crafted Features for Defocus Estimation

Semantic Jitter: Dense Supervision for Visual Comparisons via Synthetic Images

TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network

SurfNet: Generating 3D shape surfaces using deep residual networks

Transformation-Grounded Image Generation Network for Novel 3D View Synthesis

Precise Recovery of Latent Vectors from Generative Adversarial Networks

Image Generation and Editing with Variational Info Generative AdversarialNetworks

A Point Set Generation Network for 3D Object Reconstruction from a Single Image

Learning to Generate Images of Outdoor Scenes from Attributes and Semantic Layouts

Incorporating long-range consistency in CNN-based texture generation

MoCap-guided Data Augmentation for 3D Pose Estimation in the Wild

Professor Forcing: A New Algorithm for Training Recurrent Networks

Attribute2Image: Conditional Image Generation from Visual Attributes

Rain structure transfer using an exemplar rain image for synthetic rain image generation

DeepWarp: Photorealistic Image Resynthesis for Gaze Manipulation

Generative Image Modeling using Style and Structure Adversarial Networks

PARAPH: Presentation Attack Rejection by Analyzing Polarization Hypotheses

CNN-RNN: A Unified Framework for Multi-label Image Classification

Semantic Style Transfer and Turning Two-Bit Doodles into Fine Artworks

Generating Images with Perceptual Similarity Metrics based on Deep Networks

Unveiling the Dreams of Word Embeddings: Towards Language-Driven Image Generation

Performance Characterization of Image Feature Detectors in Relation to the Scene Content Utilizing a Large Image Database

Retinex filtering of foggy images: generation of a bulk set with selection and ranking

Deep Boosting: Joint Feature Selection and Analysis Dictionary Learning in Hierarchy

Band selection in RKHS for fast nonlinear unmixing of hyperspectral images

The Classification Accuracy of Multiple-Metric Learning Algorithm on Multi-Sensor Fusion

Multi-Level Coding Efficiency with Improved Quality for Image Compression based on AMBTC

$f$-Cal: Calibrated aleatoric uncertainty estimation from neural networks for robot perception

Comparison of Object Detection Algorithms Using Video and Thermal Images Collected from a UAS Platform: An Application of Drones in Traffic Management

A General Gaussian Heatmap Labeling for Arbitrary-Oriented Object Detection

VirTex: Learning Visual Representations from Textual Annotations

A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging

TreeNet: A lightweight One-Shot Aggregation Convolutional Network

RSDet++: Point-based Modulated Loss for More Accurate Rotated Object Detection

Localizing Infinity-shaped fishes: Sketch-guided object localization in the wild

FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detection

SHD360: A Benchmark Dataset for Salient Human Detection in 360° Videos

Quantization and Deployment of Deep Neural Networks on Microcontrollers

Stereo CenterNet based 3D Object Detection for Autonomous Driving

Towards practical object detection for weed spraying in precision agriculture

T6D-Direct: Transformers for Multi-Object 6D Pose Direct Regression

Automatic Detection of Aedes aegypti Breeding Grounds Based on Deep Networks with Spatio-Temporal Consistency

DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection

Probabilistic and Geometric Depth: Detecting Objects in Perspective

Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR

Oriented Object Detection in Aerial Images Based on Area Ratio of Parallelogram

Bayesian Confidence Calibration for Epistemic Uncertainty Modelling

Robust Estimation of Reflection Symmetry in Noisy and Partial 3D Point Clouds

Object Detection in Thermal Spectrum for Advanced Driver-Assistance Systems (ADAS)

MRDet: A Multi-Head Network for Accurate Oriented Object Detection in Aerial Images

Meta-DETR: Image-Level Few-Shot Object Detection with Inter-Class Correlation Exploitation

Joint Distribution Alignment via Adversarial Learning for Domain Adaptive Object Detection

Parallel Residual Bi-Fusion Feature Pyramid Network for Accurate Single-Shot Object Detection

Locally Enhanced Self-Attention: Rethinking Self-Attention as Local and Context Terms

Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development

M2RNet: Multi-modal and Multi-scale Refined Network for RGB-D Salient Object Detection

Exploiting Activation based Gradient Output Sparsity to Accelerate Backpropagation in CNNs

METEOR: A Massive Dense & Heterogeneous Behavior Dataset for Autonomous Driving

Deep Bregman Divergence for Contrastive Learning of Visual Representations

An Efficient Quantitative Approach for Optimizing Convolutional Neural Networks

Incremental Multi-Target Domain Adaptation for Object Detection with Efficient Domain Transfer

Progressive Hard-case Mining across Pyramid Levels in Object Detection

DSOR: A Scalable Statistical Filter for Removing Falling Snow from LiDAR Point Clouds in Severe Winter Weather

A Deep Learning Approach for Masking Fetal Gender in Ultrasound Images

Sensor Adversarial Traits: Analyzing Robustness of 3D Object Detection Sensor Fusion Models

Single-stage Keypoint-based Category-level Object Pose Estimation from an RGB Image

MosaicOS: A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection

Adversarially Trained Object Detector for Unsupervised Domain Adaptation

Partially-supervised novel object captioning leveraging context from paired data

MultiTask-CenterNet (MCN): Efficient and Diverse Multitask Learning using an Anchor Free Approach

Face-NMS: A Core-set Selection Approach for Efficient Face Recognition

ACFNet: Adaptively-Cooperative Fusion Network for RGB-D Salient Object Detection

Localization Uncertainty Estimation for Anchor-Free Object Detection

Suppress-and-Refine Framework for End-to-End 3D Object Detection

Rethinking the Aligned and Misaligned Features in One-stage Object Detection

Mask is All You Need: Rethinking Mask R-CNN for Dense and Arbitrary-Shaped Scene Text Detection

Towards Robust Object Detection: Bayesian RetinaNet for Homoscedastic Aleatoric Uncertainty Modeling

Identification of Driver Phone Usage Violations via State-of-the-Art Object Detection with Tracking

Robustness and Generalization via Generative Adversarial Training

Bridging the Gap between Events and Frames through Unsupervised Domain Adaptation

Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection

Tackling the Background Bias in Sparse Object Detection via Cropped Windows

Rotation Equivariant Feature Image Pyramid Network for Object Detection in Optical Remote Sensing Imagery

Training Multi-Object Detector by Estimating Bounding Box Distribution for Input Image

Moving Object Detection for Event-based Vision using k-means Clustering

A Comprehensive Approach for UAV Small Object Detection with Simulation-based Transfer Learning and Adaptive Fusion

Semantics-Guided Contrastive Network for Zero-Shot Object detection

To be Critical: Self-Calibrated Weakly Supervised Learning for Salient Object Detection

STN PLAD: A Dataset for Multi-Size Power Line Assets Detection in High-Resolution UAV Images

An Efficient Deep Learning Approach Using Improved Generative Adversarial Networks for Incomplete Information Completion of Self-driving

Discriminative Semantic Feature Pyramid Network with Guided Anchoring for Logo Detection

AIP: Adversarial Iterative Pruning Based on Knowledge Transfer for Convolutional Neural Networks

Boosting Salient Object Detection with Transformer-based Asymmetric Bilateral U-Net

Densely Semantic Enhancement for Domain Adaptive Region-free Detectors

MBDF-Net: Multi-Branch Deep Fusion Network for 3D Object Detection

Edge-Cloud Collaborated Object Detection via Difficult-Case Discriminator

DenseLiDAR: A Real-Time Pseudo Dense Depth Guided Depth Completion Network

Uncertainty-Aware Model Adaptation for Unsupervised Cross-Domain Object Detection

On the impact of using X-ray energy response imagery for object detection via Convolutional Neural Networks

Densely-Populated Traffic Detection using YOLOv5 and Non-Maximum Suppression Ensembling

An Automatic Image Content Retrieval Method for better Mobile Device Display User Experiences

LocTex: Learning Data-Efficient Visual Representations from Localized Textual Supervision

A Comparison of Deep Saliency Map Generators on Multispectral Data in Object Detection

An Underwater Image Semantic Segmentation Method Focusing on Boundaries and a Real Underwater Scene Semantic Segmentation Dataset

TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarios

ChessMix: Spatial Context Data Augmentation for Remote Sensing Semantic Segmentation

Improving Object Detection and Attribute Recognition by Feature Entanglement Reduction

PGTRNet: Two-phase Weakly Supervised Object Detection with Pseudo Ground Truth Refining

GlassNet: Label Decoupling-based Three-stream Neural Network for Robust Image Glass Detection

Detecting Small Objects in Thermal Images Using Single-Shot Detector

Layer-wise Customized Weak Segmentation Block and AIoU Loss for Accurate Object Detection

OmniDet: Surround View Cameras based Multi-task Visual Perception Network for Autonomous Driving

Deep neural networks approach to microbial colony detection -- a comparative analysis

A Self-supervised Learning System for Object Detection in Videos Using Random Walks on Graphs

Small Object Detection Based on Modified FSSD and Model Compression

Exploring Simple 3D Multi-Object Tracking for Autonomous Driving

ODAM: Object Detection, Association, and Mapping using Posed RGB Video

Robust Object Detection via Instance-Level Temporal Cycle Confusion

Recursive Contour Saliency Blending Network for Accurate Salient Object Detection

Pick-Object-Attack: Type-Specific Adversarial Attack for Object Detection

MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?

Multi-scale Edge-based U-shape Network for Salient Object Detection

Towards large-scale, automated, accurate detection of CCTV camera objects using computer vision. Applications and implications for privacy, safety, and cybersecurity. (Preprint)

Active Learning for Deep Object Detection via Probabilistic Modeling

G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation

Exploring Data Aggregation and Transformations to Generalize across Visual Domains

ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object Detection

SA-Det3D: Self-Attention Based Context-Aware 3D Object Detection

A Deep Learning Based Automatic Defect Analysis Framework for In-situ TEM Ion Irradiations

Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark

Deployment of Deep Neural Networks for Object Detection on Edge AI Devices with Runtime Optimization

Multi-patch Feature Pyramid Network for Weakly Supervised Object Detection in Optical Remote Sensing Images

Few-Shot Batch Incremental Road Object Detection via Detector Fusion

Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency

Exploring Classification Equilibrium in Long-Tailed Object Detection

RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection

VisBuddy -- A Smart Wearable Assistant for the Visually Challenged

Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

Demystifying Local Vision Transformer: Sparse Connectivity, Weight Sharing, and Dynamic Weight

PIT: Position-Invariant Transform for Cross-FoV Domain Adaptation

Towards unconstrained joint hand-object reconstruction from RGB videos

CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Images

AdaCon: Adaptive Context-Aware Object Detection for Resource-Constrained Embedded Devices

Learning Open-World Object Proposals without Learning to Classify

SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation

Vector-Decomposed Disentanglement for Domain-Invariant Object Detection

ST3D++: Denoised Self-training for Unsupervised Domain Adaptation on 3D Object Detection

Semi-supervised 3D Object Detection via Adaptive Pseudo-Labeling

Modal-Adaptive Gated Recoding Network for RGB-D Salient Object Detection

Geometry Uncertainty Projection Network for Monocular 3D Object Detection

CNN-based Two-Stage Parking Slot Detection Using Region-Specific Multi-Scale Feature Extraction

Progressive Coordinate Transforms for Monocular 3D Object Detection

MmWave Radar and Vision Fusion for Object Detection in Autonomous Driving: A Review

Provident Vehicle Detection at Night for Advanced Driver Assistance Systems

Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions

Joint Multi-Object Detection and Tracking with Camera-LiDAR Fusion for Autonomous Driving

UniNet: A Unified Scene Understanding Network and Exploring Multi-Task Relationships through the Lens of Adversarial Attacks

FusionPainting: Multimodal Fusion with Adaptive Attention for 3D Object Detection

Single-Training Collaborative Object Detectors Adaptive to Bandwidth and Computation

TriTransNet: RGB-D Salient Object Detection with a Triplet Transformer Embedding Network

BiconNet: An Edge-preserved Connectivity-based Approach for Salient Object Detection

From Voxel to Point: IoU-guided 3D Object Detection for Point Cloud with Voxel-to-Point Decoder

Anchor-free 3D Single Stage Detector with Mask-Guided Attention for Point Cloud

MPI: Multi-receptive and Parallel Integration for Salient Object Detection

Monte Carlo DropBlock for Modelling Uncertainty in Object Detection

DeepFH Segmentations for Superpixel-based Object Proposal Refinement

TS4Net: Two-Stage Sample Selective Strategy for Rotating Object Detection

Evaluating Adversarial Attacks on Driving Safety in Vision-Based Autonomous Vehicles

Colonoscopy Polyp Detection and Classification: Dataset Creation and Comparative Evaluations

Unifying Global-Local Representations in Salient Object Detection with Transformer

A Low Rank Promoting Prior for Unsupervised Contrastive Learning

Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers

Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning

Cross-modality Discrepant Interaction Network for RGB-D Salient Object Detection

Boosting Weakly Supervised Object Detection via Learning Bounding Box Adjusters

You Better Look Twice: a new perspective for designing accurate detectors with reduced computations

Angle Based Feature Learning in GNN for 3D Object Detection using Point Cloud

Investigating Attention Mechanism in 3D Point Cloud Object Detection

Developing a Compressed Object Detection Model based on YOLOv4 for Deployment on Embedded GPU Platform of Autonomous System

CrossFormer: A Versatile Vision Transformer Based on Cross-scale Attention

Fooling LiDAR Perception via Adversarial Trajectory Perturbation

From Multi-View to Hollow-3D: Hallucinated Hollow-3D R-CNN for 3D Object Detection

Bridging Gap between Image Pixels and Semantics via Supervision: A Survey

CBNetV2: A Composite Backbone Network Architecture for Object Detection

Similarity and symmetry measures based on fuzzy descriptors of image objects` composition

United We Learn Better: Harvesting Learning Improvements From Class Hierarchies Across Tasks

Visual Object Recognition in Indoor Environments Using Topologically Persistent Features

Aug3D-RPN: Improving Monocular 3D Object Detection by Synthetic Images with Virtual Depth

Confluence: A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection

A New Dataset, Poisson GAN and AquaNet for Underwater Object Grabbing

Is Object Detection Necessary for Human-Object Interaction Recognition?

SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization

DV-Det: Efficient 3D Point Cloud Object Detection with Dynamic Voxelization

Dynamic and Static Object Detection Considering Fusion Regions and Point-wise Features

Workshop on Autonomous Driving at CVPR 2021: Technical Report for Streaming Perception Challenge

BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction

ST-DETR: Spatio-Temporal Object Traces Attention Detection Transformer

Deep Machine Learning Based Egyptian Vehicle License Plate Recognition Systems

ASOD60K: Audio-Induced Salient Object Detection in Panoramic Videos

A Fully Spiking Hybrid Neural Network for Energy-Efficient Object Detection

EPSANet: An Efficient Pyramid Squeeze Attention Block on Convolutional Neural Network

An overcome of far-distance limitation on tunnel CCTV-based accident detection in AI deep-learning frameworks

Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels

Deeply Shared Filter Bases for Parameter-Efficient Convolutional Neural Networks

A Public Ground-Truth Dataset for Handwritten Circuit Diagram Images

Training Object Detectors from Few Weakly-Labeled and Many Unlabeled Images

Disentangling 3D Prototypical Networks For Few-Shot Concept Learning

Disentangling and Vectorization: A 3D Visual Perception Approach for Autonomous Driving Based on Surround-View Fisheye Cameras

Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss

A High-Performance Adaptive Quantization Approach for Edge CNN Applications

Content-Augmented Feature Pyramid Network with Light Linear Spatial Transformers for Object Detection

A Survey on Deep Domain Adaptation and Tiny Object Detection Challenges, Techniques and Datasets

Adversarial Attacks on Multi-task Visual Perception for Autonomous Driving

Diff-Net: Image Feature Difference based High-Definition Map Change Detection

Memory-Aware Fusing and Tiling of Neural Networks for Accelerated Edge Inference

RelativeNAS: Relative Neural Architecture Search via Slow-Fast Learning

One Metric to Measure them All: Localisation Recall Precision (LRP) for Evaluating Visual Detection Tasks

The efficacy of Neural Planning Metrics: A meta-analysis of PKL on nuScenes

Visual Parser: Representing Part-whole Hierarchies with Transformers

CFTrack: Center-based Radar and Camera Fusion for 3D Multi-Object Tracking

Semi-Supervised Object Detection with Adaptive Class-Rebalancing Self-Training

Prediction Surface Uncertainty Quantification in Object Detection Models for Autonomous Driving

A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving

Part-Aware Data Augmentation for 3D Object Detection in Point Cloud

BEVDetNet: Bird's Eye View LiDAR Point Cloud based Real-time 3D Object Detection for Autonomous Driving

VM-MODNet: Vehicle Motion aware Moving Object Detection for Autonomous Driving

CSL-YOLO: A New Lightweight Object Detection System for Edge Computing

Resilience of Autonomous Vehicle Object Category Detection to Universal Adversarial Perturbations

Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors

Optimizing Data Processing in Space for Object Detection in Satellite Imagery

VIN: Voxel-based Implicit Network for Joint 3D Object Detection and Segmentation for Lidars

3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection

Neighbor-Vote: Improving Monocular 3D Object Detection through Neighbor Distance Voting

Adapting Vehicle Detector to Target Domain by Adversarial Prediction Alignment

Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detection

On Model Calibration for Long-Tailed Object Detection and Instance Segmentation

Semi-supervised Learning for Dense Object Detection in Retail Scenes

SCOD: Active Object Detection for Embodied Agents using Sensory Commutativity of Action Sequences

Faster-LTN: a neuro-symbolic, end-to-end object detection architecture

Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation

Multi-View Correlation Distillation for Incremental Object Detection

A More Compact Object Detector Head Network with Feature Enhancement and Relational Reasoning

Outlier-Robust Estimation: Hardness, Minimally Tuned Algorithms, and Applications

1st Place Solutions for UG2+ Challenge 2021 -- (Semi-)supervised Face detection in the low light condition

Focal Self-attention for Local-Global Interactions in Vision Transformers

TANet++: Triple Attention Network with Filtered Pointcloud on 3D Detection

On the detection-to-track association for online multi-object tracking

MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View Understanding

End-to-end Compression Towards Machine Vision: Network Architecture Design and Optimization

Dynamic Knowledge Distillation with A Single Stream Structure for RGB-D Salient Object Detection

Simple Training Strategies and Model Scaling for Object Detection

Monocular 3D Object Detection: An Extrinsic Parameter Free Approach

Align Yourself: Self-supervised Pre-training for Fine-grained Recognition via Saliency Alignment

SIMPL: Generating Synthetic Overhead Imagery to Address Zero-shot and Few-Shot Detection Problems

An Uncertainty Estimation Framework for Probabilistic Object Detection

Six-channel Image Representation for Cross-domain Object Detection

Achieving Real-Time Object Detection on MobileDevices with Neural Pruning Search

OSKDet: Towards Orientation-sensitive Keypoint Localization for Rotated Object Detection

Dataset and Benchmarking of Real-Time Embedded Object Detection for RoboCup SSL

QuickBrowser: A Unified Model to Detect and Read Simple Object in Real-time

Transformer Transforms Salient Object Detection and Camouflaged Object Detection

A CNN Segmentation-Based Approach to Object Detection and Tracking in Ultrasound Scans with Application to the Vagus Nerve Detection

Partially fake it till you make it: mixing real and fake thermal images for improved object detection

SRPN: similarity-based region proposal networks for nuclei and cells detection in histology images

To the Point: Efficient 3D Object Detection in the Range Image with Graph Convolution Kernels

RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detection

TetraPackNet: Four-Corner-Based Object Detection in Logistics Use-Cases

GEM: Glare or Gloom, I Can Still See You -- End-to-End Multimodal Object Detection

Hand-Drawn Electrical Circuit Recognition using Object Detection and Node Recognition

Shape Prior Non-Uniform Sampling Guided Real-time Stereo 3D Object Detection

SODA10M: Towards Large-Scale Object Detection Benchmark for Autonomous Driving

Spatio-Temporal Multi-Task Learning Transformer for Joint Moving Object Detection and Segmentation

Meta Faster R-CNN: Towards Accurate Few-Shot Object Detection with Attentive Feature Alignment

Segmentation of cell-level anomalies in electroluminescence images of photovoltaic modules

You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection

Humble Teachers Teach Better Students for Semi-Supervised Object Detection

Bridging the Gap Between Object Detection and User Intent via Query-Modulation

Toward Fault Detection in Industrial Welding Processes with Deep Learning and Data Augmentation

Automatic Social Distance Estimation From Images: Performance Evaluation, Test Benchmark, and Algorithm

Quantized Neural Networks via {-1, +1} Encoding Decomposition and Acceleration

Effective Model Sparsification by Scheduled Grow-and-Prune Methods

CMA-Net: A Cascaded Mutual Attention Network for Light Field Salient Object Detection

A Random CNN Sees Objects: One Inductive Bias of CNN and Its Applications

Toward Robotic Weed Control: Detection of Nutsedge Weed in Bermudagrass Turf Using Inaccurate and Insufficient Training Data

Potato Crop Stress Identification in Aerial Images using Deep Learning-based Object Detection

2nd Place Solution for Waymo Open Dataset Challenge -- Real-time 2D Object Detection

A Spacecraft Dataset for Detection, Segmentation and Parts Recognition

Object detection and Autoencoder-based 6D pose estimation for highly cluttered Bin Picking

PolarStream: Streaming Lidar Object Detection and Segmentation with Polar Pillars

SGE net: Video object detection with squeezed GRU and information entropy map

Small Object Detection for Near Real-Time Egocentric Perception in a Manual Assembly Scenario

Gaussian Bounding Boxes and Probabilistic Intersection-over-Union for Object Detection

Fast, Accurate Barcode Detection in Ultra High-Resolution Images

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations

ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision

A Dataset And Benchmark Of Underwater Object Detection For Robot Picking

We Can Always Catch You: Detecting Adversarial Patched Objects WITH or WITHOUT Signature

Visual Sensor Pose Optimisation Using Rendering-based Visibility Models for Robust Cooperative Perception

SynthRef: Generation of Synthetic Referring Expressions for Object Segmentation

Monocular 3D Object Detection with Decoupled Structured Polygon Estimation and Height-Guided Depth Estimation

PAM: Understanding Product Images in Cross Product Category Attribute Extraction

DETReg: Unsupervised Pretraining with Region Priors for Object Detection

Progressive Multi-scale Fusion Network for RGB-D Salient Object Detection

Few-Shot Unsupervised Image-to-Image Translation on complex scenes

Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer

Self-Supervision & Meta-Learning for One-Shot Unsupervised Cross-Domain Detection

Scaling Local Self-Attention for Parameter Efficient Visual Backbones

3D Convolution Neural Network based Person Identification using Gait cycles

Guidance and Teaching Network for Video Salient Object Detection

Hybrid-Attention Guided Network with Multiple Resolution Features for Person Re-Identification

Middle-level Fusion for Lightweight RGB-D Salient Object Detection

GLSD: The Global Large-Scale Ship Database and Baseline Evaluations

Hallucination In Object Detection -- A Study In Visual Part Verification

Multi-interactive Dual-decoder for RGB-thermal Salient Object Detection

NMS-Loss: Learning with Non-Maximum Suppression for Crowded Pedestrian Detection

Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergence

E2E-VLP: End-to-End Vision-Language Pre-training Enhanced by Visual Learning

Transferable Adversarial Examples for Anchor Free Object Detection

Fine-Grained Visual Classification of Plant Species In The Wild: Object Detection as A Reinforced Means of Attention

SSMD: Semi-Supervised Medical Image Detection with Adaptive Consistency and Heterogeneous Perturbation

Multiscale Domain Adaptive YOLO for Cross-Domain Object Detection

Long Term Object Detection and Tracking in Collaborative Learning Environments

Style Normalization and Restitution for Domain Generalization and Adaptation

Dense Nested Attention Network for Infrared Small Target Detection

MSG-Transformer: Exchanging Local Spatial Information by Manipulating Messenger Tokens

Scorpion detection and classification systems based on computer vision and deep learning for health security purposes

Data Collection and Utilization Framework for Edge AI Applications

3D Object Detection from a Single Fisheye Image Without a Single Fisheye Training Image

Training Domain-invariant Object Detector Faster with Feature Replay and Slow Learner

Multiscale IoU: A Metric for Evaluation of Salient Object Detection with Fine Structures

BAAI-VANJEE Roadside Dataset: Towards the Connected Automated Vehicle Highway technologies in Challenging Environments of China

Sparse LiDAR and Stereo Fusion (SLS-Fusion) for Depth Estimationand 3D Object Detection

Dynamic Network selection for the Object Detection task: why it matters and what we (didn't) achieve

PSRR-MaxpoolNMS: Pyramid Shifted MaxpoolNMS with Relationship Recovery

Joint-DetNAS: Upgrade Your Detector with NAS, Pruning and Dynamic Distillation

Multi-Modal Semantic Inconsistency Detection in Social Media News Posts

Issues in Object Detection in Videos using Common Single-Image CNNs

Deep Learning for Weakly-Supervised Object Detection and Object Localization: A Survey

Recent Standard Development Activities on Video Coding for Machines

Monocular Instance Motion Segmentation for Autonomous Driving: KITTI InstanceMotSeg Dataset and Multi-task Baseline

Context-aware Cross-level Fusion Network for Camouflaged Object Detection

Accurate Camouflaged Object Detection via Mixture Convolution and Interactive Fusion

SalientSleepNet: Multimodal Salient Wave Detection Network for Sleep Staging

LineCounter: Learning Handwritten Text Line Segmentation by Counting

What is the State of the Art of Computer Vision-Assisted Cytology? A Systematic Literature Review

Deep Learning in Diabetic Foot Ulcers Detection: A Comprehensive Evaluation

High-level camera-LiDAR fusion for 3D object detection with machine learning

COTR: Convolution in Transformer Network for End to End Polyp Detection

Real-time Detection of Practical Universal Adversarial Perturbations

Compressing Deep CNNs using Basis Representation and Spectral Fine-tuning

Analysis of voxel-based 3D object detection methods efficiency for real-time embedded systems

WSSOD: A New Pipeline for Weakly- and Semi-Supervised Object Detection

Act Like a Radiologist: Towards Reliable Multi-view Correspondence Reasoning for Mammogram Mass Detection

An interpretable object detection based model for the diagnosis of neonatal lung diseases using Ultrasound images

AGSFCOS: Based on attention mechanism and Scale-Equalizing pyramid network of object detection

Fully Convolutional Networks for Automatically Generating Image Masks to Train Mask R-CNN

Machine-learning based methodologies for 3d x-ray measurement, characterization and optimization for buried structures in advanced ic packages

Uncertainty-Aware Unsupervised Domain Adaptation in Object Detection

Efficient Transfer Learning via Joint Adaptation of Network Architecture and Weight

SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data

How Trustworthy are Performance Evaluations for Basic Vision Tasks?

Learning to Automatically Catch Potholes in Worldwide Road Scene Images

Exploring Driving-aware Salient Object Detection via Knowledge Transfer

FGR: Frustum-Aware Geometric Reasoning for Weakly Supervised 3D Vehicle Detection

Learning Synergistic Attention for Light Field Salient Object Detection

Lightweight Compression of Intermediate Neural Network Features for Collaborative Intelligence

MutualNet: Adaptive ConvNet via Mutual Learning from Different Model Configurations

Are we Missing Confidence in Pseudo-LiDAR Methods for Monocular 3D Object Detection?

Lightweight compression of neural network feature tensors for collaborative intelligence

Deep Spiking Convolutional Neural Network for Single Object Localization Based On Deep Continuous Local Learning

Waste detection in Pomerania: non-profit project for detecting waste in environment

Object-Based Augmentation Improves Quality of Remote SensingSemantic Segmentation

Video Salient Object Detection via Adaptive Local-Global Refinement

Rethinking of Radar's Role: A Camera-Radar Dataset and Systematic Annotator via Coordinate Alignment

DeepLight: Robust & Unobtrusive Real-time Screen-Camera Communication for Real-World Displays

Let There be Light: Improved Traffic Surveillance via Detail Preserving Night-to-Day Transfer

ConTNet: Why not use convolution and transformer at the same time?

A Survey of Performance Optimization in Neural Network-Based Video Analytics Systems

A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video

Achieving Domain Generalization in Underwater Object Detection by Image Stylization and Domain Mixup

DetectorGuard: Provably Securing Object Detectors against Localized Patch Hiding Attacks

Dataset and Performance Comparison of Deep Learning Architectures for Plum Detection and Robotic Harvesting

Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss

Dirty Pixels: Towards End-to-End Image Processing and Perception

A State-of-the-art Survey of Object Detection Techniques in Microorganism Image Analysis: from Traditional Image Processing and Classical Machine Learning to Current Deep Convolutional Neural Networks and Potential Visual Transformers

Probabilistic Ranking-Aware Ensembles for Enhanced Object Detections

Detection, Tracking, and Counting Meets Drones in Crowds: A Benchmark

MODS -- A USV-oriented object detection and obstacle segmentation benchmark

PolarMask++: Enhanced Polar Representation for Single-Shot Instance Segmentation and Beyond

SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water

LAFFNet: A Lightweight Adaptive Feature Fusion Network for Underwater Image Enhancement

Improving Object Detection in Art Images Using Only Style Transfer

Robustness Enhancement of Object Detection in Advanced Driver Assistance Systems (ADAS)

Exploring Thermal Images for Object Detection in Underexposure Regions for Autonomous Driving

Automatic Visual Inspection of Rare Defects: A Framework based on GP-WGAN and Enhanced Faster R-CNN

RADDet: Range-Azimuth-Doppler based Radar Object Detection for Dynamic Road Users

Self-Knowledge Distillation with Progressive Refinement of Targets

M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers

Condensation-Net: Memory-Efficient Network Architecture with Cross-Channel Pooling Layers and Virtual Feature Maps

Pseudo-IoU: Improving Label Assignment in Anchor-Free Object Detection

Zero-Shot Detection via Vision and Language Knowledge Distillation

PDNet: Towards Better One-stage Object Detection with Prediction Decoupling

Automated System for Ship Detection from Medium Resolution Satellite Optical Imagery

HOTR: End-to-End Human-Object Interaction Detection with Transformers

Salient Instance Segmentation with Region and Box-level Annotations

Monitoring COVID-19 social distancing with person detection and tracking via fine-tuned YOLO v3 and Deepsort techniques

SGNet: A Super-class Guided Network for Image Classification and Object Detection

Sparse R-CNN: End-to-End Object Detection with Learnable Proposals

Carton dataset synthesis method for domain shift based on foreground texture decoupling and replacement

Single Stage Class Agnostic Common Object Detection: A Simple Baseline

Breast Mass Detection with Faster R-CNN: On the Feasibility of Learning from Noisy Annotations

Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation

UnrealROX+: An Improved Tool for Acquiring Synthetic Data from Virtual 3D Environments

Co-training for Deep Object Detection: Comparing Single-modal and Multi-modal Approaches

TricubeNet: 2D Kernel-Based Object Representation for Weakly-Occluded Oriented Object Detection

Heterogeneous Grid Convolution for Adaptive, Efficient, and Controllable Computation

Cycle and Semantic Consistent Adversarial Domain Adaptation for Reducing Simulation-to-Real Domain Shift in LiDAR Bird's Eye View

Exploring 2D Data Augmentation for 3D Monocular Object Detection

MVFuseNet: Improving End-to-End Object Detection and Motion Forecasting through Multi-View Fusion of LiDAR Data

Rapid Detection of Aircrafts in Satellite Imagery based on Deep Neural Networks

Efficient Golf Ball Detection and Tracking Based on Convolutional Neural Networks and Kalman Filter

Concept Grounding with Modular Action-Capsules in Semantic Video Prediction

Exploring Data Augmentation for Multi-Modality 3D Object Detection

SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloud

Multi-Modal Fusion Transformer for End-to-End Autonomous Driving

AFD-Net: Adaptive Fully-Dual Network for Few-Shot Object Detection

Preferences Prediction using a Gallery of Mobile Device based on Scene Recognition and Object Detection

MonoGRNet: A General Framework for Monocular 3D Object Detection

Real-Time Object Detection and Localization in Compressive Sensed Video on Embedded Hardware

Points as Queries: Weakly Semi-supervised Object Detection by Points

IQDet: Instance-wise Quality Distribution Sampling for Object Detection

ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks

Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds

Self-supervised object detection from audio-visual correspondence

Simultaneously Localize, Segment and Rank the Camouflaged Objects

Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates

Geometry-aware data augmentation for monocular 3D object detection

RayNet: Real-time Scene Arbitrary-shape Text Detection with Multiple Rays

Global Correlation Network: End-to-End Joint Multi-Object Detection and Tracking

Unidentified Video Objects: A Benchmark for Dense, Open-World Segmentation

PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection

Enhancing Object Detection for Autonomous Driving by Optimizing Anchor Generation and Addressing Class Imbalance

HindSight: A Graph-Based Vision Model Architecture For Representing Part-Whole Hierarchies

Deep Semi-supervised Metric Learning with Dual Alignment for Cervical Cancer Cell Detection

Artificial and beneficial -- Exploiting artificial images for aerial vehicle detection

Uncertainty-aware Joint Salient Object and Camouflaged Object Detection

RadarScenes: A Real-World Radar Point Cloud Data Set for Automotive Applications

Buy Me That Look: An Approach for Recommending Similar Fashion Products

Few-Cost Salient Object Detection with Adversarial-Paced Learning

RADIATE: A Radar Dataset for Automotive Perception in Bad Weather

Visual Relationship Detection with Visual-Linguistic Knowledge from Multimodal Representations

BTS-Net: Bi-directional Transfer-and-Selection Network For RGB-D Salient Object Detection

Data Augmentation for Object Detection via Differentiable Neural Rendering

Dense Contrastive Learning for Self-Supervised Visual Pre-Training

MeGA-CDA: Memory Guided Attention for Category-Aware Unsupervised Domain Adaptive Object Detection

Joint Object Detection and Multi-Object Tracking with Graph Neural Networks

Uncertainty for Identifying Open-Set Errors in Visual Object Detection

DyStaB: Unsupervised Object Segmentation via Dynamic-Static Bootstrapping

Efficient DETR: Improving End-to-End Object Detector with Dense Prior

HVPR: Hybrid Voxel-Point Representation for Single-stage 3D Object Detection

Efficient sign language recognition system and dataset creation method based on deep learning and image processing

Motion Guided Attention Fusion to Recognize Interactions from Videos

SCALoss: Side and Corner Aligned Loss for Bounding Box Regression

Two-phase weakly supervised object detection with pseudo ground truth mining

Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object Detection

SIENet: Spatial Information Enhancement Network for 3D Object Detection from Point Cloud

Improved and efficient inter-vehicle distance estimation using road gradients of both ego and target vehicles

GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection

DA-DETR: Domain Adaptive Detection Transformer by Hybrid Attention

Fixing the Teacher-Student Knowledge Discrepancy in Distillation

MobileDets: Searching for Object Detection Architectures for Mobile Accelerators

Depth-conditioned Dynamic Message Propagation for Monocular 3D Object Detection

FBNetV3: Joint Architecture-Recipe Search using Predictor Pretraining

Distribution Alignment: A Unified Framework for Long-tail Visual Recognition

Improving robustness against common corruptions with frequency biased models

Delving into Localization Errors for Monocular 3D Object Detection

Accurate Monocular Object Detection via Color-Embedded 3D Reconstruction for Autonomous Driving

Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detection

Few-Shot Learning for Video Object Detection in a Transfer-Learning Scheme

Diverse Branch Block: Building a Convolution as an Inception-like Unit

Data-Uncertainty Guided Multi-Phase Learning for Semi-Supervised Object Detection

IENet: Interacting Embranchment One Stage Anchor Free Detector for Orientation Aerial Object Detection

Faraway-Frustum: Dealing with Lidar Sparsity for 3D Object Detection using Fusion

COVID-19 personal protective equipment detection using real-time deep learning methods

ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection

On the Arbitrary-Oriented Object Detection: Classification based Approaches Revisited

Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection

Few-shot Weakly-Supervised Object Detection via Directional Statistics

Multi-Target Domain Adaptation via Unsupervised Domain Classification for Weather Invariant Object Detection

Modulating Localization and Classification for Harmonized Object Detection

Gaussian Guided IoU: A Better Metric for Balanced Learning on Object Detection

Enabling Retrain-free Deep Neural Network Pruning using Surrogate Lagrangian Relaxation

MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation

DSIC: Dynamic Sample-Individualized Connector for Multi-Scale Object Detection

Unsupervised object-centric video generation and decomposition in 3D

FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagery

Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Types

cMinMax: A Fast Algorithm to Find the Corners of an N-dimensional Convex Polytope

MonoRUn: Monocular 3D Object Detection by Reconstruction and Uncertainty Propagation

UAV Images Dataset for Moving Object Detection from Moving Cameras

Categorical Depth Distribution Network for Monocular 3D Object Detection

RangeRCNN: Towards Fast and Accurate 3D Object Detection with Range Image Representation

End-to-End Trainable Multi-Instance Pose Estimation with Transformers

Deep RGB-D Saliency Detection with Depth-Sensitive Attention and Automatic Multi-Modal Fusion

n-hot: Efficient bit-level sparsity for powers-of-two neural network quantization

Control Distance IoU and Control Distance IoU Loss Function for Better Bounding Box Regression

Optimization for Oriented Object Detection via Representation Invariance Loss

Pack and Detect: Fast Object Detection in Videos Using Region-of-Interest Packing

Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework

Learning Calibrated-Guidance for Object Detection in Aerial Images

A first step towards automated species recognition from camera trap images of mammals using AI in a European temperate forest

Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection

RangeDet:In Defense of Range View for LiDAR-based 3D Object Detection

Deformable DETR: Deformable Transformers for End-to-End Object Detection

NaturalAE: Natural and Robust Physical Adversarial Examples for Object Detectors

Learning a Geometric Representation for Data-Efficient Depth Estimation via Gradient Field and Contrastive Loss

YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D Detection

Potential Escalator-related Injury Identification and Prevention Based on Multi-module Integrated System for Public Health

Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes

QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object Detection

Adversarial YOLO: Defense Human Detection Patch Attacks via Detecting Adversarial Patches

S-AT GCN: Spatial-Attention Graph Convolution Network based Feature Enhancement for 3D Object Detection

DeepUSPS: Deep Robust Unsupervised Saliency Prediction With Self-Supervision

3D-FFS: Faster 3D object detection with Focused Frustum Search in sensor fusion based networks

Refine Myself by Teaching Myself: Feature Refinement via Self-Knowledge Distillation

Geometric Change Detection in Digital Twins using 3D Machine Learning

FSCE: Few-Shot Object Detection via Contrastive Proposal Encoding

ReDet: A Rotation-equivariant Detector for Aerial Object Detection

Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors

Learnable Companding Quantization for Accurate Low-bit Neural Networks

Advanced Multiple Linear Regression Based Dark Channel Prior Applied on Dehazing Image and Generating Synthetic Haze

Regularized Densely-connected Pyramid Network for Salient Instance Segmentation

Auto4D: Learning to Label 4D Objects from Sequential Point Clouds

OPANAS: One-Shot Path Aggregation Network Architecture Search for Object Detection

PatchNet -- Short-range Template Matching for Efficient Video Processing

Beyond Self-Supervision: A Simple Yet Effective Network Distillation Alternative to Improve Backbones

MapFusion: A General Framework for 3D Object Detection with HDMaps

VinVL: Revisiting Visual Representations in Vision-Language Models

Predicting Classification Accuracy When Adding New Unobserved Classes

Thumbnail: A Novel Data Augmentation for Convolutional Neural Network

Online Monitoring of Object Detection Performance During Deployment

Multi-level Cross-modal Interaction Network for RGB-D Salient Object Detection

End-to-End Human Object Interaction Detection with HOI Transformer

End-to-end optimized image compression for multiple machine tasks

A Real-time Low-cost Artificial Intelligence System for Autonomous Spraying in Palm Plantations

A Simple and Efficient Multi-task Network for 3D Object Detection and Road Understanding

Learning from Counting: Leveraging Temporal Classification for Weakly Supervised Object Localization and Detection

labelCloud: A Lightweight Domain-Independent Labeling Tool for 3D Object Detection in Point Clouds

IAFA: Instance-aware Feature Aggregation for 3D Object Detection from a Single Image

SSTN: Self-Supervised Domain Adaptation Thermal Object Detection for Autonomous Driving

UniT: Unified Knowledge Transfer for Any-shot Object Detection and Segmentation

Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation

There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge

Over-sampling De-occlusion Attention Network for Prohibited Items Detection in Noisy X-ray Images

Achieving Competitive Play Through Bottom-Up Approach in Semantic Segmentation

The Hessigheim 3D (H3D) Benchmark on Semantic Segmentation of High-Resolution 3D Point Clouds and Textured Meshes from UAV LiDAR and Multi-View-Stereo

Auto-Detection of Tibial Plateau Angle in Canine Radiographs Using a Deep Learning Approach

Image Augmentation for Multitask Few-Shot Learning: Agricultural Domain Use-Case

Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges

Rethinking Natural Adversarial Examples for Classification Models

Detecting soccer balls with reduced neural networks: a comparison of multiple architectures under constrained hardware scenarios

What's in my Room? Object Recognition on Indoor Panoramic Images

Deep Miner: A Deep and Multi-branch Network which Mines Rich and Diverse Features for Person Re-identification

A Self-Training Approach for Point-Supervised Object Detection and Counting in Crowds

LambdaNetworks: Modeling Long-Range Interactions Without Attention

Anchor Distance for 3D Multi-Object Distance Estimation from 2D Single Shot

DeepRA: Predicting Joint Damage From Radiographs Using CNN with Attention

Instance-Invariant Domain Adaptive Object Detection via Progressive Disentanglement

A novel method for object detection using deep learning and CAD models

Object Detection Under Rainy Conditions for Autonomous Vehicles: A Review of State-of-the-Art and Emerging Techniques

ABOShips -- An Inshore and Offshore Maritime Vessel Detection Dataset with Precise Annotations

Scale Normalized Image Pyramids with AutoFocus for Object Detection

Structure-Aware Completion of Photogrammetric Meshes in Urban Road Environment

RODNet: A Real-Time Radar Object Detection Network Cross-Supervised by Camera-Radar Fused Object 3D Localization

Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search

RMOPP: Robust Multi-Objective Post-Processing for Effective Object Detection

An Efficient Framework for Zero-Shot Sketch-Based Image Retrieval

DPointNet: A Density-Oriented PointNet for 3D Object Detection in Point Clouds

Gated3D: Monocular 3D Object Detection From Temporal Illumination Cues

Weighted boxes fusion: Ensembling boxes from different object detection models

Custom Object Detection via Multi-Camera Self-Supervised Learning

Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection

Autodidactic Neurosurgeon: Collaborative Deep Inference for Mobile Edge Intelligence via Online Learning

Evaluating Large-Vocabulary Object Detectors: The Devil is in the Details

Ground-aware Monocular 3D Object Detection for Autonomous Driving

Box Re-Ranking: Unsupervised False Positive Suppression for Domain Adaptive Pedestrian Detection

Towards Universal Physical Attacks On Cascaded Camera-Lidar 3D Object Detection Models

PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detection

MLMA-Net: multi-level multi-attentional learning for multi-label object detection in textile defect images

SA-Net: Shuffle Attention for Deep Convolutional Neural Networks

Latent-Space Inpainting for Packet Loss Concealment in Collaborative Object Detection

Synthetic Data and Hierarchical Object Detection in Overhead Imagery

Leveraging Orientation for Weakly Supervised Object Detection with Application to Firearm Localization

Gaining Scale Invariance in UAV Bird's Eye View Object Detection by Adaptive Resizing

IterDet: Iterative Scheme for Object Detection in Crowded Environments

A Scalable Multilabel Classification to Deploy Deep Learning Architectures For Edge Devices

CubifAE-3D: Monocular Camera Space Cubification for Auto-Encoder based 3D Object Detection

CoDeNet: Efficient Deployment of Input-Adaptive Object Detection on Embedded FPGAs

RGB-D Salient Object Detection via 3D Convolutional Neural Networks

Lightweight Convolutional Neural Network with Gaussian-based Grasping Representation for Robotic Grasping Detection

They See Me Rollin': Inherent Vulnerability of the Rolling Shutter in CMOS Image Sensors

A Comprehensive Survey on Hardware-Aware Neural Architecture Search

Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection

A two-stage data association approach for 3D Multi-object Tracking

COLLIDE-PRED: Prediction of On-Road Collision From Surveillance Videos

Knowledge Distillation for Incremental Learning in Semantic Segmentation

Curriculum Self-Paced Learning for Cross-Domain Object Detection

HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPS

Video Relation Detection with Trajectory-aware Multi-modal Features

Focal and Efficient IOU Loss for Accurate Bounding Box Regression

DNA: Deeply-supervised Nonlinear Aggregation for Salient Object Detection

Class balanced underwater object detection dataset generated by class-wise style augmentation

Online Active Proposal Set Generation for Weakly Supervised Object Detection

Multi-Task Network Pruning and Embedded Optimization for Real-time Deployment in ADAS

An Improvement of Object Detection Performance using Multi-step Machine Learnings

Regional Attention Network (RAN) for Head Pose and Fine-grained Gesture Recognition

PREGAN: Pose Randomization and Estimation for Weakly Paired Image Style Translation

VINNAS: Variational Inference-based Neural Network Architecture Search

Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision

Harmonic Convolutional Networks based on Discrete Cosine Transform

Automated Detection of Patellofemoral Osteoarthritis from Knee Lateral View Radiographs Using Deep Learning: Data from the Multicenter Osteoarthritis Study (MOST)

RethNet: Object-by-Object Learning for Detecting Facial Skin Problems

Explainable Artificial Intelligence (XAI): An Engineering Perspective

Heatmap-based Object Detection and Tracking with a Fully Convolutional Neural Network

Channel Boosting Feature Ensemble for Radar-based Object Detection

Salient Object Detection in the Deep Learning Era: An In-Depth Survey

From Black-box to White-box: Examining Confidence Calibration under different Conditions

A Density-Aware PointRCNN for 3D Object Detection in Point Clouds

Active learning for object detection in high-resolution satellite images

A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object Detection

A Robust Illumination-Invariant Camera System for Agricultural Applications

Dataset on Bi- and Multi-Nucleated Tumor Cells in Canine Cutaneous Mast Cell Tumors

A Framework for Fast Scalable BNN Inference using Googlenet and Transfer Learning

SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection

A New Window Loss Function for Bone Fracture Detection and Localization in X-ray Images with Point-based Annotation

Fooling Object Detectors: Adversarial Attacks by Half-Neighbor Masks

Weakly-Supervised Saliency Detection via Salient Object Subitizing

Data Augmentation via Mixed Class Interpolation using Cycle-Consistent Generative Adversarial Networks Applied to Cross-Domain Imagery

SID: Incremental Learning for Anchor-Free Object Detection via Selective and Inter-Related Distillation

SharpGAN: Receptive Field Block Net for Dynamic Scene Deblurring

YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design

RTS3D: Real-time Stereo 3D Detection from 4D Feature-Consistency Embedding Space for Autonomous Driving

Interpolation-based semi-supervised learning for object detection

Data-efficient Weakly-supervised Learning for On-line Object Detection under Domain Shift in Robotics

Ellipse Regression with Predicted Uncertainties for Accurate Multi-View 3D Object Estimation

Balance-Oriented Focal Loss with Linear Scheduling for Anchor Free Object Detection

Probabilistic 3D Multi-Modal, Multi-Object Tracking for Autonomous Driving

AmphibianDetector: adaptive computation for moving objects detection

Centralized Information Interaction for Salient Object Detection

Seed Phenotyping on Neural Networks using Domain Randomization and Transfer Learning

Towards Overcoming False Positives in Visual Relationship Detection

epBRM: Improving a Quality of 3D Object Detection using End Point Box Regression Module

Second-Moment Loss: A Novel Regression Objective for Improved Uncertainties

The Translucent Patch: A Physical and Universal Attack on Object Detectors

Limitation of Acyclic Oriented Graphs Matching as Cell Tracking Accuracy Measure when Evaluating Mitosis

PC-RGNN: Point Cloud Completion and Graph Neural Network for 3D Object Detection

Contraband Materials Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery

What You See is What You Get: Exploiting Visibility for 3D Object Detection

An Unsupervised Domain Adaptation Scheme for Single-Stage Artwork Recognition in Cultural Sites

Using Feature Alignment Can Improve Clean Average Precision and Adversarial Robustness in Object Detection

ResizeMix: Mixing Data with Preserved Object Information and True Labels

Static object detection and segmentation in videos based on dual foregrounds difference with noise filtering

Dense Multiscale Feature Fusion Pyramid Networks for Object Detection in UAV-Captured Images

A Systematic Evaluation of Object Detection Networks for Scientific Plots

SCNet: Training Inference Sample Consistency for Instance Segmentation

Labels Are Not Perfect: Inferring Spatial Uncertainty in Object Detection

Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose Annotations

Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices

FNA++: Fast Network Adaptation via Parameter Remapping and Architecture Search

Domain Adaptive Object Detection via Feature Separation and Alignment

Unsupervised Domain Adaptation from Synthetic to Real Images for Anchorless Object Detection

Decoupled Self Attention for Accurate One Stage Object Detection

Compressed Domain Image Classification Using a Dynamic-Rate Neural Network

The Open Brands Dataset: Unified brand detection and recognition at scale

On Focal Loss for Class-Posterior Probability Estimation: A Theoretical Perspective

ALET (Automated Labeling of Equipment and Tools): A Dataset, a Baseline and a Usecase for Tool Detection in the Wild

Using Computer Vision to Automate Hand Detection and Tracking of Surgeon Movements in Videos of Open Surgery

A new automatic approach to seed image analysis: From acquisition to segmentation

R-AGNO-RPN: A LIDAR-Camera Region Deep Network for Resolution-Agnostic Detection

HRCenterNet: An Anchorless Approach to Chinese Character Segmentation in Historical Documents

A Free Lunch for Unsupervised Domain Adaptive Object Detection without Source Data

Towards Better Object Detection in Scale Variation with Adaptive Feature Selection

JANUS: Benchmarking Commercial and Open-Source Cloud and Edge Platforms for Object and Anomaly Detection Workloads

Decoupled Classification Refinement: Hard False Positive Suppression for Object Detection

Structure-Consistent Weakly Supervised Salient Object Detection with Local Saliency Coherence

Semi-supervised Active Learning for Instance Segmentation via Scoring Predictions

Deep Learning based Multi-Modal Sensing for Tracking and State Extraction of Small Quadcopters

R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object

Cost-effective Machine Learning Inference Offload for Edge Computing

It's All Around You: Range-Guided Cylindrical Network for 3D Object Detection

FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding

Feature Sharing and Integration for Cooperative Cognition and Perception with Volumetric Sensors

Traffic Surveillance using Vehicle License Plate Detection and Recognition in Bangladesh

Generalized Object Detection on Fisheye Cameras for Autonomous Driving: Dataset, Representations and Baseline

Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection

A Simple Semi-Supervised Learning Framework for Object Detection

Meta-Cognition-Based Simple And Effective Approach To Object Detection

An Once-for-All Budgeted Pruning Framework for ConvNets Considering Input Resolution

Global Table Extractor (GTE): A Framework for Joint Table Identification and Cell Structure Recognition Using Visual Context

Monocular 3D Object Detection with Sequential Feature Association and Depth Hint Augmentation

A Unified Structure for Efficient RGB and RGB-D Salient Object Detection

DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution

RfD-Net: Point Scene Understanding by Semantic Instance Reconstruction

Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review

Rethinking Bottleneck Structure for Efficient Mobile Network Design

Towards real-time object recognition and pose estimation in point clouds

Temporal-Channel Transformer for 3D Lidar-Based Video Object Detection in Autonomous Driving

Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images

Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection

Detection as Regression: Certified Object Detection by Median Smoothing

Relation3DMOT: Exploiting Deep Affinity for 3D Multi-Object Tracking from View Aggregation

AutoAssign: Differentiable Label Assignment for Dense Object Detection

Multi-Stage CNN-Based Monocular 3D Vehicle Localization and Orientation Estimation

Robust Processing-In-Memory Neural Networks via Noise-Aware Normalization

KeepAugment: A Simple Information-Preserving Data Augmentation Approach

EAGLE: Large-scale Vehicle Detection Dataset in Real-World Scenarios using Aerial Imagery

YOdar: Uncertainty-based Sensor Fusion for Vehicle Detection with Camera and Radar Sensors

Industrial object, machine part and defect recognition towards fully automated industrial monitoring employing deep learning. The case of multilevel VGG19

Rethinking Transformer-based Set Prediction for Object Detection

Synthetic Image Rendering Solves Annotation Problem in Deep Learning Nanoparticle Segmentation

Joint Representation of Temporal Image Sequences and Object Motion for Video Object Detection

Cascade Attentive Dropout for Weakly Supervised Object Detection

Report on UG^2+ Challenge Track 1: Assessing Algorithms to Improve Video Object Detection and Classification from Unconstrained Mobility Platforms

DeepMorph: A System for Hiding Bitstrings in Morphable Vector Drawings

End-to-End Object Detection with Adaptive Clustering Transformer

RGBT Salient Object Detection: A Large-scale Dataset and Benchmark

EfficientPose: An efficient, accurate and scalable end-to-end 6D multi object pose estimation approach

Optimized Loss Functions for Object detection: A Case Study on Nighttime Vehicle Detection

Weakly Supervised Instance Segmentation by Deep Community Learning

FRDet: Balanced and Lightweight Object Detector based on Fire-Residual Modules for Embedded Processor of Autonomous Driving

Per-frame mAP Prediction for Continuous Performance Monitoring of Object Detection During Deployment

Ellipse R-CNN: Learning to Infer Elliptical Object from Clustering and Occlusion

G-RCN: Optimizing the Gap between Classification and Localization Tasks for Object Detection

Bi-Dimensional Feature Alignment for Cross-Domain Object Detection

Transformer-Encoder Detector Module: Using Context to Improve Robustness to Adversarial Attacks on Object Detection

Measuring Human and Economic Activity from Satellite Imagery to Support City-Scale Decision-Making during COVID-19 Pandemic

SVAM: Saliency-guided Visual Attention Modeling by Autonomous Underwater Robots

Real Time Multi-Class Object Detection and Recognition Using Vision Augmentation Algorithm

LittleYOLO-SPP: A Delicate Real-Time Vehicle Detection Algorithm

Learning from THEODORE: A Synthetic Omnidirectional Top-View Indoor Dataset for Deep Transfer Learning

On-Device Language Identification of Text in Images using Diacritic Characters

CoADNet: Collaborative Aggregation-and-Distribution Networks for Co-Salient Object Detection

Adjusting Bias in Long Range Stereo Matching: A semantics guided approach

Ellipse Detection and Localization with Applications to Knots in Sawn Lumber Images

CenterFusion: Center-based Radar and Camera Fusion for 3D Object Detection

Watch out! Motion is Blurring the Vision of Your Deep Neural Networks

Towards Resolving the Challenge of Long-tail Distribution in UAV Images for Object Detection

Improving Point Cloud Semantic Segmentation by Learning 3D Object Detection

Stochastic-YOLO: Efficient Probabilistic Object Detection under Dataset Shifts

Spatio-temporal Tubelet Feature Aggregation and Object Linking in Videos

Uncertainty-Aware Vehicle Orientation Estimation for Joint Detection-Prediction Models

Few-Shot Object Detection in Real Life: Case Study on Auto-Harvest

Uncertainty-Aware Voxel based 3D Object Detection and Tracking with von-Mises Loss

Learning Visual Representations for Transfer Learning by Suppressing Texture

CPM R-CNN: Calibrating Point-guided Misalignment in Object Detection

The Devil is in Classification: A Simple Framework for Long-tail Object Detection and Instance Segmentation

Content-based Analysis of the Cultural Differences between TikTok and Douyin

Cooperative Perception for 3D Object Detection in Driving Scenarios using Infrastructure Sensors

COBE: Contextualized Object Embeddings from Narrated Instructional Video

A Comprehensive Comparison of End-to-End Approaches for Handwritten Digit String Recognition

RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder

Object sieving and morphological closing to reduce false detections in wide-area aerial imagery

GAN Mask R-CNN:Instance semantic segmentation benefits from generativeadversarial networks

Multiple instance learning on deep features for weakly supervised object detection with extreme domain shifts

Representation Sharing for Fast Object Detector Search and Beyond

R-TOD: Real-Time Object Detector with Minimized End-to-End Delay for Autonomous Driving

Comprehensive Attention Self-Distillation for Weakly-Supervised Object Detection

Fine-tuned Pre-trained Mask R-CNN Models for Surface Object Detection

Efficient Scale-Permuted Backbone with Learned Resource Distribution

Bandwidth-Adaptive Feature Sharing for Cooperative LIDAR Object Detection

UFO$^2$: A Unified Framework towards Omni-supervised Object Detection

Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object Detection

Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region

ApproxDet: Content and Contention-Aware Approximate Object Detection for Mobiles

Image Captioning with Visual Object Representations Grounded in the Textual Modality

TTPLA: An Aerial-Image Dataset for Detection and Segmentation of Transmission Towers and Power Lines

SF-UDA$^{3D}$: Source-Free Unsupervised Domain Adaptation for LiDAR-Based 3D Object Detection

Unsupervised Domain Adaptation for Spatio-Temporal Action Localization

Vision-Based Layout Detection from Scientific Literature using Recurrent Convolutional Neural Networks

Neural Compression and Filtering for Edge-assisted Real-time Object Detection in Challenged Networks

PolarDet: A Fast, More Precise Detector for Rotated Target in Aerial Images

DPAttack: Diffused Patch Attacks against Universal Object Detection

CVPR 2019 WAD Challenge on Trajectory Prediction and 3D Perception

LaserFlow: Efficient and Probabilistic Object Detection and Motion Forecasting

A Simple Non-i.i.d. Sampling Approach for Efficient Training and Better Generalization

Privacy-Preserving Object Detection & Localization Using Distributed Machine Learning: A Case Study of Infant Eyeblink Conditioning

A Very Compact Embedded CNN Processor Design Based on Logarithmic Computing

Object as Hotspots: An Anchor-Free 3D Object Detection Approach via Firing of Hotspots

The MECCANO Dataset: Understanding Human-Object Interactions from Egocentric Videos in an Industrial-like Domain

Learning Selective Mutual Attention and Contrast for RGB-D Saliency Detection

Boosted Semantic Embedding based Discriminative Feature Generation for Texture Analysis

Towards Class-incremental Object Detection with Nearest Mean of Exemplars

3D Object Detection and Pose Estimation of Unseen Objects in Color Images with Local Surface Embeddings

UESegNet: Context Aware Unconstrained ROI Segmentation Networks for Ear Biometric

Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels

MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection

Joint COCO and Mapillary Workshop at ICCV 2019: COCO Instance Segmentation Challenge Track

Video Anomaly Detection Using Pre-Trained Deep Convolutional Neural Nets and Context Mining

Conditional Negative Sampling for Contrastive Learning of Visual Representations

Background Adaptive Faster R-CNN for Semi-Supervised Convolutional Object Detection of Threats in X-Ray Images

Delving into Robust Object Detection from Unmanned Aerial Vehicles: A Deep Nuisance Disentanglement Approach

Embedded Systems and Computer Vision Techniques utilized in Spray Painting Robots: A Review

Dynamic Graph: Learning Instance-aware Connectivity for Neural Networks

A Parallel Down-Up Fusion Network for Salient Object Detection in Optical Remote Sensing Images

A novel Region of Interest Extraction Layer for Instance Segmentation

Learning Object Detection from Captions via Textual Scene Attributes

Monocular Differentiable Rendering for Self-Supervised 3D Object Detection

Robust Detection of Objects under Periodic Motion with Gaussian Process Filtering

Localize to Classify and Classify to Localize: Mutual Guidance in Object Detection

MLOD: Awareness of Extrinsic Perturbation in Multi-LiDAR 3D Object Detection for Autonomous Driving

DPANet: Depth Potentiality-Aware Gated Attention Network for RGB-D Salient Object Detection

Pixel-Semantic Revise of Position Learning A One-Stage Object Detector with A Shared Encoder-Decoder

Perceptual underwater image enhancement with deep learning and physical priors

Multispectral Fusion for Object Detection with Cyclic Fuse-and-Refine Blocks

Few-shot Object Detection with Self-adaptive Attention Network for Remote Sensing Images

A Few-shot Learning Approach for Historical Ciphered Manuscript Recognition

Tied Block Convolution: Leaner and Better CNNs with Shared Thinner Filters

An original framework for Wheat Head Detection using Deep, Semi-supervised and Ensemble Learning within Global Wheat Head Detection (GWHD) Dataset

CoFF: Cooperative Spatial Feature Fusion for 3D Object Detection on Autonomous Vehicles

Multi-Frame to Single-Frame: Knowledge Distillation for 3D Object Detection

CLASS: Cross-Level Attention and Supervision for Salient Objects Detection

MimicDet: Bridging the Gap Between One-Stage and Two-Stage Object Detection

Curriculum Learning with Diversity for Supervised Computer Vision Tasks

Objects detection for remote sensing images based on polar coordinates

It's Raining Cats or Dogs? Adversarial Rain Attack on DNN Perception

IDA: Improved Data Augmentation Applied to Salient Object Detection

Moving object detection for visual odometry in a dynamic environment based on occlusion accumulation

Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection

Radar-Camera Sensor Fusion for Joint Object Detection and Distance Estimation in Autonomous Vehicles

Dynamic Edge Weights in Graph Neural Networks for 3D Object Detection

CSI2Image: Image Reconstruction from Channel State Information Using Generative Adversarial Networks

Knowledge Guided Learning: Towards Open Domain Egocentric Action Recognition with Zero Supervision

Monitoring Spatial Sustainable Development: semi-automated analysis of Satellite and Aerial Images for Energy Transition and Sustainability Indicators

Key-Nets: Optical Transformation Convolutional Networks for Privacy Preserving Vision Sensors

Image Conditioned Keyframe-Based Video Summarization Using Object Detection

A Comparison of Deep Learning Object Detection Models for Satellite Imagery

Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review

FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking

SoccerDB: A Large-Scale Database for Comprehensive Video Understanding

A Review on Near Duplicate Detection of Images using Computer Vision Techniques

Object Detection for Graphical User Interface: Old Fashioned or Deep Learning or a Combination?

A Light-Weight Object Detection Framework with FPA Module for Optical Remote Sensing Imagery

Rain rendering for evaluating and improving robustness to bad weather

Probabilistic Anchor Assignment with IoU Prediction for Object Detection

Modification method for single-stage object detectors that allows to exploit the temporal behaviour of a scene to improve detection accuracy

Few-shot Object Detection with Feature Attention Highlight Module in Remote Sensing Images

Temporal Self-Ensembling Teacher for Semi-Supervised Object Detection

CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detection

Monocular 3D Detection with Geometric Constraints Embedding and Semi-supervised Training

Topological Sweep for Multi-Target Detection of Geostationary Space Objects

LabelEnc: A New Intermediate Supervision Method for Object Detection

Radar+RGB Attentive Fusion for Robust Object Detection in Autonomous Vehicles

Cheaper Pre-training Lunch: An Efficient Paradigm for Object Detection

Evaluating Single Image Dehazing Methods Under Realistic Sunlight Haze

TENet: Triple Excitation Network for Video Salient Object Detection

Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors

PV-RCNN: The Top-Performing LiDAR-only Solutions for 3D Detection / 3D Tracking / Domain Adaptation of Waymo Open Dataset Challenges

Fast Single-shot Ship Instance Segmentation Based on Polar Template Mask in Remote Sensing Images

Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving

Many-shot from Low-shot: Learning to Annotate using Mixed Supervision for Object Detection

Side-Aware Boundary Localization for More Precise Object Detection

Fusion of Global-Local Features for Image Quality Inspection of Shipping Label

Using the discrete radon transformation for grayscale image moments

Strawberry Detection using Mixed Training on Simulated and Real Data

Towards Autonomous Driving: a Multi-Modal 360$^{\circ}$ Perception Proposal

Blending of Learning-based Tracking and Object Detection for Monocular Camera-based Target Following

ASAP-NMS: Accelerating Non-Maximum Suppression Using Spatially Aware Priors

APRICOT: A Dataset of Physical Adversarial Attacks on Object Detection

Deformable PV-RCNN: Improving 3D Object Detection with Learned Deformations

OS2D: One-Stage One-Shot Object Detection by Matching Anchor Features

Gradually Applying Weakly Supervised and Active Learning for Mass Detection in Breast Ultrasound Images

CCA: Exploring the Possibility of Contextual Camouflage Attack on Object Detection

Learning Connectivity of Neural Networks from a Topological Perspective

Multilanguage Number Plate Detection using Convolutional Neural Networks

MVLidarNet: Real-Time Multi-Class Scene Understanding for Autonomous Driving Using Multiple Views

Towards Better Performance and More Explainable Uncertainty for 3D Object Detection of Autonomous Vehicles

Progressively Guided Alternate Refinement Network for RGB-D Salient Object Detection

A novel approach to remove foreign objects from chest X-ray images

Object Detection with a Unified Label Space from Multiple Datasets

Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

Occluded Prohibited Items Detection: an X-ray Security Inspection Benchmark and De-occlusion Attention Module

HOSE-Net: Higher Order Structure Embedded Network for Scene Graph Generation

SIDOD: A Synthetic Image Dataset for 3D Object Pose Recognition with Distractors

Labels Are Not Perfect: Improving Probabilistic Object Detection via Label Uncertainty

Rethinking of the Image Salient Object Detection: Object-level Semantic Saliency Re-ranking First, Pixel-wise Saliency Refinement Latter

Micro-Batch Training with Batch-Channel Normalization and Weight Standardization

MOR-UAV: A Benchmark Dataset and Baselines for Moving Object Recognition in UAV Videos

Cascade Graph Neural Networks for RGB-D Salient Object Detection

Knowing Depth Quality In Advance: A Depth Quality Assessment Method For RGB-D Salient Object Detection

Recursive Multi-model Complementary Deep Fusion forRobust Salient Object Detection via Parallel Sub Networks

Data-Level Recombination and Lightweight Fusion Scheme for RGB-D Salient Object Detection

Exploring Rich and Efficient Spatial Temporal Interactions for Real Time Video Salient Object Detection

A Novel Video Salient Object Detection Method via Semi-supervised Motion Quality Perception

A Deeper Look at Salient Object Detection: Bi-stream Network with a Small Training Dataset

IIIT-AR-13K: A New Dataset for Graphical Object Detection in Documents

U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection

1st Place Solutions of Waymo Open Dataset Challenge 2020 -- 2D Object Detection Track

Hierarchical Context Embedding for Region-based Object Detection

Multi-Class 3D Object Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery

Solving Missing-Annotation Object Detection with Background Recalibration Loss

Point-Set Anchors for Object Detection, Instance Segmentation and Pose Estimation

PP-YOLO: An Effective and Efficient Implementation of Object Detector

Utilising Visual Attention Cues for Vehicle Detection and Tracking

Object Detection and Tracking Algorithms for Vehicle Counting: A Comparative Analysis

Exploring Image Enhancement for Salient Object Detection in Low Light Images

Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses

Unidentified Floating Object detection in maritime environment using dictionary learning

MnasFPN: Learning Latency-aware Pyramid Architecture for Object Detection on Mobile Devices

Black-box Adversarial Sample Generation Based on Differential Evolution

SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation

Detection and Localization of Robotic Tools in Robot-Assisted Surgery Videos Using Deep Neural Networks for Region Proposal and Detection

Can Your Face Detector Do Anti-spoofing? Face Presentation Attack Detection with a Multi-Channel Face Detector

A Deep Learning-based Detector for Brown Spot Disease in Passion Fruit Plant Leaves

Chained-Tracker: Chaining Paired Attentive Regression Results for End-to-End Joint Multiple-Object Detection and Tracking

RadarNet: Exploiting Radar for Robust Perception of Dynamic Objects

Context-Aware Dynamic Feature Extraction for 3D Object Detection in Point Clouds

On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures

Accurate, Low-Latency Visual Perception for Autonomous Racing:Challenges, Mechanisms, and Practical Solutions

Corner Proposal Network for Anchor-free, Two-stage Object Detection

Two-Level Residual Distillation based Triple Network for Incremental Object Detection

Suppress and Balance: A Simple Gated Network for Salient Object Detection

Research Progress of Convolutional Neural Network and its Application in Object Detection

Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training

Improving Object Detection with Selective Self-supervised Self-training

An LSTM Approach to Temporal 3D Object Detection in LiDAR Point Clouds

Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild

Leveraging Bottom-Up and Top-Down Attention for Few-Shot Object Detection

A Study on Evaluation Standard for Automatic Crack Detection Regard the Random Fractal

Accurate RGB-D Salient Object Detection via Collaborative Learning

Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors

Finding Your (3D) Center: 3D Object Detection Using a Learned Loss

Spatial Attention Pyramid Network for Unsupervised Domain Adaptation

Learning to Exploit Multiple Vision Modalities by Using Grafted Networks

3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for 3D Object Detection

Broad Area Search and Detection of Surface-to-Air Missile Sites Using Spatial Fusion of Component Object Detections from Deep Neural Networks

Learning to Separate: Detecting Heavily-Occluded Objects in Urban Scenes

DeepACEv2: Automated Chromosome Enumeration in Metaphase Cell Images Using Deep Convolutional Neural Networks

PIoU Loss: Towards Accurate Oriented Object Detection in Complex Environments

Multi-Scale Positive Sample Refinement for Few-Shot Object Detection

AABO: Adaptive Anchor Box Optimization for Object Detection via Bayesian Sub-sampling

Analyzing and Improving Neural Networks by Generating Semantic Counterexamples through Differentiable Rendering

EPNet: Enhancing Point Features with Image Semantics for 3D Object Detection

2nd Place Solution to ECCV 2020 VIPriors Object Detection Challenge

CASNet: Common Attribute Support Network for image instance and panoptic segmentation

Advances in Deep Learning for Hyperspectral Image Analysis--Addressing Challenges Arising in Practical Imaging Scenarios

Improving 3D Object Detection through Progressive Population Based Augmentation

InfoFocus: 3D Object Detection for Autonomous Driving with Dynamic Information Modeling

RepPoints V2: Verification Meets Regression for Object Detection

Hierarchical Dynamic Filtering Network for RGB-D Salient Object Detection

CenterNet3D:An Anchor free Object Detector for Autonomous Driving

TrashCan: A Semantically-Segmented Dataset towards Visual Detection of Marine Debris

Boosting Weakly Supervised Object Detection with Progressive Knowledge Transfer

Tracking Passengers and Baggage Items using Multi-camera Systems at Security Checkpoints

Prior-based Domain Adaptive Object Detection for Hazy and Rainy Conditions

Borrow from Anywhere: Pseudo Multi-modal Object Detection in Thermal Imagery

A Single Stream Network for Robust and Real-time RGB-D Salient Object Detection

Automatic extraction of road intersection points from USGS historical map series using deep convolutional neural networks

RGB-D Salient Object Detection with Cross-Modality Modulation and Selection

Towards Best Practice in Explaining Neural Network Decisions with LRP

Automatic Pass Annotation from Soccer VideoStreams Based on Object Detection and LSTM

Location-Aware Box Reasoning for Anchor-Based Single-Shot Object Detection

Traffic Prediction Framework for OpenStreetMap using Deep Learning based Complex Event Processing and Open Traffic Cameras

Learning to associate detections for real-time multiple object tracking

Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks

Are pathologist-defined labels reproducible? Comparison of the TUPAC16 mitotic figure dataset with an alternative set of labels

FathomNet: An underwater image training database for ocean exploration and discovery

AdaScale SGD: A User-Friendly Algorithm for Distributed Training

Cross-Modal Weighting Network for RGB-D Salient Object Detection

Building Robust Industrial Applicable Object Detection Models Using Transfer Learning and Single Pass Deep Learning Architectures

A Quick Review on Recent Trends in 3D Point Cloud Data Compression Techniques and the Challenges of Direct Processing in 3D Compressed Domain

Deep Learning for Apple Diseases: Classification and Identification

Learning a Domain Classifier Bank for Unsupervised Adaptive Object Detection

Local Grid Rendering Networks for 3D Object Detection in Point Clouds

Efficient and accurate object detection with simultaneous classification and tracking

Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies

Learning Permutation Invariant Representations using Memory Networks

Domain Adaptive Object Detection via Asymmetric Tri-way Faster-RCNN

Deep Learning Models for Visual Inspection on Automotive Assembling Line

TiledSoilingNet: Tile-level Soiling Detection on Automotive Surround-view Cameras Using Coverage Metric

Group Ensemble: Learning an Ensemble of ConvNets in a single ConvNet

Optimisation of the PointPillars network for 3D object detection in point clouds

Automatic Crack Detection on Road Pavements Using Encoder Decoder Architecture

Data-Efficient Image Recognition with Contrastive Predictive Coding

Boosting Deep Neural Networks with Geometrical Prior Knowledge: A Survey

Seeing Through Fog Without Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather

Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints

MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time

A Benchmark dataset for both underwater image enhancement and underwater object detection

Compositional Convolutional Neural Networks: A Robust and Interpretable Model for Object Recognition under Occlusion

2nd Place Solution for Waymo Open Dataset Challenge -- 2D Object Detection

1st Place Solution for Waymo Open Dataset Challenge -- 3D Detection and Domain Adaptation

Self-supervised Robust Object Detectors from Partially Labelled Datasets

3D Object Detection on Point Clouds using Local Ground-aware and Adaptive Representation of scenes' surface

Resisting Crowd Occlusion and Hard Negatives for Pedestrian Detection in the Wild

DCNNs: A Transfer Learning comparison of Full Weapon Family threat detection for Dual-Energy X-Ray Baggage Imagery

Boundary Regularized Building Footprint Extraction From Satellite Images Using Deep Neural Network

Single-Shot 3D Detection of Vehicles from Monocular RGB Images via Geometry Constrained Keypoints in Real-Time

SLV: Spatial Likelihood Voting for Weakly Supervised Object Detection

iffDetector: Inference-aware Feature Filtering for Object Detection

Category-wise Attack: Transferable Adversarial Examples for Anchor Free Object Detection

Generative Sparse Detection Networks for 3D Single-shot Object Detection

High-Precision Digital Traffic Recording with Multi-LiDAR Infrastructure Sensor Setups

Semi-Supervised Object Detection with Sparsely Annotated Dataset

Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection

AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning

Shop The Look: Building a Large Scale Visual Shopping System at Pinterest

Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax

The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOps

Fast Object Classification and Meaningful Data Representation of Segmented Lidar Instances

SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization

PointVoteNet: Accurate Object Detection and 6 DoF Pose Estimation in Point Clouds

LRPD: Long Range 3D Pedestrian Detection Leveraging Specific Strengths of LiDAR and RGB

Foreground-Background Imbalance Problem in Deep Object Detectors: A Review

Visibility Guided NMS: Efficient Boosting of Amodal Object Detection in Crowded Traffic Scenes

Star-convex Polyhedra for 3D Object Detection and Segmentation in Microscopy

Estimation of a function of low local dimensionality by deep neural networks

Working with scale: 2nd place solution to Product Detection in Densely Packed Scenes [Technical Report]

Learning a Unified Sample Weighting Network for Object Detection

Hyper RPCA: Joint Maximum Correntropy Criterion and Laplacian Scale Mixture Modeling On-the-Fly for Moving Object Detection

Bonseyes AI Pipeline -- bringing AI to you. End-to-end integration of data, algorithms and deployment tools

Dynamic Refinement Network for Oriented and Densely Packed Object Detection

VecQ: Minimal Loss DNN Model Compression With Vectorized Weight Quantization

TubeTK: Adopting Tubes to Track Multi-Object in a One-Step Training Model

Off-the-shelf sensor vs. experimental radar -- How much resolution is necessary in automotive radar classification?

Stereo RGB and Deeper LIDAR Based Network for 3D Object Detection

Can Synthetic Data Improve Object Detection Results for Remote Sensing Images?

Passive Batch Injection Training Technique: Boosting Network Performance by Injecting Mini-Batches from a different Data Distribution

Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection

Associate-3Ddet: Perceptual-to-Conceptual Association for 3D Point Cloud Object Detection

Deep Neural Network Based Real-time Kiwi Fruit Flower Detection in an Orchard Environment

Enabling Incremental Knowledge Transfer for Object Detection at the Edge

SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds

Exploiting Temporal Coherence for Multi-modal Video Categorization

Adaptive and Azimuth-Aware Fusion Network of Multimodal Local Features for 3D Object Detection

Resolving Class Imbalance in Object Detection with Weighted Cross Entropy Losses

Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples

Symbol Spotting on Digital Architectural Floor Plans Using a Deep Learning-based Framework

Robust Object Detection under Occlusion with Context-Aware CompositionalNets

Squeezed Deep 6DoF Object Detection Using Knowledge Distillation

LR-CNN: Local-aware Region CNN for Vehicle Detection in Aerial Imagery

Overview: Computer vision and machine learning for microstructural characterization and analysis

Center3D: Center-based Monocular 3D Object Detection with Joint Depth Understanding

Target-Tailored Source-Transformation for Scene Graph Generation

Accelerating Neural Network Inference by Overflow Aware Quantization

Concurrent Segmentation and Object Detection CNNs for Aircraft Detection and Identification in Satellite Images

Joint Detection and Tracking in Videos with Identification Features

Underwater object detection using Invert Multi-Class Adaboost with deep learning

Attention-guided Context Feature Pyramid Network for Object Detection

Delving into the Imbalance of Positive Proposals in Two-stage Object Detection

Hashing-based Non-Maximum Suppression for Crowded Object Detection

Image Translation by Latent Union of Subspaces for Cross-Domain Plaque Detection

KL-Divergence-Based Region Proposal Network for Object Detection

Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

A Fixation-based 360° Benchmark Dataset for Salient Object Detection

Synthesizing Unrestricted False Positive Adversarial Objects Using Generative Models

Large-Scale Object Detection in the Wild from Imbalanced Multi-Labels

Learning from Unlabelled Videos Using Contrastive Predictive Neural 3D Mapping

Train in Germany, Test in The USA: Making 3D Object Detectors Generalize

\emph{cm}SalGAN: RGB-D Salient Object Detection with Cross-View Generative Adversarial Networks

Ventral-Dorsal Neural Networks: Object Detection via Selective Attention

FuSSI-Net: Fusion of Spatio-temporal Skeletons for Intention Prediction Network

A Deep Learning-based Radar and Camera Sensor Fusion Architecture for Object Detection

Exploring the Capabilities and Limits of 3D Monocular Object Detection -- A Study on Simulation and Real World Data

Temperate Fish Detection and Classification: a Deep Learning based Approach

A High-Performance Object Proposals based on Horizontal High Frequency Signal

Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles

Apple Defect Detection Using Deep Learning Based Object Detection For Better Post Harvest Handling

LRCN-RetailNet: A recurrent neural network architecture for accurate people counting

SAC-Net: Spatial Attenuation Context for Salient Object Detection

Stillleben: Realistic Scene Synthesis for Deep Learning in Robotics

Attention-based Assisted Excitation for Salient Object Detection

Deep Learning Based Vehicle Tracking System Using License Plate Detection And Recognition

Contrast-weighted Dictionary Learning Based Saliency Detection for Remote Sensing Images

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector

A Computationally Efficient Pipeline Approach to Full Page Offline Handwritten Text Recognition

View Invariant Human Body Detection and Pose Estimation from Multiple Depth Sensors

STINet: Spatio-Temporal-Interactive Network for Pedestrian Detection and Trajectory Prediction

IPG-Net: Image Pyramid Guidance Network for Small Object Detection

Automatic Detection and Recognition of Individuals in Patterned Species

Drosophila-Inspired 3D Moving Object Detection Based on Point Clouds

A Neural Model for Text Localization, Transcription and Named Entity Recognition in Full Pages

Automated eye disease classification method from anterior eye image using anatomical structure focused image classification technique

LIMEtree: Interactively Customisable Explanations Based on Local Surrogate Multi-output Regression Trees

Weighted Average Precision: Adversarial Example Detection in the Visual Perception of Autonomous Vehicles

Salient Object Detection Combining a Self-attention Module and a Feature Pyramid Network

Deep SCNN-based Real-time Object Detection for Self-driving Vehicles Using LiDAR Temporal Data

Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network

SCRDet++: Detecting Small, Cluttered and Rotated Objects via Instance-Level Feature Denoising and Rotation Loss Smoothing

Localizing Grouped Instances for Efficient Detection in Low-Resource Scenarios

On the safety of vulnerable road users by cyclist orientation detection using Deep Learning

Detective: An Attentive Recurrent Model for Sparse Object Detection

Any Motion Detector: Learning Class-agnostic Scene Dynamics from a Sequence of LiDAR Point Clouds

Label-PEnet: Sequential Label Propagation and Enhancement Networks for Weakly Supervised Instance Segmentation

Distilling Knowledge from Refinement in Multiple Instance Detection Networks

Aerial Images Processing for Car Detection using Convolutional Neural Networks: Comparison between Faster R-CNN and YoloV3

Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning

Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection

Comparison of object detection methods for crop damage assessment using deep learning

3D Object Detection Method Based on YOLO and K-Means for Image and Point Clouds

YOLO and K-Means Based 3D Object Detection Method on Image and Point Cloud

Mixture Dense Regression for Object Detection and Human Pose Estimation

Lightweight Mask R-CNN for Long-Range Wireless Power Transfer Systems

Learning to Evaluate Perception Models Using Planner-Centric Metrics

An end-to-end CNN framework for polarimetric vision tasks based on polarization-parameter-constructing network

JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection

Role of Spatial Context in Adversarial Robustness for Object Detection

A Deep Learning Framework for Detection of Targets in Thermal Images to Improve Firefighting

Object Detection and Recognition of Swap-Bodies using Camera mounted on a Vehicle

Active Learning with Point Supervision for Cost-Effective Panicle Detection in Cereal Crops

RescueNet: Joint Building Segmentation and Damage Assessment from Satellite Imagery

Developing a Recommendation Benchmark for MLPerf Training and Inference

WQT and DG-YOLO: towards domain generalization in underwater object detection

An Efficient UAV-based Artificial Intelligence Framework for Real-Time Visual Tasks

Domain Generalization via Universal Non-volume Preserving Models

Dont Even Look Once: Synthesizing Features for Zero-Shot Detection

FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary

Decoupled Gradient Harmonized Detector for Partial Annotation: Application to Signet Ring Cell Detection

Fast Neural Network Adaptation via Parameter Remapping and Architecture Search

TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems

Gliding vertex on the horizontal bounding box for multi-oriented object detection

Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation

MUXConv: Information Multiplexing in Convolutional Neural Networks

ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks

DAPAS : Denoising Autoencoder to Prevent Adversarial attack in Semantic Segmentation

SSN: Shape Signature Networks for Multi-class Object Detection from Point Clouds

Feature Super-Resolution Based Facial Expression Recognition for Multi-scale Low-Resolution Faces

Empirical Upper Bound, Error Diagnosis and Invariance Analysis of Modern Object Detectors

Quantifying Data Augmentation for LiDAR based 3D Object Detection

DFNet: Discriminative feature extraction and integration network for salient object detection

LiDAR-based Online 3D Video Object Detection with Graph-based Message Passing and Spatiotemporal Transformer Attention

Combining Visible and Infrared Spectrum Imagery using Machine Learning for Small Unmanned Aerial System Detection

Physically Realizable Adversarial Examples for LiDAR Object Detection

RN-VID: A Feature Fusion Architecture for Video Object Detection

Towards Generalization Across Depth for Monocular 3D Object Detection

Safety-Aware Hardening of 3D Object Detection Neural Network Systems

Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks

Region Proposal Network with Graph Prior and IoU-Balance Loss for Landmark Detection in 3D Ultrasound

Boundary-Aware Dense Feature Indicator for Single-Stage 3D Object Detection from Point Clouds

Neural Data Server: A Large-Scale Search Engine for Transfer Learning Data

MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization

Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming

Learning Human-Object Interaction Detection using Interaction Points

3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segmentation

Seeing without Looking: Contextual Rescoring of Object Detections for AP Maximization

Predicting Semantic Map Representations from Images using Pyramid Occupancy Networks

Cross-Domain Document Object Detection: Benchmark Suite and Method

Refined Plane Segmentation for Cuboid-Shaped Objects by Leveraging Edge Detection

On the Evaluation of Prohibited Item Classification and Detection in Volumetric 3D Computed Tomography Baggage Security Screening Imagery

Memory Enhanced Global-Local Aggregation for Video Object Detection

Pseudo-Labeling for Small Lesion Detection on Diabetic Retinopathy Images

Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection

PPDM: Parallel Point Detection and Matching for Real-time Human-Object Interaction Detection

Cylindrical Convolutional Networks for Joint Object Detection and Viewpoint Estimation

What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective

GeoGraph: Learning graph-based multi-view object detection with geometric cues end-to-end

RoIMix: Proposal-Fusion among Multiple Images for Underwater Object Detection

Real-time 3D object proposal generation and classification under limited processing resources

A Simple Fix for Convolutional Neural Network via Coordinate Embedding

MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and Resolution

Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation

BABO: Background Activation Black-Out for Efficient Object Detection

Multi-Plateau Ensemble for Endoscopic Artefact Segmentation and Detection

RefineDetLite: A Lightweight One-stage Object Detection Framework for CPU-only Devices

Self-Guided Adaptation: Progressive Representation Alignment for Domain Adaptive Object Detection

Review of data analysis in vision inspection of power lines with an in-depth discussion of deep learning technology

Exploring Bottom-up and Top-down Cues with Attentive Learning for Webly Supervised Object Detection

Exploring Categorical Regularization for Domain Adaptive Object Detection

CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection

Weakly Supervised Object Detection with 2D and 3D Regression Neural Networks

Evaluating Salient Object Detection in Natural Images with Multiple Objects having Multi-level Saliency

Post-Training Piecewise Linear Quantization for Deep Neural Networks

Training Quantized Neural Networks with a Full-precision Auxiliary Module

LapNet : Automatic Balanced Loss and Optimal Assignment for Real-Time Dense Object Detection

Weakly-Supervised Salient Object Detection via Scribble Annotations

1st Place Solutions for OpenImage2019 -- Object Detection and Instance Segmentation

Deep Object Detection based Mitosis Analysis in Breast Cancer Histopathological Images

Context-Transformer: Tackling Object Confusion for Few-Shot Detection

From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network

MotionNet: Joint Perception and Motion Prediction for Autonomous Driving Based on Bird's Eye View Maps

Meta R-CNN : Towards General Solver for Instance-level Few-shot Learning

Joint Anchor-Feature Refinement for Real-Time Accurate Object Detection in Images and Videos

Harmonizing Transferability and Discriminability for Adapting Object Detectors

Confidence Guided Stereo 3D Object Detection with Split Depth Estimation

DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs (Extended)

BirdNet+: End-to-End 3D Object Detection in LiDAR Bird's Eye View

iFAN: Image-Instance Full Alignment Networks for Adaptive Object Detection

Learned Enrichment of Top-View Grid Maps Improves Object Detection

Spherical formulation of moving object geometric constraints for monocular fisheye cameras

Traffic Signs Detection and Recognition System using Deep Learning

Reveal of Domain Effect: How Visual Restoration Contributes to Object Detection in Aquatic Scenes

DeepSperm: A robust and real-time bull sperm-cell detection in densely populated semen videos

3D Object Detection From LiDAR Data Using Distance Dependent Feature Extraction

Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud

DEEVA: A Deep Learning and IoT Based Computer Vision System to Address Safety and Security of Production Sites in Energy Industry

Plug & Play Convolutional Regression Tracker for Video Object Detection

Global Context-Aware Progressive Aggregation Network for Salient Object Detection

ZoomNet: Part-Aware Adaptive Zooming Neural Network for 3D Object Detection

MonoPair: Monocular 3D Object Detection Using Pairwise Spatial Relationships

Learning from Suspected Target: Bootstrapping Performance for Breast Cancer Detection in Mammography

Adapted Center and Scale Prediction: More Stable and More Accurate

SkyNet: a Hardware-Efficient Method for Object Detection and Tracking on Embedded Systems

Hazard Detection in Supermarkets using Deep Learning on the Edge

"Who is Driving around Me?" Unique Vehicle Instance Classification using Deep Neural Features

A Video Analysis Method on Wanfang Dataset via Deep Neural Network

Target Detection, Tracking and Avoidance System for Low-cost UAVs using AI-Based Approaches

SilhoNet-Fisheye: Adaptation of A ROI Based Object Pose Estimation Network to Monocular Fisheye Images

Active query-driven visual search using probabilistic bisection and convolutional neural networks

Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image

Chargrid-OCR: End-to-end Trainable Optical Character Recognition for Printed Documents using Instance Segmentation

PointTrackNet: An End-to-End Network For 3-D Object Detection and Tracking From Point Clouds

Progressive Gradient Pruning for Classification, Detection and DomainAdaptation

MDSSD: Multi-scale Deconvolutional Single Shot Detector for Small Objects

Cross-layer Feature Pyramid Network for Salient Object Detection

An Explicit Local and Global Representation Disentanglement Framework with Applications in Deep Clustering and Unsupervised Object Detection

SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation

Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving

The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale

Classification and Disease Localization in Histopathology Using Only Global Labels: A Weakly-Supervised Approach

ViP: Virtual Pooling for Accelerating CNN-based Image Classification and Object Detection

Learning Object Scale With Click Supervision for Object Detection

Cooperative LIDAR Object Detection via Feature Sharing in Deep Networks

siaNMS: Non-Maximum Suppression with Siamese Networks for Multi-Camera 3D Object Detection

EHSOD: CAM-Guided End-to-end Hybrid-Supervised Object Detection with Cascade Refinement

Universal-RCNN: Universal Object Detector via Transferable Graph R-CNN

Generating Interpretable Poverty Maps using Object Detection in Satellite Images

Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving

Object Detection on Single Monocular Images through Canonical Correlation Analysis

Retrain or not retrain? -- efficient pruning methods of deep CNN networks

Center and Scale Prediction: A Box-free Approach for Pedestrian and Face Detection

Fast Underwater Image Enhancement for Improved Visual Perception

Symbiotic Attention with Privileged Information for Egocentric Action Recognition

Training Set Effect on Super Resolution for Automated Target Recognition

Frustum VoxNet for 3D object detection from RGB-D or Depth images

Learning an Uncertainty-Aware Object Detector for Autonomous Driving

Evaluating and Calibrating Uncertainty Prediction in Regression Tasks

Single-Stage Object Detection from Top-View Grid Maps on Custom Sensor Setups

AU-AIR: A Multi-modal Unmanned Aerial Vehicle Dataset for Low Altitude Traffic Surveillance

Unsupervised Domain Adaptive Object Detection using Forward-Backward Cyclic Adaptation

S-DOD-CNN: Doubly Injecting Spatially-Preserved Object Information for Event Recognition

ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes

CodeReef: an open platform for portable MLOps, reusable automation actions and reproducible benchmarking

UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking

GTNet: Generative Transfer Network for Zero-Shot Object Detection

PENet: Object Detection using Points Estimation in Aerial Images

Depthwise Non-local Module for Fast Salient Object Detection Using a Single Thread

Real-Time Object Detection and Recognition on Low-Compute Humanoid Robots using Deep Learning

NETNet: Neighbor Erasing and Transferring Network for Better Single Shot Object Detection

ScarfNet: Multi-scale Features with Deeply Fused and Redistributed Semantics for Enhanced Object Detection

FedVision: An Online Visual Object Detection Platform Powered by Federated Learning

Analysis and a Solution of Momentarily Missed Detection for Anchor-based Object Detectors

Moving Objects Detection with a Moving Camera: A Comprehensive Review

CS-R-FCN: Cross-supervised Learning for Large-Scale Object Detection

SVIRO: Synthetic Vehicle Interior Rear Seat Occupancy Dataset and Benchmark

MatrixNets: A New Scale and Aspect Ratio Aware Architecture for Object Detection

Benchmark for Generic Product Detection: A Low Data Baseline for Dense Object Detection

Robust, Extensible, and Fast: Teamed Classifiers for Vehicle Tracking and Vehicle Re-ID in Multi-Camera Networks

Accuracy Booster: Performance Boosting using Feature Map Re-calibration

An Improving Framework of regularization for Network Compression

MinneApple: A Benchmark Dataset for Apple Detection and Segmentation

Mixed-Precision Quantized Neural Network with Progressively Decreasing Bitwidth For Image Classification and Object Detection

3D Sensing of a Moving Object with a Nodding 2D LIDAR and Reconfigurable Mirrors

FisheyeMultiNet: Real-time Multi-task Learning Architecture for Surround-view Automated Parking System

A Survey of Deep Learning Applications to Autonomous Vehicle Control

Comparison-Based Convolutional Neural Networks for Cervical Cell/Clumps Detection in the Limited Data Scenario

Seek and You Will Find: A New Optimized Framework for Efficient Detection of Pedestrian

Assessing Data Quality of Annotations with Krippendorff Alpha For Applications in Computer Vision

MFPN: A Novel Mixture Feature Pyramid Network of Multiple Architectures for Object Detection

Image Analytics for Legal Document Review: A Transfer Learning Approach

PerspectiveNet: 3D Object Detection from a Single RGB Image via Perspective Points

A Novel Automation-Assisted Cervical Cancer Reading Method Based on Convolutional Neural Network

Dually Supervised Feature Pyramid for Object Detection and Segmentation

Solving Visual Object Ambiguities when Pointing: An Unsupervised Learning Approach

Real-time texturing for 6D object instance detection from RGB Images

Learning Depth-Guided Convolutions for Monocular 3D Object Detection

Toward Automatic Threat Recognition for Airport X-ray Baggage Screening with Deep Convolutional Object Detection

Joint Viewpoint and Keypoint Estimation with Real and Synthetic Data

The Benefits of Close-Domain Fine-Tuning for Table Detection in Document Images

One Framework to Register Them All: PointNet Encoding for Point Cloud Alignment

AugFPN: Improving Multi-scale Feature Learning for Object Detection

Boundary-Aware Salient Object Detection via Recurrent Two-Stream Guided Refinement Network

TANet: Robust 3D Object Detection from Point Clouds with Triple Attention

RDSNet: A New Deep Architecture for Reciprocal Object Detection and Instance Segmentation

Online Structured Sparsity-based Moving Object Detection from Satellite Videos

Residual Bi-Fusion Feature Pyramid Network for Accurate Single-shot Object Detection

MDFN: Multi-Scale Deep Feature Learning Network for Object Detection

Learning a Layout Transfer Network for Context Aware Object Detection

Training a Fast Object Detector for LiDAR Range Images Using Labeled Data from Sensors with Higher Resolution

Deep Learning Based Segmentation Free License Plate Recognition Using Roadway Surveillance Camera Images

Deep Learning based Switching Filter for Impulsive Noise Removal in Color Images

It GAN DO Better: GAN-based Detection of Objects on Images with Varying Quality

StarNet: Targeted Computation for Object Detection in Point Clouds

SADA: Semantic Adversarial Diagnostic Attacks for Autonomous Applications

Dynamic Spatial Verification for Large-Scale Object-Level Image Retrieval

Deep Regionlets: Blended Representation and Deep Learning for Generic Object Detection

SM-NAS: Structural-to-Modular Neural Architecture Search for Object Detection

PointRGCN: Graph Convolution Networks for 3D Vehicles Detection Refinement

Towards Precise End-to-end Weakly Supervised Object Detection Network

CSPNet: A New Backbone that can Enhance Learning Capability of CNN

FVNet: 3D Front-View Proposal Generation for Real-Time Object Detection from Point Clouds

Data-Free Quantization Through Weight Equalization and Bias Correction

Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detection

Computer Vision-based Accident Detection in Traffic Surveillance

Rethinking Normalization and Elimination Singularity in Neural Networks

RefinedMPL: Refined Monocular PseudoLiDAR for 3D Object Detection in Autonomous Driving

Neural Architecture Search using Deep Neural Networks and Monte Carlo Tree Search

Data Augmentation Revisited: Rethinking the Distribution Gap between Clean and Augmented Data

SCL: Towards Accurate Domain Adaptive Object Detection via Gradient Detach Based Stacked Complementary Losses

Evaluating the Transferability and Adversarial Discrimination of Convolutional Neural Networks for Threat Object Detection and Classification within X-Ray Security Imagery

Vision: A Deep Learning Approach to provide walking assistance to the visually impaired

Event-based Object Detection and Tracking for Space Situational Awareness

Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression

Tell Me What They're Holding: Weakly-supervised Object Detection with Transferable Knowledge from Human-object Interaction

Are object detection assessment criteria ready for maritime computer vision?

2nd Place Solution in Google AI Open Images Object Detection Track 2019

SimVODIS: Simultaneous Visual Odometry, Object Detection, and Instance Segmentation

EdgeNet: Balancing Accuracy and Performance for Edge-based Convolutional Neural Network Object Detectors

Efficient ConvNet-based Object Detection for Unmanned Aerial Vehicles by Selective Tile Processing

Progressive Feature Polishing Network for Salient Object Detection

RandAugment: Practical automated data augmentation with a reduced search space

FreeAnchor: Learning to Match Anchors for Visual Object Detection

HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks

FlatteNet: A Simple Versatile Framework for Dense Pixelwise Prediction

A Delay Metric for Video Object Detection: What Average Precision Fails to Tell

PCRNet: Point Cloud Registration Network using PointNet Encoding

On the Interaction Between Deep Detectors and Siamese Trackers in Video Surveillance

Fine-Grained Object Detection over Scientific Document Images with Region Embeddings

Distributed and Consistent Multi-Image Feature Matching via QuickMatch

Learning an Efficient Network for Large-Scale Hierarchical Object Detection with Data Imbalance: 3rd Place Solution to Open Images Challenge 2019

Soft Prototyping Camera Designs for Car Detection Based on a Convolutional Neural Network

End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Clouds

AFO-TAD: Anchor-free One-Stage Detector for Temporal Action Detection

An Adaptive Supervision Framework for Active Learning in Object Detection

Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles

An application of a deep learning algorithm for automatic detection of unexpected accidents under bad CCTV monitoring conditions in tunnels

xYOLO: A Model For Real-Time Object Detection In Humanoid Soccer On Low-End Hardware

Deep Neural Network Compression for Image Classification and Object Detection

360-Indoor: Towards Learning Real-World Objects in 360° Indoor Equirectangular Images

YOLO Nano: a Highly Compact You Only Look Once Convolutional Neural Network for Object Detection

ANDA: A Novel Data Augmentation Technique Applied to Salient Object Detection

Road scenes analysis in adverse weather conditions by polarization-encoded images and adapted deep learning

AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search

A Review of Object Detection Models based on Convolutional Neural Network

Enhancing Object Detection in Adverse Conditions using Thermal Imaging

REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs

MRCNet: Crowd Counting and Density Map Estimation in Aerial and Ground Imagery

Mixed Supervised Object Detection with Robust Objectness Transfer

The Good, the Bad and the Ugly: Evaluating Convolutional Neural Networks for Prohibited Item Detection Using Real and Synthetically Composited X-ray Imagery

Guided Attention Network for Object Detection and Counting on Drones

Deep Mangoes: from fruit detection to cultivar identification in colour images of mango trees

Enhancing Traffic Scene Predictions with Generative Adversarial Networks

RILOD: Near Real-Time Incremental Learning for Object Detection at the Edge

Object Detection in Optical Remote Sensing Images: A Survey and A New Benchmark

Deep cross-domain building extraction for selective depth estimation from oblique aerial imagery

Road Damage Detection Acquisition System based on Deep Neural Networks for Physical Asset Management

On the Importance of Visual Context for Data Augmentation in Scene Understanding

Wasserstein Distance Based Domain Adaptation for Object Detection

Exploring Reciprocal Attention for Salient Object Detection by Cooperative Learning

Masked-RPCA: Sparse and Low-rank Decomposition Under Overlaying Model and Application to Moving Object Detection

Masking Salient Object Detection, a Mask Region-based Convolutional Neural Network Analysis for Segmentation of Salient Objects

A*3D Dataset: Towards Autonomous Driving in Challenging Environments

BayesOD: A Bayesian Approach for Uncertainty Estimation in Deep Object Detectors

Global Aggregation then Local Distribution in Fully Convolutional Networks

Points2Pix: 3D Point-Cloud to Image Translation using conditional Generative Adversarial Networks

A Single Multi-Task Deep Neural Network with Post-Processing for Object Detection with Reasoning and Robotic Grasp Detection

Street Crossing Aid Using Light-weight CNNs for the Visually Impaired

Three-dimensional Backbone Network for 3D Object Detection in Traffic Scenes

F-Cooper: Feature based Cooperative Perception for Autonomous Vehicle Edge Computing System Using 3D Point Clouds

Relative Saliency and Ranking: Models, Metrics, Data, and Benchmarks

Human-Machine Collaborative Design for Accelerated Design of Compact Deep Neural Networks for Autonomous Driving

Distortion-adaptive Salient Object Detection in 360$^\circ$ Omnidirectional Images

Selectivity or Invariance: Boundary-aware Salient Object Detection

Structured Modeling of Joint Deep Feature and Prediction Refinement for Salient Object Detection

MLOD: A multi-view 3D object detection based on robust feature fusion method

Understanding the Effects of Pre-Training for Object Detectors via Eigenspectrum

CBNet: A Novel Composite Backbone Network Architecture for Object Detection

Coarse-to-Fine Salient Object Detection with Low-Rank Matrix Recovery

Efficient Neural Architecture Transformation Searchin Channel-Level for Object Detection

Let's agree to disagree: learning highly debatable multirater labelling

OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge

Aerial multi-object tracking by detection using deep association networks

Object Viewpoint Classification Based 3D Bounding Box Estimation for Autonomous Vehicles

HishabNet: Detection, Localization and Calculation of Handwritten Bengali Mathematical Expressions

Self-Training and Adversarial Background Regularization for Unsupervised Domain Adaptive One-Stage Object Detection

Learning Instance-Aware Object Detection Using Determinantal Point Processes

3D Bounding Box Estimation for Autonomous Vehicles by Cascaded Geometric Constraints and Depurated 2D Detections Using 3D Results

FisheyeMODNet: Moving Object detection on Surround-view Cameras for Autonomous Driving

DeepBbox: Accelerating Precise Ground Truth Generation for Autonomous Driving Datasets

Great Ape Detection in Challenging Jungle Camera Trap Footage via Attention-Based Spatial and Temporal Feature Blending

Metric-based Regularization and Temporal Ensemble for Multi-task Learning using Heterogeneous Unsupervised Tasks

iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images

Error Bounded Foreground and Background Modeling for Moving Object Detection in Satellite Videos

Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection

An Objectness Score for Accurate and Fast Detection during Navigation

Patchwork: A Patch-wise Attention Network for Efficient Object Detection and Segmentation in Video Streams

Explaining the Ambiguity of Object Detection and 6D Pose From Visual Data

Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks

C-RPNs: Promoting Object Detection in real world via a Cascade Structure of Region Proposal Networks

SE2Net: Siamese Edge-Enhancement Network for Salient Object Detection

Cap2Det: Learning to Amplify Weak Caption Supervision for Object Detection

Foveated image processing for faster object detection and recognition in embedded systems using deep convolutional neural networks

Detecting 11K Classes: Large Scale Object Detection without Fine-Grained Bounding Boxes

Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object Detection

EvalNorm: Estimating Batch Normalization Statistics for Evaluation

Optimizing the F-measure for Threshold-free Salient Object Detection

Synthesizing Diverse Lung Nodules Wherever Massively: 3D Multi-Conditional GAN-based CT Image Augmentation for Object Detection

Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving

M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

Edge-guided Non-local Fully Convolutional Network for Salient Object Detection

Pixel and Feature Level Based Domain Adaption for Object Detection in Autonomous Driving

Conditional Generative Adversarial Networks for Data Augmentation and Adaptation in Remotely Sensed Imagery

Object-Aware Instance Labeling for Weakly Supervised Object Detection

SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects

PosNeg-Balanced Anchors with Aligned Features for Single-Shot Object Detection

Anytime Lane-Level Intersection Estimation Based on Trajectories of Other Traffic Participants

Image Matters: Scalable Detection of Offensive and Non-Compliant Content / Logo in Product Images

Extract and Merge: Merging extracted humans from different images utilizing Mask R-CNN

Synthetic Image Augmentation for Improved Classification using Generative Adversarial Networks

BshapeNet: Object Detection and Instance Segmentation with Bounding Shape Masks

Reprojection R-CNN: A Fast and Accurate Object Detector for 360° Images

Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes

SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV Applications

Simultaneous multi-view instance detection with learned geometric soft-constraints

An Efficient Method of Detection and Recognition in Remote Sensing Image Based on multi-angle Region of Interests

RGB-D image-based Object Detection: from Traditional Methods to Deep Learning Techniques

DetectFusion: Detecting and Segmenting Both Known and Unknown Dynamic Objects in Real-time SLAM

Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night

Self-supervised Training of Proposal-based Segmentation via Background Prediction

SoilingNet: Soiling Detection on Automotive Surround-View Cameras

RGB and LiDAR fusion based 3D Semantic Segmentation for Autonomous Driving

Implicit 3D Orientation Learning for 6D Object Detection from RGB Images

OGNet: Salient Object Detection with Output-guided Attention Module

How much real data do we actually need: Analyzing object detection performance using synthetic and real data

Mango Tree Net -- A fully convolutional network for semantic segmentation and individual crown detection of mango trees

Voxel-FPN: multi-scale voxel feature aggregation in 3D object detection from point clouds

Cascade RetinaNet: Maintaining Consistency for Single-Stage Object Detection

Deep inspection: an electrical distribution pole parts study via deep neural networks

Improving 3D Object Detection for Pedestrians with Virtual Multi-View Synthesis Orientation Estimation

Object Detection in Video with Spatial-temporal Context Aggregation

Data Augmentation for Object Detection via Progressive and Selective Instance-Switching

Improving Deep Lesion Detection Using 3D Contextual and Spatial Attention

SkyNet: A Champion Model for DAC-SDC on Low Power Object Detection

Attentive CT Lesion Detection Using Deep Pyramid Inference with Multi-Scale Booster

A Comparison of Super-Resolution and Nearest Neighbors Interpolation Applied to Object Detection on Satellite Data

A unified neural network for object detection, multiple object tracking and vehicle re-identification

Real-time Dynamic Object Detection for Autonomous Driving using Prior 3D-Maps

Multi-Cue Vehicle Detection for Semantic Video Compression In Georegistered Aerial Videos

Learning Objectness from Sonar Images for Class-Independent Object Detection

Cascade R-CNN: High Quality Object Detection and Instance Segmentation

Adaptive Period Embedding for Representing Oriented Objects in Aerial Images

Baidu-UTS Submission to the EPIC-Kitchens Action Recognition Challenge 2019

MMLSpark: Unifying Machine Learning Ecosystems at Massive Scales

Pattern Spotting in Historical Documents Using Convolutional Models

Monocular 3D Object Detection and Box Fitting Trained End-to-End Using Intersection-over-Union Loss

Nested Network with Two-Stream Pyramid for Salient Object Detection in Optical Remote Sensing Images

The Attack Generator: A Systematic Approach Towards Constructing Adversarial Attacks

RIU-Net: Embarrassingly simple semantic segmentation of 3D LiDAR point cloud

Asynchronous Convolutional Networks for Object Detection in Neuromorphic Cameras

VolMap: A Real-time Model for Semantic Segmentation of a LiDAR surrounding view

Lidar based Detection and Classification of Pedestrians and Vehicles Using Machine Learning Methods

Clouds of Oriented Gradients for 3D Detection of Objects, Surfaces, and Indoor Scene Layouts

SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

Deep Fitting Degree Scoring Network for Monocular 3D Object Detection

Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation

Weakly-Supervised Spatio-Temporally Grounding Natural Sentence in Video

StyleNAS: An Empirical Study of Neural Architecture Search to Uncover Surprisingly Fast End-to-End Universal Style Transfer Networks

Farm land weed detection with region-based deep convolutional neural networks

A Feature Transfer Enabled Multi-Task Deep Learning Model on Medical Imaging

Efficient architecture for deep neural networks with heterogeneous sensitivity

Triangulation Learning Network: from Monocular to Stereo 3D Object Detection

Driver Behavior Analysis Using Lane Departure Detection Under Challenging Conditions

Multi-Precision Quantized Neural Networks via Encoding Decomposition of -1 and +1

SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation

All-In-One Underwater Image Enhancement using Domain-Adversarial Learning

Prostate Cancer Detection using Deep Convolutional Neural Networks

Fooling Detection Alone is Not Enough: First Adversarial Attack against Multiple Object Tracking

Distant Pedestrian Detection in the Wild using Single Shot Detector with Deep Convolutional Generative Adversarial Networks

LeagueAI: Improving object detector performance and flexibility through automatically generated training data and domain randomization

Fourier-based Rotation-invariant Feature Boosting: An Efficient Framework for Geospatial Object Detection

Training a Binary Weight Object Detector by Knowledge Transfer for Autonomous Driving

Shift R-CNN: Deep Monocular 3D Object Detection with Closed-Form Geometric Constraints

Foothill: A Quasiconvex Regularization for Edge Computing of Deep Neural Networks

3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning Models

Multiple receptive fields and small-object-focusing weakly-supervised segmentation network for fast object detection

A Bi-Directional Co-Design Approach to Enable Deep Learning on IoT Devices

Efficient Coarse-to-Fine Non-Local Module for the Detection of Small Objects

Vision-based Navigation of Autonomous Vehicle in Roadway Environments with Unexpected Hazards

Enabling Computer Vision Driven Assistive Devices for the Visually Impaired via Micro-architecture Design Exploration

DOTA: A Large-scale Dataset for Object Detection in Aerial Images

Utilizing Deep Learning Towards Multi-modal Bio-sensing and Vision-based Affective Computing

PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud

Robust Real-time Pedestrian Detection in Aerial Imagery on Jetson TX2

Dataset Culling: Towards Efficient Training Of Distillation-Based Domain Specific Models

Predictive Ensemble Learning with Application to Scene Text Detection

Tracking in Urban Traffic Scenes from Background Subtraction and Object Detection

RRPN: Radar Region Proposal Network for Object Detection in Autonomous Vehicles

Monocular 3D Object Detection via Geometric Reasoning on Keypoints

Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds

Transferable Adversarial Attacks for Image and Video Object Detection

ROSA: Robust Salient Object Detection against Adversarial Attacks

Enhancing Cross-task Transferability of Adversarial Examples with Dispersion Reduction

Generalization ability of region proposal networks for multispectral person detection

On Applying Machine Learning/Object Detection Models for Analysing Digitally Captured Physical Prototypes from Engineering Design Projects

Precise Synthetic Image and LiDAR (PreSIL) Dataset for Autonomous Vehicle Perception

PointPillars: Fast Encoders for Object Detection from Point Clouds

VSSA-NET: Vertical Spatial Sequence Attention Network for Traffic Sign Detection

Dynamic Mini-batch SGD for Elastic Distributed Training: Learning in the Limbo of Resources

ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector

Wearable Travel Aid for Environment Perception and Navigation of Visually Impaired People

MSDC-Net: Multi-Scale Dense and Contextual Networks for Automated Disparity Map for Stereo Matching

HOG feature extraction from encrypted images for privacy-preserving machine learning

Mixture of Pre-processing Experts Model for Noise Robust Deep Learning on Resource Constrained Platforms

Synthetic Data Generation and Adaption for Object Detection in Smart Vending Machines

A New Loss Function for CNN Classifier Based on Pre-defined Evenly-Distributed Class Centroids

Reduced Focal Loss: 1st Place Solution to xView object detection in Satellite Imagery

Sensor Fusion for Joint 3D Object Detection and Semantic Segmentation

Bottom-up Object Detection by Grouping Extreme and Center Points

HAR-Net: Joint Learning of Hybrid Attention for Single-stage Object Detection

PCA-RECT: An Energy-efficient Object Detection Approach for Event Cameras

Transferable Semi-supervised 3D Object Detection from RGB-D Data

Detecting inter-sectional accuracy differences in driver drowsiness detection algorithms

Detecting retail products in situ using CNN without human effort labeling

An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection

A Simple Pooling-Based Design for Real-Time Salient Object Detection

Sampling Techniques for Large-Scale Object Detection from Sparsely Annotated Objects

Feature Selective Small Object Detection via Knowledge-based Recurrent Attentive Neural Network

Deep Learning Based Automatic Video Annotation Tool for Self-Driving Car

A deep learning based solution for construction equipment detection: from development to deployment

Salient Object Detection: A Distinctive Feature Integration Model

Cascaded Partial Decoder for Fast and Accurate Salient Object Detection

Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data

Deep Optics for Monocular Depth Estimation and 3D Object Detection

Bounding Box Regression with Uncertainty for Accurate Object Detection

Complexer-YOLO: Real-Time 3D Object Detection and Tracking on Semantic Point Clouds

DuBox: No-Prior Box Objection Detection via Residual Dual Scale Detectors

NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection

AttoNets: Compact and Efficient Deep Neural Networks for the Edge via Human-Machine Collaborative Design

Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression

C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object Detection

Evaluation of a Dual Convolutional Neural Network Architecture for Object-wise Anomaly Detection in Cluttered X-ray Security Imagery

ModaNet: A Large-Scale Street Fashion Dataset with Polygon Annotations

Hierarchy Denoising Recursive Autoencoders for 3D Scene Layout Prediction

ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape

Local Aggregation for Unsupervised Learning of Visual Embeddings

The Effects of Super-Resolution on Object Detection Performance in Satellite Imagery

FPGA/DNN Co-Design: An Efficient Design Methodology for IoT Intelligence on the Edge

Moving Object Detection under Discontinuous Change in Illumination Using Tensor Low-Rank and Invariant Sparse Decomposition

AOGNets: Compositional Grammatical Architectures for Deep Learning

Attentive Relational Networks for Mapping Images to Scene Graphs

CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification

Strong-Weak Distribution Alignment for Adaptive Object Detection

Exploring the Bounds of the Utility of Context for Object Detection

A Training-free, One-shot Detection Framework For Geospatial Objects In Remote Sensing Images

Super accurate low latency object detection on a surveillance UAV

Monocular 3D Object Detection Leveraging Accurate Proposals and Shape Reconstruction

DSAL-GAN: Denoising based Saliency Prediction with Generative Adversarial Networks

Scene Graph Generation with External Knowledge and Image Reconstruction

Weakly Supervised Object Detection with Segmentation Collaboration

Salient Object Detection via High-to-Low Hierarchical Context Aggregation

ImageGCN: Multi-Relational Image Graph Convolutional Networks for Disease Identification with Chest X-rays

R$^2$-CNN: Fast Tiny Object Detection in Large-Scale Remote Sensing Images

ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network

GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving

Optimising the Input Image to Improve Visual Relationship Detection

Task-generalizable Adversarial Attack based on Perceptual Metric

OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillation

Deep Reasoning with Multi-Scale Context for Salient Object Detection

Software-Defined FPGA Accelerator Design for Mobile Deep Learning Applications

SQuantizer: Simultaneous Learning for Both Sparse and Low-precision Neural Networks

Automated pulmonary nodule detection using 3D deep convolutional neural networks

Towards Compact ConvNets via Structure-Sparsity Regularized Filter Pruning

Towards Robust Curve Text Detection with Conditional Spatial Expansion

LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving

DC-SPP-YOLO: Dense Connection and Spatial Pyramid Pooling Based YOLO for Object Detection

IvaNet: Learning to jointly detect and segment objets with the help of Local Top-Down Modules

Real-time Pedestrian Detection Approach with an Efficient Data Communication Bandwidth Strategy

SCNN: A General Distribution based Statistical Convolutional Neural Network with Application to Video Object Detection

BLVD: Building A Large-scale 5D Semantics Benchmark for Autonomous Driving

Did You Miss the Sign? A False Negative Alarm System for Traffic Sign Detectors

Learning Orientation-Estimation Convolutional Neural Network for Building Detection in Optical Remote Sensing Image

SimpleDet: A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition

A Multiclass Multiple Instance Learning Method with Exact Likelihood

Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation

Weakly Supervised Complementary Parts Models for Fine-Grained Image Classification from the Bottom Up

Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection

Real-world Underwater Enhancement: Challenges, Benchmarks, and Solutions

Improve Object Detection by Data Enhancement based on Generative Adversarial Nets

The H3D Dataset for Full-Surround 3D Multi-Object Detection and Tracking in Crowded Urban Scenes

CBinfer: Exploiting Frame-to-Frame Locality for Faster Convolutional Network Inference on Video Streams

CAD-Net: A Context-Aware Detection Network for Objects in Remote Sensing Imagery

Feature Selective Anchor-Free Module for Single-Shot Object Detection

Progress Regression RNN for Online Spatial-Temporal Action Localization in Unconstrained Videos

Towards Automatic Construction of Diverse, High-quality Image Dataset

An Annotation Saved is an Annotation Earned: Using Fully Synthetic Training for Object Instance Detection

Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose Estimation

CaTDet: Cascaded Tracked Detector for Efficient Object Detection from Video

Dynamic Temporal Pyramid Network: A Closer Look at Multi-Scale Modeling for Activity Detection

A system for generating complex physically accurate sensor images for automotive applications

DOD-CNN: Doubly-injecting Object Information for Event Recognition

Vulnerable road user detection: state-of-the-art and open challenges

AdaScale: Towards Real-time Video Object Detection Using Adaptive Scaling

TrackNet: Simultaneous Object Detection and Tracking and Its Application in Traffic Video Analysis

Real-time Prediction of Automotive Collision Risk from Monocular Video

Object Detection and 3D Estimation via an FMCW Radar Using a Fully Convolutional Network

Towards Pedestrian Detection Using RetinaNet in ECCV 2018 Wider Pedestrian Detection Challenge

Confidence Trigger Detection: An Approach to Build Real-time Tracking-by-detection System

Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art

Deep Learning Solutions for TanDEM-X-based Forest Classification

Pixel-wise Ear Detection with Convolutional Encoder-Decoder Networks

Self-Supervised Visual Representations for Cross-Modal Retrieval

ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features

A deep learning pipeline for product recognition on store shelves

Salient Object Detection with Lossless Feature Reflection and Weighted Structural Loss

Design of Real-time Semantic Segmentation Decoder for Automated Driving

Embedded CNN based vehicle classification and counting in non-laned road traffic

Cooking State Recognition from Images Using Inception Architecture

ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes

Cost-effective Object Detection: Active Sample Mining with Switchable Selection Criteria

Indoor Scene Understanding in 2.5/3D for Autonomous Agents: A Survey

Weakly Supervised Object Localization on grocery shelves using simple FCN and Synthetic Dataset

Richer and Deeper Supervision Network for Salient Object Detection

3D Object Detection Using Scale Invariant and Feature Reweighting Networks

Sensor Transfer: Learning Optimal Sensor Effect Image Augmentation for Sim-to-Real Domain Adaptation

M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network

Intelligent Intersection: Two-Stream Convolutional Networks for Real-time Near Accident Detection in Traffic Video

Fast and Accurate, Convolutional Neural Network Based Approach for Object Detection from UAV

Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision

Large-Scale Object Detection of Images from Network Cameras in Variable Ambient Lighting Conditions

Pixel personality for dense object tracking in a 2D honeybee hive

An Adaptive Approach for Automated Grapevine Phenotyping using VGG-based Convolutional Neural Networks

Region Proposal Networks with Contextual Selective Attention for Real-Time Organ Detection

Detection of distal radius fractures trained by a small set of X-ray images and Faster R-CNN

PiCANet: Pixel-wise Contextual Attention Learning for Accurate Saliency Detection

Benchmark Dataset for Automatic Damaged Building Detection from Post-Hurricane Remotely Sensed Imagery

Fire SSD: Wide Fire Modules based Single Shot Detector on Edge Device

Tube-CNN: Modeling temporal evolution of appearance for object detection in video

Bag of Tricks for Image Classification with Convolutional Neural Networks

Object Detection and Classification in Occupancy Grid Maps using Deep Convolutional Networks

Learning RoI Transformer for Detecting Oriented Objects in Aerial Images

NOTE-RCNN: NOise Tolerant Ensemble RCNN for Semi-Supervised Object Detection

Snapshot Distillation: Teacher-Student Optimization in One Generation

Real Time Bangladeshi Sign Language Detection using Faster R-CNN

Integrated Object Detection and Tracking with Tracklet-Conditioned Detection

A Convolutional Neural Network based Live Object Recognition System as Blind Aid

A Survey on Joint Object Detection and Pose Estimation using Monocular Vision

Learning to discover and localize visual objects with open vocabulary

Dissimilarity Coefficient based Weakly Supervised Object Detection

A Framework of Transfer Learning in Object Detection for Embedded Systems

Detecting Heads using Feature Refine Net and Cascaded Multi-Scale Architecture

A Proposal-Based Solution to Spatio-Temporal Action Detection in Untrimmed Videos

Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection

Domain Adaptation from Synthesis to Reality in Single-model Detector for Video Smoke Detection

Orthographic Feature Transform for Monocular 3D Object Detection

Data-Efficient Graph Embedding Learning for PCB Component Detection

Explain to Fix: A Framework to Interpret and Correct DNN Object Detector Predictions

Past, Present, and Future Approaches Using Computer Vision for Animal Re-Identification from Camera Trap Data

FotonNet: A HW-Efficient Object Detection System Using 3D-Depth Segmentation and 2D-DNN Classifier

Pixel-Anchor: A Fast Oriented Scene Text Detector with Combined Networks

RepMet: Representative-based metric learning for classification and one-shot object detection

Training Domain Specific Models for Energy-Efficient Object Detection

DeRPN: Taking a further step toward more general object detection

CADP: A Novel Dataset for CCTV Traffic Camera based Accident Analysis

Detecting The Objects on The Road Using Modular Lightweight Network

LoANs: Weakly Supervised Object Detection with Localizer Assessor Networks

ShuffleDet: Real-Time Vehicle Detection Network in On-board Embedded UAV Imagery

Development of Real-time ADAS Object Detector for Deployment on CPU

Geometry-Aware Recurrent Neural Networks for Active Visual Recognition

YOLO-LITE: A Real-Time Object Detection Algorithm Optimized for Non-GPU Computers

Detect or Track: Towards Cost-Effective Video Object Detection/Tracking

Road Damage Detection And Classification In Smartphone Captured Images Using Mask R-CNN

RoarNet: A Robust 3D Object Detection based on RegiOn Approximation Refinement

Robust Deep Multi-modal Learning Based on Gated Information Fusion Network

Towards Multi-class Object Detection in Unconstrained Remote Sensing Imagery

Cross-Modal Attentional Context Learning for RGB-D Object Detection

Hybrid Knowledge Routed Modules for Large-scale Object Detection

3D Regression Neural Network for the Quantification of Enlarged Perivascular Spaces in Brain MRI

Fast and accurate object detection in high resolution 4K and 8K video using GPUs

A Robust Local Binary Similarity Pattern for Foreground Object Detection

Salient Object Detection in Video using Deep Non-Local Neural Networks

Solution for Large-Scale Hierarchical Object Detection Datasets with Incomplete Annotation and Data Imbalance

Learnable Histogram: Statistical Context Features for Deep Neural Networks

PCL: Proposal Cluster Learning for Weakly Supervised Object Detection

Incremental Deep Learning for Robust Object Detection in Unknown Cluttered Environments

PDNet: Prior-model Guided Depth-enhanced Network for Salient Object Detection

DeepScores and Deep Watershed Detection: current state and open issues

Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications

CFENet: An Accurate and Efficient Single-Shot Object Detector for Autonomous Driving

UOLO - automatic object detection and segmentation in biomedical images

Training Convolutional Neural Networks and Compressed Sensing End-to-End for Microscopy Cell Detection

Unsupervised Adversarial Visual Level Domain Adaptation for Learning Video Object Detectors from Images

A Robot Localization Framework Using CNNs for Object Detection and Pose Estimation

Deep Perm-Set Net: Learn to predict sets with unknown permutation and cardinality using deep neural networks

Landmine Detection Using Autoencoders on Multi-polarization GPR Volumetric Data

Modeling Camera Effects to Improve Visual Learning from Synthetic Data

Extended Bit-Plane Compression for Convolutional Neural Network Accelerators

RGB-D Object Detection and Semantic Segmentation for Autonomous Manipulation in Clutter

Smart Surveillance as an Edge Network Service: from Harr-Cascade, SVM to a Lightweight CNN

Boundary-guided Feature Aggregation Network for Salient Object Detection

Cursive Scene Text Analysis by Deep Convolutional Linear Pyramids

Dropout Distillation for Efficiently Estimating Model Confidence

Real-time 3D Pose Estimation with a Monocular Camera Using Deep Learning and Object Priors On an Autonomous Racecar

PointSeg: Real-Time Semantic Segmentation Based on 3D LiDAR Point Cloud

Triply Supervised Decoder Networks for Joint Detection and Segmentation

Satellite Imagery Multiscale Rapid Detection with Windowed Networks

Object segmentation in depth maps with one user click and a synthetically trained fully convolutional network

Artistic Instance-Aware Image Filtering by Convolutional Neural Networks

Global Weighted Average Pooling Bridges Pixel-level Localization and Image-level Classification

A Fast and Accurate System for Face Detection, Identification, and Verification

Counting the uncountable: deep semantic density estimation from Space

Revisit Multinomial Logistic Regression in Deep Learning: Data Dependent Model Initialization for Image Recognition

An FPGA-Accelerated Design for Deep Learning Pedestrian Detection in Self-Driving Vehicles

Fingertip Detection and Tracking for Recognition of Air-Writing in Videos

MDCN: Multi-Scale, Deep Inception Convolutional Neural Networks for Efficient Object Detection

Conditional Transfer with Dense Residual Attention: Synthesizing traffic signs from street-view imagery

Discriminative Learning of Open-Vocabulary Object Retrieval and Localization by Negative Phrase Augmentation

PFDet: 2nd Place Solution to Open Images Challenge 2018 Object Detection Track

DAC-SDC Low Power Object Detection Challenge for UAV Applications

Optimizing the Trade-off between Single-Stage and Two-Stage Object Detectors using Image Difficulty Prediction

Real-time Detection, Tracking, and Classification of Moving and Stationary Objects using Multiple Fisheye Images

Exploring the Applications of Faster R-CNN and Single-Shot Multi-box Detection in a Smart Nursery Domain

Label and Sample: Efficient Training of Vehicle Object Detector from Sparsely Labeled Data

Multidomain Document Layout Understanding using Few Shot Object Detection

A Survey of Modern Object Detection Literature using Deep Learning

Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery

Dynamic Routing on Deep Neural Network for Thoracic Disease Classification and Sensitive Area Localization

Probabilistic Model of Object Detection Based on Convolutional Neural Network

Network Decoupling: From Regular to Depthwise Separable Convolutions

DNN Feature Map Compression using Learned Representation over GF(2)

SAN: Learning Relationship between Convolutional Features for Multi-Scale Object Detection

Backtracking Spatial Pyramid Pooling (SPP)-based Image Classifier for Weakly Supervised Top-down Salient Object Detection

Fast Convergence for Object Detection by Learning how to Combine Error Functions

Unsupervised Hard Example Mining from Videos for Improved Object Detection

Object Detection in Satellite Imagery using 2-Step Convolutional Neural Networks

YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud

Disparity Sliding Window: Object Proposals From Disparity Images

Traits & Transferability of Adversarial Examples against Instance Segmentation & Object Detection

Online Illumination Invariant Moving Object Detection by Generative Neural Network

Acquisition of Localization Confidence for Accurate Object Detection

Improved Techniques for Learning to Dehaze and Beyond: A Collective Study

Tiny-DSOD: Lightweight Object Detection for Resource-Restricted Usages

Learning to Segment Object Candidates via Recursive Neural Networks

Receptive Field Block Net for Accurate and Fast Object Detection

Toward Scale-Invariance and Position-Sensitive Region Proposal Networks

Domain Stylization: A Strong, Simple Baseline for Synthetic to Real Image Domain Adaptation

Visual Mesh: Real-time Object Detection Using Constant Sample Density

Salient Objects in Clutter: Bringing Salient Object Detection to the Foreground

IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks

Modeling Visual Context is Key to Augmenting Object Detection Datasets

Deep Adaptive Proposal Network for Object Detection in Optical Remote Sensing Images

In pixels we trust: From Pixel Labeling to Object Localization and Scene Categorization

Leveraging Pre-Trained 3D Object Detection Models For Fast Ground Truth Generation

Applying Domain Randomization to Synthetic Data for Object Category Detection

Uncertainty and Interpretability in Convolutional Neural Networks for Semantic Segmentation of Colorectal Polyps

Assessing fish abundance from underwater video using deep neural networks

Spatio-Temporal Structured Sparse Regression with Hierarchical Gaussian Process Priors

TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection

CADDY Underwater Stereo-Vision Dataset for Human-Robot Interaction (HRI) in the Context of Diver Activities

Joint 3D Proposal Generation and Object Detection from View Aggregation

Falling Things: A Synthetic Dataset for 3D Object Detection and Pose Estimation

Combining Background Subtraction Algorithms with Convolutional Neural Network

Optimal Sensor Data Fusion Architecture for Object Detection in Adverse Weather Conditions

Localization Recall Precision (LRP): A New Performance Metric for Object Detection

TextTopicNet - Self-Supervised Learning of Visual Features Through Embedding Images on Semantic Text Spaces

MITOS-RCNN: A Novel Approach to Mitotic Figure Detection in Breast Cancer Histopathology Images using Region Based Convolutional Neural Networks

An Integration of Bottom-up and Top-Down Salient Cues on RGB-D Data: Saliency from Objectness vs. Non-Objectness

Faster Bounding Box Annotation for Object Detection in Indoor Scenes

Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector

Hyperspectral Image Dataset for Benchmarking on Salient Object Detection

Structure Inference Net: Object Detection Using Scene-Level Context and Instance-Level Relationships

Detecting Mammals in UAV Images: Best Practices to address a substantially Imbalanced Dataset with Deep Learning

How To Extract Fashion Trends From Social Media? A Robust Object Detector With Support For Unsupervised Learning

Deployment of Customized Deep Learning based Video Analytics On Surveillance Cameras

Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation

Symmetry Aware Evaluation of 3D Object Detection and Pose Estimation in Scenes of Many Parts in Bulk

Video Salient Object Detection Using Spatiotemporal Deep Features

MV-YOLO: Motion Vector-aided Tracking by Semantic Object Detection

Real-Time Deep Learning Method for Abandoned Luggage Detection in Video

Automatic Ship Detection of Remote Sensing Images from Google Earth in Complex Scenes Based on Multi-Scale Rotation Dense Feature Pyramid Networks

Object detection and tracking benchmark in industry based on improved correlation filter

Object Detection using Domain Randomization and Generative Adversarial Refinement of Synthetic Images

Zoom Out-and-In Network with Map Attention Decision for Region Proposal and Object Detection

Domain Adaptive Generation of Aircraft on Satellite Imagery via Simulated and Unsupervised Learning

Model-based active learning to detect isometric deformable objects in the wild with deep architectures

DEEPEYE: A Compact and Accurate Video Comprehension at Terminal Devices Compressed with Quantization and Tensorization

The EuroCity Persons Dataset: A Novel Benchmark for Object Detection

How convolutional neural network see the world - A survey of convolutional neural network visualization methods

Adversarial Attacks on Face Detectors using Neural Net based Constrained Optimization

Getting to Know Low-light Images with The Exclusively Dark Dataset

Towards Human-Machine Cooperation: Self-supervised Sample Mining for Object Detection

You Only Look Twice: Rapid Multi-Scale Object Detection In Satellite Imagery

A scene perception system for visually impaired based on object detection and classification using multi-modal DCNN

Memory-Efficient Deep Salient Object Segmentation Networks on Gridized Superpixels

Unsupervised Deep Context Prediction for Background Foreground Separation

LMNet: Real-time Multiclass Object Detection on CPU using 3D LiDAR

Scene Understanding Networks for Autonomous Driving based on Around View Monitoring System

SINet: A Scale-insensitive Convolutional Neural Network for Fast Vehicle Detection

Exploiting the Value of the Center-dark Channel Prior for Salient Object Detection

Visual Attribute-augmented Three-dimensional Convolutional Neural Network for Enhanced Human Action Recognition

IncepText: A New Inception-Text Module with Deformable PSROI Pooling for Multi-Oriented Scene Text Detection

Fused Text Segmentation Networks for Multi-oriented Scene Text Detection

SqueezeJet: High-level Synthesis Accelerator Design for Deep Convolutional Neural Networks

Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination

Assessing a mobile-based deep learning model for plant disease surveillance

Algorithms for Semantic Segmentation of Multispectral Remote Sensing Imagery using Deep Learning

Precise Box Score: Extract More Information from Datasets to Improve the Performance of Face Detection

Real-Time Human Detection as an Edge Service Enabled by a Lightweight CNN

Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization

Object Counts! Bringing Explicit Detections Back into Image Captioning

Rethinking the Faster R-CNN Architecture for Temporal Action Localization

Dropout Sampling for Robust Object Detection in Open-Set Conditions

HyperFusion-Net: Densely Reflective Fusion for Salient Object Detection

Automatic Salient Object Detection for Panoramic Images Using Region Growing and Fixation Prediction Model

DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks

Exploring Multi-Branch and High-Level Semantic Networks for Improving Pedestrian Detection

Multi-scale Location-aware Kernel Representation for Object Detection

Contrast-Oriented Deep Neural Networks for Salient Object Detection

Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation

Task-Driven Super Resolution: Object Detection in Low-resolution Images

Deep neural networks can be improved using human-derived contextual expectations

Memory Warps for Learning Long-Term Online Video Representations

Deep Learning Object Detection Methods for Ecological Camera Trap Data

Mobile Video Object Detection with Temporally-Aware Feature Maps

TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild

BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depth

A multilayer backpropagation saliency detection algorithm and its applications

The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking

Revisiting Salient Object Detection: Simultaneous Detection, Ranking, and Subitizing of Multiple Salient Objects

Hardware based Spatio-Temporal Neural Processing Backend for Imaging Sensors: Towards a Smart Camera

Buried object detection from B-scan ground penetrating radar data using Faster-RCNN

Single-Shot Bidirectional Pyramid Networks for High-Quality Object Detection

Fusion of an Ensemble of Augmented Image Detectors for Robust Object Detection

Deeply supervised salient object detection with short connections

Zero-Shot Object Detection: Learning to Simultaneously Recognize and Localize Novel Concepts

Pseudo-labels for Supervised Learning on Dynamic Vision Sensor Data, Applied to Object Detection under Ego-motion

Visual and Semantic Knowledge Transfer for Large Scale Semi-supervised Object Detection

Learning Scene-specific Object Detectors Based on a Generative-Discriminative Model with Minimal Supervision

Learning Effective Binary Visual Representations with Deep Networks

AffordanceNet: An End-to-End Deep Learning Approach for Object Affordance Detection

Multi-Oriented Scene Text Detection via Corner Localization and Region Segmentation

Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning

3D-SSD: Learning Hierarchical Features from RGB-D Images for Amodal 3D Object Detection

Co-occurrence matrix analysis-based semi-supervised training for object detection

Agile Amulet: Real-Time Salient Object Detection with Contextual Attention

Can you tell where in India I am from? Comparing humans and computers on fine-grained race face classification

Tiny SSD: A Tiny Single-shot Detection Deep Convolutional Neural Network for Real-time Embedded Object Detection

Fusing Bird View LIDAR Point Cloud and Front View Camera Image for Deep Object Detection

Brain Tumor Segmentation Based on Refined Fully Convolutional Neural Networks with A Hierarchical Dice Loss

Generating Triples with Adversarial Networks for Scene Graph Construction

Tracking Multiple Moving Objects Using Unscented Kalman Filtering Techniques

Towards Multi-Object Detection and Tracking in Urban Scenario under Uncertainties

Road Damage Detection Using Deep Neural Networks with Images Captured Through a Smartphone

Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks

Sliding Line Point Regression for Shape Robust Scene Text Detection

Object Detection on Dynamic Occupancy Grid Maps Using Deep Learning and Automatic Label Generation

Weakly Supervised Object Detection with Pointwise Mutual Information

The challenge of simultaneous object detection and pose estimation: a comparative study

Extend the shallow part of Single Shot MultiBox Detector via Convolutional Neural Network

StressedNets: Efficient Feature Representations via Stress-induced Evolutionary Synthesis of Deep Neural Networks

An Accurate and Real-time Self-blast Glass Insulator Location Method Based On Faster R-CNN and U-net with Aerial Images

An octree cells occupancy geometric dimensionality descriptor for massive on-server point cloud visualisation and classification

MSDNN: Multi-Scale Deep Neural Network for Salient Object Detection

From Superpixel to Human Shape Modelling for Carried Object Detection

ReMotENet: Efficient Relevant Motion Event Detection for Large-scale Home Surveillance Videos

Learning Fixation Point Strategy for Object Detection and Classification

Like What You Like: Knowledge Distill via Neuron Selectivity Transfer

Kill Two Birds With One Stone: Boosting Both Object Detection Accuracy and Speed With adaptive Patch-of-Interest Composition

Detection and Attention: Diagnosing Pulmonary Lung Cancer from CT by Imitating Physicians

MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features

Symbol detection in online handwritten graphics using Faster R-CNN

ADA: A Game-Theoretic Perspective on Data Augmentation for Object Detection

DFUNet: Convolutional Neural Networks for Diabetic Foot Ulcer Classification

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

ClusterNet: Detecting Small Objects in Large Scenes by Exploiting Spatio-Temporal Information

SeeThrough: Finding Chairs in Heavily Occluded Indoor Scene Images

Automatic Recognition of Coal and Gangue based on Convolution Neural Network

Multi-Channel CNN-based Object Detection for Enhanced Situation Awareness

A novel graph structure for salient object detection based on divergence background and compact foreground

Multiple Instance Curriculum Learning for Weakly Supervised Object Detection

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

Apprentice: Using Knowledge Distillation Techniques To Improve Low-Precision Network Accuracy

Squeeze-SegNet: A new fast Deep Convolutional Neural Network for Semantic Segmentation

MODNet: Moving Object Detection Network with Motion and Appearance for Autonomous Driving

Detecting and classifying lesions in mammograms with Deep Learning

Object Detection Through Exploration With A Foveated Visual Field

Spatial Pyramid Context-Aware Moving Object Detection and Tracking for Full Motion Video and Wide Aerial Motion Imagery

A Taught-Obesrve-Ask (TOA) Method for Object Detection with Critical Supervision

Recognizing Textures with Mobile Cameras for Pedestrian Safety Applications

Robust Saliency Detection via Fusing Foreground and Background Priors

A multitask deep learning model for real-time deployment in embedded systems

Image Patch Matching Using Convolutional Descriptors with Euclidean Distance

Cascade Region Proposal and Global Context for Deep Object Detection

Investigating the feature collection for semantic segmentation via single skip connection

Fishing for Clickbaits in Social Images and Texts with Linguistically-Infused Neural Network Models

Sushi Dish - Object detection and classification from real images

Towards lightweight convolutional neural networks for object detection

Edge Preserving and Multi-Scale Contextual Neural Network for Salient Object Detection

CLAD: A Complex and Long Activities Dataset with Rich Crowdsourced Annotations

Beyond Skip Connections: Top-Down Modulation for Object Detection

Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in Video

Scene Graph Generation from Objects, Phrases and Region Captions

Extremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM

Automatic Ground Truths: Projected Image Annotations for Omnidirectional Vision

Fully Convolutional Neural Networks for Dynamic Object Detection in Grid Maps

Fully Convolutional Neural Networks for Dynamic Object Detection in Grid Maps (Masters Thesis)

Objectness Scoring and Detection Proposals in Forward-Looking Sonar Images with Convolutional Neural Networks

Synthesizing Training Data for Object Detection in Indoor Scenes

6D Object Pose Estimation with Depth Images: A Seamless Approach for Robotic Interaction and Augmented Reality

Detection of Moving Object in Dynamic Background Using Gaussian Max-Pooling and Segmentation Constrained RPCA

Incremental Learning of Object Detectors without Catastrophic Forgetting

In search of inliers: 3d correspondence by local and global voting

Multiple-Kernel Based Vehicle Tracking Using 3D Deformable Model and Camera Self-Calibration

Learning in an Uncertain World: Representing Ambiguity Through Multiple Hypotheses

Nazr-CNN: Fine-Grained Classification of UAV Imagery for Damage Assessment

Quantization and Training of Low Bit-Width Convolutional Neural Networks for Object Detection

Free Space Estimation using Occupancy Grids and Dynamic Object Detection

S-OHEM: Stratified Online Hard Example Mining for Object Detection

Deep Steering: Learning End-to-End Driving Model from Spatial and Temporal Visual Cues

CoupleNet: Coupling Global Structure with Local Parts for Object Detection

Weakly Supervised Image Annotation and Segmentation with Objects and Attributes

Learning Uncertain Convolutional Features for Accurate Saliency Detection

Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection

PPR-FCN: Weakly Supervised Visual Relation Detection via Parallel Pairwise R-FCN

Optimizing Region Selection for Weakly Supervised Object Detection

Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection

Augmented Reality Meets Computer Vision : Efficient Data Generation for Urban Driving Scenes

T-CNN: Tubelets with Convolutional Neural Networks for Object Detection from Videos

Temporal Dynamic Graph LSTM for Action-driven Video Object Detection

Towards the Success Rate of One: Real-time Unconstrained Salient Object Detection

Tube Convolutional Neural Network (T-CNN) for Action Detection in Videos

Object Detection of Satellite Images Using Multi-Channel Higher-order Local Autocorrelation

A spatiotemporal model with visual attention for video classification

Team Applied Robotics: A closer look at our robotic picking system

Adversarial Examples for Semantic Segmentation and Object Detection

DeNet: Scalable Real-time Object Detection with Directed Sparse Sampling

Adaptive Feeding: Achieving Fast and Accurate Detections by Adaptively Combining Object Detectors

Unsupervised Object Discovery and Co-Localization by Deep Descriptor Transforming

Deformable Part-based Fully Convolutional Network for Object Detection

Unconstrained Still/Video-Based Face Verification with Deep Convolutional Neural Networks

A New Urban Objects Detection Framework Using Weakly Annotated Sets

Inner-Scene Similarities as a Contextual Cue for Object Detection

DeepSkeleton: Learning Multi-task Scale-associated Deep Side Outputs for Object Skeleton Extraction in Natural Images

Aerial Vehicle Tracking by Adaptive Fusion of Hyperspectral Likelihood Maps

NO Need to Worry about Adversarial Examples in Object Detection in Autonomous Vehicles

RON: Reverse Connection with Objectness Prior Networks for Object Detection

SMC Faster R-CNN: Toward a scene-specialized multi-object detector

Co-salient Object Detection Based on Deep Saliency Networks and Seed Propagation over an Integrated Graph

Saliency Guided End-to-End Learning for Weakly Supervised Object Detection

Perceptual Generative Adversarial Networks for Small Object Detection

Integrated Deep and Shallow Networks for Salient Object Detection

RGB-D Salient Object Detection Based on Discriminative Cross-modal Transfer Learning

Probabilistic Global Scale Estimation for MonoSLAM Based on Generic Object Detection

Enhancement of SSD by concatenating feature maps for object detection

Self-supervised learning of visual features through embedding images into text topic spaces

VANETs Meet Autonomous Vehicles: A Multimodal 3D Environment Learning Approach

Towards seamless multi-view scene analysis from satellite to street-level

Sequential Optimization for Efficient High-Quality Object Proposal Generation

LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded Systems

Active Control of Camera Parameters for Object Detection Algorithms

An Efficient Approach for Object Detection and Tracking of Objects in a Video with Variable Background

Learning RGB-D Salient Object Detection using background enclosure, depth contrast, and top-down features

A Benchmark Dataset and Saliency-guided Stacked Autoencoders for Video-based Salient Object Detection

Bridging between Computer and Robot Vision through Data Augmentation: a Case Study on Object Recognition

Joint Denoising / Compression of Image Contours via Shape Prior and Context Tree

Object Detection by Spatio-Temporal Analysis and Tracking of the Detected Objects in a Video with Variable Background

Compressive Sensing Approaches for Autonomous Object Detection in Video Sequences

Relief R-CNN : Utilizing Convolutional Features for Fast Object Detection

3D Object Proposals using Stereo Imagery for Accurate Object Class Detection

Speed/accuracy trade-offs for modern convolutional object detectors

Context-based Object Viewpoint Estimation: A 2D Relational Approach

Accurate Single Stage Detector Using Recurrent Rolling Convolution

Skeleton Boxes: Solving skeleton based action detection with a single deep convolutional neural network

Visual-Inertial-Semantic Scene Representation for 3-D Object Detection

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark

Fast Learning and Prediction for Object Detection using Whitened CNN Features

Generating Holistic 3D Scene Abstractions for Text-based Image Retrieval

A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection

Pixelwise Instance Segmentation with a Dynamically Instantiated Network

Convolutional neural networks for segmentation and object detection of human semen

The Stixel world: A medium-level representation of traffic scenes

Multiple Instance Detection Network with Online Instance Classifier Refinement

Efficient Privacy Preserving Viola-Jones Type Object Detection via Random Base Image Representation

Exploiting Web Images for Dataset Construction: A Domain Robust Approach

YouTube-BoundingBoxes: A Large High-Precision Human-Annotated Data Set for Object Detection in Video

Cost Sensitive Learning of Deep Feature Representations from Imbalanced Data

Cross-View Image Matching for Geo-localization in Urban Environments

Object Detection via Aspect Ratio and Context Aware Region-based Convolutional Networks

IOD-CNN: Integrating Object Detection Networks for Event Recognition

Vision-based Real-Time Aerial Object Localization and Tracking for UAV Sensing System

Weakly-supervised DCNN for RGB-D Object Recognition in Real-World Applications Which Lack Large-scale Annotated Training Data

Improving training of deep neural networks via Singular Value Bounding

Evaluating Deep Convolutional Neural Networks for Material Classification

Development of An Android Application for Object Detection Based on Color, Shape, or Local Features

Subcategory-aware Convolutional Neural Networks for Object Proposals and Detection

Bridging Saliency Detection to Weakly Supervised Object Detection Based on Self-paced Curriculum Learning

Weakly- and Semi-Supervised Object Detection with Expectation-Maximization Algorithm

Seeing What Is Not There: Learning Context to Determine Where Objects Are Missing

Learning Chained Deep Features and Classifiers for Cascade in Object Detection

A dataset and exploration of models for understanding video data through fill-in-the-blank question-answering

An Experimental Study of Deep Convolutional Features For Iris Recognition

3D Fully Convolutional Network for Vehicle Detection in Point Cloud

Information Pursuit: A Bayesian Framework for Sequential Scene Parsing

Abnormal Event Detection in Videos using Spatiotemporal Autoencoder

PVANet: Lightweight Deep Neural Networks for Real-time Object Detection

STC: A Simple to Complex Framework for Weakly-supervised Semantic Segmentation

Point Pair Feature based Object Detection for Random Bin Picking

Skin Cancer Detection and Tracking using Data Synthesis and Deep Learning

Object Detection Free Instance Segmentation With Labeling Transformations

Video Processing from Electro-optical Sensors for Object Detection and Tracking in Maritime Environment: A Survey

Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization

Node-Adapt, Path-Adapt and Tree-Adapt:Model-Transfer Domain Adaptation for Random Forest

Generalized Haar Filter based Deep Networks for Real-Time Object Detection in Traffic Scene

mdBrief - A Fast Online Adaptable, Distorted Binary Descriptor for Real-Time Applications Using Calibrated Wide-Angle Or Fisheye Cameras

Enhanced Object Detection via Fusion With Prior Beliefs from Image Classification

Multi-view metric learning for multi-instance image classification

A Robust 3D-2D Interactive Tool for Scene Segmentation and Annotation

Exploiting Depth from Single Monocular Images for Object Detection and Semantic Segmentation

Recovering hard-to-find object instances by sampling context-based object proposals

PVANET: Deep but Lightweight Neural Networks for Real-time Object Detection

Using Filter Banks in Convolutional Neural Networks for Texture Classification

GAdaBoost: Accelerating Adaboost Feature Selection with Genetic Algorithms

Detection of concealed cars in complex cargo X-ray imagery using Deep Learning

UberNet: Training a `Universal' Convolutional Neural Network for Low-, Mid-, and High-Level Vision using Diverse Datasets and Limited Memory

Face Detection with End-to-End Integration of a ConvNet and a 3D Model

Object Detection, Tracking, and Motion Segmentation for Object-level Video Segmentation

Intra-layer Nonuniform Quantization for Deep Convolutional Neural Network

Fusing Deep Convolutional Networks for Large Scale Visual Concept Classification

Challenges in video based object detection in maritime scenario using computer vision

A 58.6mW Real-Time Programmable Object Detector with Multi-Scale Multi-Object Support Using Deformable Parts Model on 1920x1080 Video at 30fps

A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection

A Multi-cut Formulation for Joint Segmentation and Tracking of Multiple Objects

Deep Learning of Local RGB-D Patches for 3D Object Detection and 6D Pose Estimation

Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking

Context Matters: Refining Object Detection in Video with Recurrent Neural Networks

Hierarchical Bayesian Noise Inference for Robust Real-time Probabilistic Object Classification

R-FCN: Object Detection via Region-based Fully Convolutional Networks

High-resolution LIDAR-based Depth Mapping using Bilateral Filter

Attend Refine Repeat: Active Box Proposal Generation via In-Out Localization

Re-ranking Object Proposals for Object Detection in Automatic Driving

Learning to decompose for object detection and instance segmentation

Recognizing Activities of Daily Living with a Wrist-mounted Camera

An Empirical Study into Annotator Agreement, Ground Truth Estimation, and Algorithm Evaluation

Track and Transfer: Watching Videos to Simulate Strong Human Supervision for Weakly-Supervised Object Detection

Recovering 6D Object Pose and Predicting Next-Best-View in the Crowd

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

Object Detection from Video Tubelets with Convolutional Neural Networks

Training Region-based Object Detectors with Online Hard Example Mining

Object Skeleton Extraction in Natural Images by Fusing Scale-associated Deep Side Outputs

HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detection

Learning Hough Regression Models via Bridge Partial Least Squares for Object Detection

An end-to-end convolutional selective autoencoder approach to Soybean Cyst Nematode eggs detection

Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices

Active Detection and Localization of Textureless Objects in Cluttered Environments

Buried object detection using handheld WEMI with task-driven extended functions of multiple instances

Region Graph Based Method for Multi-Object Detection and Tracking using Depth Cameras

Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images

Keypoint Density-based Region Proposal for Fine-Grained Object Detection and Classification using Regions with Convolutional Neural Network Features

A Dataset for Improved RGBD-based Object Detection and Pose Estimation for Warehouse Pick-and-Place

COROLA: A Sequential Solution to Moving Object Detection Using Low-rank Approximation

Towards the Design of an End-to-End Automated System for Image and Video-based Recognition

Analysing domain shift factors between videos and images for object detection

DeePM: A Deep Part-Based Model for Object Detection and Semantic Part Localization

Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and Pose-dependent Priors

Detecting Temporally Consistent Objects in Videos through Object Class Label Propagation

Improving Object Detection with Deep Convolutional Networks via Bayesian Optimization and Structured Prediction

Lifting GIS Maps into Strong Geometric Context for Scene Understanding

Automatic 3D object detection of Proteins in Fluorescent labeled microscope images with spatial statistical analysis

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Robust Method of Vote Aggregation and Proposition Verification for Invariant Local Features

A framework for robust object multi-detection with a vote aggregation and a cascade filtering

Modeling Colors of Single Attribute Variations with Application to Food Appearance

Instance-aware Semantic Segmentation via Multi-task Network Cascades

Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks

Evaluation of Object Detection Proposals Under Condition Variations

Exploring Person Context and Local Scene Context for Object Detection

Accelerating Very Deep Convolutional Networks for Classification and Detection

LOGO-Net: Large-scale Deep Logo Detection and Brand Recognition with Deep Region-based Convolutional Networks

Sketch-based Image Retrieval from Millions of Images under Rotation, Translation and Scale Variations

Cascaded Sparse Spatial Bins for Efficient and Effective Generic Object Detection

Spatial Semantic Regularisation for Large Scale Object Detection

Relaxed Multiple-Instance SVM with Application to Object Discovery

Data Association for an Adaptive Multi-target Particle Filter Tracking System

Moving Object Detection in Video Using Saliency Map and Subspace Learning

AttentionNet: Aggregating Weak Directions for Accurate Object Detection

Object detection via a multi-region & semantic segmentation-aware CNN model

DenseBox: Unifying Landmark Localization with End to End Object Detection

VESICLE: Volumetric Evaluation of Synaptic Interfaces using Computer vision at Large Scale

LCNN: Low-level Feature Embedded CNN for Salient Object Detection

Pedestrian Detection with Spatially Pooled Features and Structured Ensemble Learning

New Descriptor for Glomerulus Detection in Kidney Microscopy Image

Reflection Invariance: an important consideration of image orientation

DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection

Inner and Inter Label Propagation: Salient Object Detection in the Wild

Watch and Learn: Semi-Supervised Learning of Object Detectors from Videos

GazeDPM: Early Integration of Gaze Information in Deformable Part Models

Object Class Detection and Classification using Multi Scale Gradient and Corner Point based Shape Descriptors

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

Transferring Rich Feature Hierarchies for Robust Visual Tracking

Multi-view Face Detection Using Deep Convolutional Neural Networks

Learning Multiple Visual Tasks while Discovering their Structure

A Coarse-to-Fine Model for 3D Pose Estimation and Sub-category Recognition

Unsupervised Video Analysis Based on a Spatiotemporal Saliency Detector

Visual Chunking: A List Prediction Framework for Region-Based Object Detection

Context Forest for efficient object detection with large mixture models

Convolutional Neural Networks for joint object detection and pose estimation: A comparative study

segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection

An Expressive Deep Model for Human Action Parsing from A Single Image

Discriminatively Trained And-Or Graph Models for Object Shape Detection

On the Distribution of Salient Objects in Web Images and its Influence on Salient Object Detection

Semantic Part Segmentation using Compositional Model combining Shape and Appearance

Compressing Deep Convolutional Networks using Vector Quantization

What is a salient object? A dataset and a baseline model for salient object detection

Untangling Local and Global Deformations in Deep Convolutional Networks for Image Classification and Sliding Window Detection

ConceptLearner: Discovering Visual Concepts from Weakly Labeled Image Collections

End-to-End Integration of a Convolutional Network, Deformable Parts Model and Non-Maximum Suppression

Do More Dropouts in Pool5 Feature Maps for Better Object Detection

Towards Scene Understanding with Detailed 3D Object Representations

A Faster Method for Tracking and Scoring Videos Corresponding to Sentences

Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models

Return of the Devil in the Details: Delving Deep into Convolutional Nets

Foreground-Background Segmentation Based on Codebook and Edge Detector

Rich feature hierarchies for accurate object detection and semantic segmentation

Memristive Threshold Logic Circuit Design of Fast Moving Object Detection

Deep Learning Representation using Autoencoder for 3D Shape Retrieval

DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection

2D View Aggregation for Lymph Node Detection Using a Shallow Hierarchy of Linear Classifiers

Learning Rich Features from RGB-D Images for Object Detection and Segmentation

Template Matching based Object Detection Using HOG Feature Pyramid

Human-Machine CRFs for Identifying Bottlenecks in Holistic Scene Understanding

Self-tuned Visual Subclass Learning with Shared Samples An Incremental Approach

Generic Object Detection With Dense Neural Patterns and Regionlets

A Robust Framework for Moving-Object Detection and Vehicular Traffic Density Estimation

Delegating Custom Object Detection Tasks to a Universal Classification System

Object Recognition System Design in Computer Vision: a Universal Approach

A Study of Actor and Action Semantic Retention in Video Supervoxel Segmentation

Efficient pedestrian detection by directly optimize the partial area under the ROC curve

Shadow Detection: A Survey and Comparative Evaluation of Recent Methods

Full Object Boundary Detection by Applying Scale Invariant Features in a Region Merging Segmentation Algorithm

Stereo Acoustic Perception based on Real Time Video Acquisition for Navigational Assistance

Moving Object Detection by Detecting Contiguous Outliers in the Low-Rank Representation

How important are Deformable Parts in the Deformable Parts Model?

Efficient Hierarchical Markov Random Fields for Object Detection on a Mobile Robot

Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models

Detachable Object Detection: Segmentation and Depth Ordering From Short-Baseline Video

Generalised Object Detection and Semantic Analysis: Casino Example using Matlab

Toward Parts-Based Scene Understanding with Pixel-Support Parts-Sparse Pictorial Structures

Hamiltonian Streamline Guided Feature Extraction with Applications to Face Detection

A Multiple Component Matching Framework for Person Re-Identification

Asymmetric Totally-corrective Boosting for Real-time Object Detection

A Machine Learning Approach to Recovery of Scene Geometry from Images

Incremental Training of a Detector Using Online Sparse Eigen-decomposition

LACBoost and FisherBoost: Optimally Building Cascade Classifiers

Introducing New AdaBoost Features for Real-Time Vehicle Detection

Extension of Path Probability Method to Approximate Inference over Time

Learning Object Location Predictors with Boosting and Grammar-Guided Feature Extraction

A Keygraph Classification Framework for Real-Time Object Detection

Assisted Video Sequences Indexing : Motion Analysis Based on Interest Points

PASS: An ImageNet replacement for self-supervised pretraining without humans

Bayesian Transfer Learning: An Overview of Probabilistic Graphical Models for Transfer Learning

Improving Generalization of Transfer Learning Across Domains Using Spatio-Temporal Features in Autonomous Driving

Robust Generalization of Quadratic Neural Networks via Function Identification

Fully probabilistic design for knowledge fusion between Bayesian filters under uniform disturbances

DeepGaze IIE: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling

A Study of the Generalizability of Self-Supervised Representations

AutoInit: Analytic Signal-Preserving Weight Initialization for Neural Networks

Intra-Inter Subject Self-supervised Learning for Multivariate Cardiac Signals

Effect of Pre-Training Scale on Intra- and Inter-Domain Full and Few-Shot Transfer Learning for Natural and Medical X-Ray Chest Images

A Medical Pre-Diagnosis System for Histopathological Image of Breast Cancer

Disentangling Transfer and Interference in Multi-Domain Learning

Point-set Distances for Learning Representations of 3D Point Clouds

Program-to-Circuit: Exploiting GNNs for Program Representation and Circuit Translation

Facial Anatomical Landmark Detection using Regularized Transfer Learning with Application to Fetal Alcohol Syndrome Recognition

Transfer of Pretrained Model Weights Substantially Improves Semi-Supervised Image Classification

A Supervised Machine Learning Model For Imputing Missing Boarding Stops In Smart Card Data

Contrastive Cross-Modal Pre-Training: A General Strategy for Small Sample Medical Imaging

Fisher Task Distance and Its Applications in Transfer Learning and Neural Architecture Search

Identification of Social-Media Platform of Videos through the Use of Shared Features

Training Deep Networks from Zero to Hero: avoiding pitfalls and going beyond

Less is More: Lighter and Faster Deep Neural Architecture for Tomato Leaf Disease Classification

Robust Importance Sampling for Error Estimation in the Context of Optimal Bayesian Transfer Learning

A Bayesian Approach to (Online) Transfer Learning: Theory and Algorithms

Towards Learning Spatially Discriminative Feature Representations

Explanation and Use of Uncertainty Obtained by Bayesian Neural Network Classifiers for Breast Histopathology Images

roadscene2vec: A Tool for Extracting and Embedding Road Scene-Graphs

Deep Learning of Transferable MIMO Channel Modes for 6G V2X Communications

Why Adversarial Reprogramming Works, When It Fails, and How to Tell the Difference

Towards Explainable, Privacy-Preserved Human-Motion Affect Recognition

A Framework for Supervised Heterogeneous Transfer Learning using Dynamic Distribution Adaptation and Manifold Regularization

Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set Framework

Targeting Underrepresented Populations in Precision Medicine: A Federated Transfer Learning Approach

Geometry Based Machining Feature Retrieval with Inductive Transfer Learning

CDCGen: Cross-Domain Conditional Generation via Normalizing Flows and Adversarial Training

TransFER: Learning Relation-aware Facial Expression Representations with Transformers

A Scaling Law for Synthetic-to-Real Transfer: A Measure of Pre-Training

Learning Topology from Synthetic Data for Unsupervised Depth Completion

How Transferable Are Self-supervised Features in Medical Image Classification Tasks?

Analysis of Information Transfer from Heterogeneous Sources via Precise High-dimensional Asymptotics

A new semi-supervised inductive transfer learning framework: Co-Transfer

Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier

Combination of Transfer Learning, Recursive Learning and Ensemble Learning for Multi-Day Ahead COVID-19 Cases Prediction in India using Gated Recurrent Unit Networks

Distance Metric-Based Learning with Interpolated Latent Features for Location Classification in Endoscopy Image and Video

Concurrent Discrimination and Alignment for Self-Supervised Feature Learning

Inverse design optimization framework via a two-step deep learning approach: application to a wind turbine airfoil

STAR: Noisy Semi-Supervised Transfer Learning for Visual Classification

eGAN: Unsupervised approach to class imbalance using transfer learning

ConvNets vs. Transformers: Whose Visual Representations are More Transferable?

TL-SDD: A Transfer Learning-Based Method for Surface Defect Detection with Few Samples

Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection

Integrated Generalized Zero-Shot Learning for Fine-Grained Classification

HCR-Net: A deep learning based script independent handwritten character recognition network

Focus on the Positives: Self-Supervised Learning for Biodiversity Monitoring

GeoCLR: Georeference Contrastive Learning for Efficient Seafloor Image Interpretation

A Systematic Benchmarking Analysis of Transfer Learning for Medical Image Analysis

PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation

Dynamic Attention-based Communication-Efficient Federated Learning

Communication Optimization in Large Scale Federated Learning using Autoencoder Compressed Weight Updates

Resetting the baseline: CT-based COVID-19 diagnosis with Deep Transfer Learning is not as accurate as widely thought

Self-supervised Visual Attribute Learning for Fashion Compatibility

Towards artificially intelligent recycling Improving image processing for waste classification

Transfer Learning Gaussian Anomaly Detection by Fine-Tuning Representations

Densely Guided Knowledge Distillation using Multiple Teacher Assistants

Adaptive Consistency Regularization for Semi-Supervised Transfer Learning

Transfer Learning for Future Wireless Networks: A Comprehensive Survey

Deep Transfer Learning for Identifications of Slope Surface Cracks

Basis Scaling and Double Pruning for Efficient Transfer Learning

A Data Augmented Approach to Transfer Learning for Covid-19 Detection

Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures

Transformer-based Map Matching Model with Limited Ground-Truth Data using Transfer-Learning Approach

Few-shot calibration of low-cost air pollution (PM2.5) sensors using meta-learning

Semi-Supervising Learning, Transfer Learning, and Knowledge Distillation with SimCLR

Using transfer learning to study burned area dynamics: A case study of refugee settlements in West Nile, Northern Uganda

Transfer Learning in Electronic Health Records through Clinical Concept Embedding

Transferable Knowledge-Based Multi-Granularity Aggregation Network for Temporal Action Localization: Submission to ActivityNet Challenge 2021

An Uncertainty-Aware Deep Learning Framework for Defect Detection in Casting Products

Developing efficient transfer learning strategies for robust scene recognition in mobile robotics using pre-trained convolutional neural networks

Compositional Models: Multi-Task Learning and Knowledge Transfer with Modular Networks

Size doesn't matter: predicting physico- or biochemical properties based on dozens of molecules

Window Detection In Facade Imagery: A Deep Learning Approach Using Mask R-CNN

FedHealth 2: Weighted Federated Transfer Learning via Batch Normalization for Personalized Healthcare

Transfer Learning for Credit Card Fraud Detection: A Journey from Research to Production

Equivariant Graph Neural Networks for 3D Macromolecular Structure

Information Theoretic Evaluation of Privacy-Leakage, Interpretability, and Transferability for a Novel Trustworthy AI Framework

Cats, not CAT scans: a study of dataset similarity in transfer learning for 2D medical image classification

SynLiDAR: Learning From Synthetic LiDAR Sequential Point Cloud for Semantic Segmentation

Detection of Plant Leaf Disease Directly in the JPEG Compressed Domain using Transfer Learning Technique

Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability

Exploiting the relationship between visual and textual features in social networks for image classification with zero-shot deep learning

Introducing the structural bases of typicality effects in deep learning

Transfer Learning in Information Criteria-based Feature Selection

Dealing with Adversarial Player Strategies in the Neural Network Game iNNk through Ensemble Learning

Towards Scheduling Federated Deep Learning using Meta-Gradients for Inter-Hospital Learning

Extended Few-Shot Learning: Exploiting Existing Resources for Novel Tasks

Learning from scarce information: using synthetic data to classify Roman fine ware pottery

Empirically Measuring Transfer Distance for System Design and Operation

Parasitic Egg Detection and Classification in Low-cost Microscopic Images using Transfer Learning

Deep Learning for Molecular Graphs with Tiered Graph Autoencoders and Graph Prediction

Extraction of Key-frames of Endoscopic Videos by using Depth Information

Practical Transferability Estimation for Image Classification Tasks

A Systematic Evaluation of Domain Adaptation in Facial Expression Recognition

Domain Adaptation Broad Learning System Based on Locally Linear Embedding

An Evaluation of Self-Supervised Pre-Training for Skin-Lesion Analysis

Multiple Meta-model Quantifying for Medical Visual Question Answering

Pre-training transformer-based framework on large-scale pediatric claims data for downstream population-specific tasks

Permuted AdaIN: Reducing the Bias Towards Global Statistics in Image Classification

LogME: Practical Assessment of Pre-trained Models for Transfer Learning

Interpretable Deep Learning for the Remote Characterisation of Ambulation in Multiple Sclerosis using Smartphones

Towards Better Shale Gas Production Forecasting Using Transfer Learning

Analysis Towards Classification of Infection and Ischaemia of Diabetic Foot Ulcers

Semi-supervised Optimal Transport with Self-paced Ensemble for Cross-hospital Sepsis Early Detection

Adversarial Training Helps Transfer Learning via Better Representations

RobustSleepNet: Transfer learning for automated sleep staging at scale

Materials Representation and Transfer Learning for Multi-Property Prediction

PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python

Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning

FG-Net: Fast Large-Scale LiDAR Point Clouds Understanding Network Leveraging Correlated Feature Mining and Geometric-Aware Modelling

Improving filling level classification with adversarial training

Deep Transfer Learning for Brain Magnetic Resonance Image Multi-class Classification

Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks

Generating Thermal Human Faces for Physiological Assessment Using Thermal Sensor Auxiliary Labels

Physics-Informed Neural Network for Modelling the Thermochemical Curing Process of Composite-Tool Systems During Manufacture

Fortify Machine Learning Production Systems: Detect and Classify Adversarial Attacks

HistoTransfer: Understanding Transfer Learning for Histopathology

Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions

Non-Transferable Learning: A New Approach for Model Verification and Authorization

FGLP: A Federated Fine-Grained Location Prediction System for Mobile Users

Efficient Deep Learning Architectures for Fast Identification of Bacterial Strains in Resource-Constrained Devices

ModelDiff: Testing-Based DNN Similarity Comparison for Model Reuse Detection

HPO-B: A Large-Scale Reproducible Benchmark for Black-Box HPO based on OpenML

A multi-objective perspective on jointly tuning hardware and hyperparameters

Probing transfer learning with a model of synthetic correlated datasets

Affordance Transfer Learning for Human-Object Interaction Detection

DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Rendering

SpaceMeshLab: Spatial Context Memoization and Meshgrid Atrous Convolution Consensus for Semantic Segmentation

FedNILM: Applying Federated Learning to NILM Applications at the Edge

TinyTL: Reduce Activations, Not Trainable Parameters for Efficient On-Device Learning

Simultaneous Corn and Soybean Yield Prediction from Remote Sensing Data Using Deep Transfer Learning

When Vision Transformers Outperform ResNets without Pretraining or Strong Data Augmentations

On the Effectiveness of Vision Transformers for Zero-shot Face Anti-Spoofing

Out-of-Distribution Detection in Dermatology using Input Perturbation and Subset Scanning

Neural Network Training Using $\ell_1$-Regularization and Bi-fidelity Data

Using Early-Learning Regularization to Classify Real-World Noisy Data

LIFT-SLAM: a deep-learning feature-based monocular visual SLAM method

Transfer Learning as an Enhancement for Reconfiguration Management of Cyber-Physical Production Systems

Transfer Learning under High-dimensional Generalized Linear Models

Open-Ended Fine-Grained 3D Object Categorization by Combining Shape and Texture Features in Multiple Colorspaces

A Survey on Anomaly Detection for Technical Systems using LSTM Networks

Designing ECG Monitoring Healthcare System with Federated Transfer Learning and Explainable AI

TransNAS-Bench-101: Improving Transferability and Generalizability of Cross-Task Neural Architecture Search

AdaGCN:Adaptive Boosting Algorithm for Graph Convolutional Networks on Imbalanced Node Classification

PEMNET: A Transfer Learning-based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems

Multi-Type-TD-TSR -- Extracting Tables from Document Images using a Multi-stage Pipeline for Table Detection and Table Structure Recognition: from OCR to Structured Table Representations

GAN pretraining for deep convolutional autoencoders applied to Software-based Fingerprint Presentation Attack Detection

DeepDarts: Modeling Keypoints as Objects for Automatic Scorekeeping in Darts using a Single Camera

Joint Discriminative and Generative Learning for Person Re-identification

Automatic Assessment of Alzheimer's Disease Diagnosis Based on Deep Learning Techniques

Deep Metric Learning for Few-Shot Image Classification: A Selective Review

Transfer Learning with Ensembles of Deep Neural Networks for Skin Cancer Detection in Imbalanced Data Sets

Unsupervised Feature Learning by Cross-Level Instance-Group Discrimination

Differentially Private Transfer Learning with Conditionally Deep Autoencoders

TAR: Generalized Forensic Framework to Detect Deepfakes using Weakly Supervised Learning

ChaLearn LAP Large Scale Signer Independent Isolated Sign Language Recognition Challenge: Design, Results and Future Research

FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare

Slash or burn: Power line and vegetation classification for wildfire prevention

Enhancing ensemble learning and transfer learning in multimodal data analysis by adaptive dimensionality reduction

ASMNet: a Lightweight Deep Neural Network for Face Alignment and Pose Estimation

GANTL: Towards Practical and Real-Time Topology Optimization with Conditional GANs and Transfer Learning

Solving Linear Inverse Problems Using the Prior Implicit in a Denoiser

Online Transfer Learning: Negative Transfer and Effect of Prior Knowledge

Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data

GistNet: a Geometric Structure Transfer Network for Long-Tailed Recognition

With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations

A Deep Transfer Learning-based Edge Computing Method for Home Health Monitoring

Renofeation: A Simple Transfer Learning Method for Improved Adversarial Robustness

Medical Transformer: Universal Brain Encoder for 3D MRI Analysis

Imitating Targets from all sides: An Unsupervised Transfer Learning method for Person Re-identification

Towards Sustainable Census Independent Population Estimation in Mozambique

Improving Botnet Detection with Recurrent Neural Network and Transfer Learning

Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification

Landmark-Aware and Part-based Ensemble Transfer Learning Network for Facial Expression Recognition from Static images

Transfer learning suppresses simulation bias in predictive models built from sparse, multi-modal data

Personalized Semi-Supervised Federated Learning for Human Activity Recognition

Deep Learning Based Classification of Unsegmented Phonocardiogram Spectrograms Leveraging Transfer Learning

Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings

Spirit Distillation: Precise Real-time Semantic Segmentation of Road Scenes with Insufficient Data

Assessment of deep learning based blood pressure prediction from PPG and rPPG signals

Do Deep Neural Networks Forget Facial Action Units? -- Exploring the Effects of Transfer Learning in Health Related Facial Expression Recognition

Fruit Quality and Defect Image Classification with Conditional GAN Data Augmentation

Self-Supervised Contrastive Learning for Efficient User Satisfaction Prediction in Conversational Agents

Active, Continual Fine Tuning of Convolutional Neural Networks for Reducing Annotation Efforts

Transfer Learning for Oral Cancer Detection using Microscopic Images

CutPaste: Self-Supervised Learning for Anomaly Detection and Localization

DerainCycleGAN: Rain Attentive CycleGAN for Single Image Deraining and Rainmaking

Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark

TATL: Task Agnostic Transfer Learning for Skin Attributes Detection

On the Pitfalls of Learning with Limited Data: A Facial Expression Recognition Case Study

A Realistic Evaluation of Semi-Supervised Learning for Fine-Grained Classification

Drowsiness Detection Based On Driver Temporal Behavior Using a New Developed Dataset

SimPLE: Similar Pseudo Label Exploitation for Semi-Supervised Classification

Automated Cleanup of the ImageNet Dataset by Model Consensus, Explainability and Confident Learning

Sparse Object-level Supervision for Instance Segmentation with Pixel Embeddings

Interpretable and Transferable Models to Understand the Impact of Lockdown Measures on Local Air Quality

OTCE: A Transferability Metric for Cross-Domain Cross-Task Representations

On Robustness and Transferability of Convolutional Neural Networks

Channel Scaling: A Scale-and-Select Approach for Transfer Learning

Intra-Inter Camera Similarity for Unsupervised Person Re-Identification

A Modular and Unified Framework for Detecting and Localizing Video Anomalies

Cognitive simulation models for inertial confinement fusion: Combining simulation and experimental data

Self-training for Few-shot Transfer Across Extreme Task Differences

3D_DEN: Open-ended 3D Object Recognition using Dynamically Expandable Networks

Bullseye Polytope: A Scalable Clean-Label Poisoning Attack with Improved Transferability

Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning

Interleaving Learning, with Application to Neural Architecture Search

Transfer Learning Can Outperform the True Prior in Double Descent Regularization

Inter-subject Deep Transfer Learning for Motor Imagery EEG Decoding

Deep Transfer Learning for Infectious Disease Case Detection Using Electronic Medical Records

VIPriors 1: Visual Inductive Priors for Data-Efficient Deep Learning Challenges

NemaNet: A convolutional neural network model for identification of nematodes soybean crop in brazil

Use of Transfer Learning and Wavelet Transform for Breast Cancer Detection

Contrastive Learning Meets Transfer Learning: A Case Study In Medical Image Analysis

TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning

AdeNet: Deep learning architecture that identifies damaged electrical insulators in power lines

Ultra Efficient Transfer Learning with Meta Update for Cross Subject EEG Classification

FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation

Transfer of Fully Convolutional Policy-Value Networks Between Games and Game Variants

Comparative evaluation of CNN architectures for Image Caption Generation

EEV: A Large-Scale Dataset for Studying Evoked Expressions from Video

Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-supervised Learning

On the Limits to Multi-Modal Popularity Prediction on Instagram -- A New Robust, Efficient and Explainable Baseline

Ensemble Transfer Learning of Elastography and B-mode Breast Ultrasound Images

Domain Adaptation with Joint Learning for Generic, Optical Car Part Recognition and Detection Systems (Go-CaRD)

Real-Time Topology Optimization in 3D via Deep Transfer Learning

Domain-Specific Priors and Meta Learning for Few-Shot First-Person Action Recognition

Transfer learning based few-shot classification using optimal transport mapping from preprocessed latent space of backbone neural network

Partial transfusion: on the expressive influence of trainable batch norm parameters for transfer learning

Boosting Template-based SSVEP Decoding by Cross-domain Transfer Learning

Deep Multilabel CNN for Forensic Footwear Impression Descriptor Identification

MetaTune: Meta-Learning Based Cost Model for Fast and Efficient Auto-tuning Frameworks

HydroDeep -- A Knowledge Guided Deep Neural Network for Geo-Spatiotemporal Data Analysis

Common Spatial Generative Adversarial Networks based EEG Data Augmentation for Cross-Subject Brain-Computer Interface

Multi-kernel Passive Stochastic Gradient Algorithms and Transfer Learning

Damage detection using in-domain and cross-domain transfer learning

Unsupervised Audio-Visual Subspace Alignment for High-Stakes Deception Detection

Show, Attend and Distill:Knowledge Distillation via Attention-based Feature Matching

Noise-Response Analysis of Deep Neural Networks Quantifies Robustness and Fingerprints Structural Malware

Recurrent Neural Network for MoonBoard Climbing Route Classification and Generation

Real-time detection of uncalibrated sensors using Neural Networks

CODE-AE: A Coherent De-confounding Autoencoder for Predicting Patient-Specific Drug Response From Cell Line Transcriptomics

AutoFCL: Automatically Tuning Fully Connected Layers for Handling Small Dataset

FADACS: A Few-shot Adversarial Domain Adaptation Architecture for Context-Aware Parking Availability Sensing

Performance Evaluation of Convolutional Neural Networks for Gait Recognition

Information-Theoretic Bounds on Transfer Generalization Gap Based on Jensen-Shannon Divergence

DAF:re: A Challenging, Crowd-Sourced, Large-Scale, Long-Tailed Dataset For Anime Character Recognition

Deep Neural Network Fingerprinting by Conferrable Adversarial Examples

Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations

TLU-Net: A Deep Learning Approach for Automatic Steel Surface Defect Detection

Transferring model structure in Bayesian transfer learning for Gaussian process regression

Measure-conditional Discriminator with Stationary Optimum for GANs and Statistical Distance Surrogates

A relic sketch extraction framework based on detail-aware hierarchical deep network

A Transfer Learning-based State of Charge Estimation for Lithium-Ion Battery at Varying Ambient Temperatures

Extracting Pasture Phenotype and Biomass Percentages using Weakly Supervised Multi-target Deep Learning on a Small Dataset

Transfer Learning Between Different Architectures Via Weights Injection

Phase Transitions in Transfer Learning for High-Dimensional Perceptrons

Exploring Transfer Learning on Face Recognition of Dark Skinned, Low Quality and Low Resource Face Data

Advances in deep learning methods for pavement surface crack detection and identification with visible light visual images

Ranking and Rejecting of Pre-Trained Deep Neural Networks in Transfer Learning based on Separation Index

PaXNet: Dental Caries Detection in Panoramic X-ray using Ensemble Transfer Learning and Capsule Classifier

Flexible deep transfer learning by separate feature embeddings and manifold alignment

Training Convolutional Neural Networks With Hebbian Principal Component Analysis

MailLeak: Obfuscation-Robust Character Extraction Using Transfer Learning

Cross-Domain Latent Modulation for Variational Transfer Learning

Bayesian neural network with pretrained protein embedding enhances prediction accuracy of drug-protein interaction

Predictive Analysis of Diabetic Retinopathy with Transfer Learning

Transfer Learning Based Automatic Model Creation Tool For Resource Constraint Devices

Multi-Modal Depth Estimation Using Convolutional Neural Networks

Computation-Efficient Knowledge Distillation via Uncertainty-Aware Mixup

A General Class of Transfer Learning Regression without Implementation Cost

Towards Reusable Network Components by Learning Compatible Representations

Hypothesis Disparity Regularized Mutual Information Maximization

DeepGamble: Towards unlocking real-time player intelligence using multi-layer instance segmentation and attribute detection

Stochastic analysis of heterogeneous porous material with modified neural architecture search (NAS) based physics-informed neural networks using transfer learning

Attr2Style: A Transfer Learning Approach for Inferring Fashion Styles via Apparel Attributes

Food Classification with Convolutional Neural Networks and Multi-Class Linear Discernment Analysis

Deep Learning Approach Combining Lightweight CNN Architecture with Transfer Learning: An Automatic Approach for the Detection and Recognition of Bangladeshi Banknotes

Enhancing Human Pose Estimation in Ancient Vase Paintings via Perceptually-grounded Style Transfer Learning

Developing High Quality Training Samples for Deep Learning Based Local Climate Zone Classification in Korea

Hyperspectral Classification Based on Lightweight 3-D-CNN With Transfer Learning

Deep Transfer Learning for Industrial Automation: A Review and Discussion of New Techniques for Data-Driven Machine Learning

Boosting offline handwritten text recognition in historical documents with few labeled lines

Generalisation Guarantees for Continual Learning with Orthogonal Gradient Descent

SB-MTL: Score-based Meta Transfer-Learning for Cross-Domain Few-Shot Learning

AutoTune: Automatically Tuning Convolutional Neural Networks for Improved Transfer Learning

Solvable Model for Inheriting the Regularization through Knowledge Distillation

Chair Segments: A Compact Benchmark for the Study of Object Segmentation

A Generative Model to Synthesize EEG Data for Epileptic Seizure Prediction

Transfer learning to enhance amenorrhea status prediction in cancer and fertility data with missing values

AutoBayes: Automated Bayesian Graph Exploration for Nuisance-Robust Inference

Multi-objective Neural Architecture Search with Almost No Training

Grafit: Learning fine-grained image representations with coarse labels

Transfer Learning for Aided Target Recognition: Comparing Deep Learning to other Machine Learning Approaches

Unsupervised Domain Adaptation in Semantic Segmentation via Orthogonal and Clustered Embeddings

Artificial Intelligence for COVID-19 Detection -- A state-of-the-art review

Making Graph Neural Networks Worth It for Low-Data Molecular Machine Learning

An analysis of the transfer learning of convolutional neural networks for artistic images

Unsupervised Transfer Learning for Anomaly Detection: Application to Complementary Operating Condition Transfer

Planar 3D Transfer Learning for End to End Unimodal MRI Unbalanced Data Segmentation

Deep Learning for Automatic Quality Grading of Mangoes: Methods and Insights

Application of Facial Recognition using Convolutional Neural Networks for Entry Access Control

Deep Transfer Learning for Automated Diagnosis of Skin Lesions from Photographs

Towards All-around Knowledge Transferring: Learning From Task-irrelevant Labels

Assistive Diagnostic Tool for Brain Tumor Detection using Computer Vision

On the Transferability of VAE Embeddings using Relational Knowledge with Semi-Supervision

A Study of Domain Generalization on Ultrasound-based Multi-Class Segmentation of Arteries, Veins, Ligaments, and Nerves Using Transfer Learning

Roof fall hazard detection with convolutional neural networks using transfer learning

Improving Model Accuracy for Imbalanced Image Classification Tasks by Adding a Final Batch Normalization Layer: An Empirical Study

A Transfer Learning Framework for Anomaly Detection Using Model of Normality

DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs

Generic Semi-Supervised Adversarial Subject Translation for Sensor-Based Human Activity Recognition

A Benchmark for Studying Diabetic Retinopathy: Segmentation, Grading, and Transferability

Recognizing More Emotions with Less Data Using Self-supervised Transfer Learning

Automatic identification of fossils and abiotic grains during carbonate microfacies analysis using deep convolutional neural networks

Unsupervised Attention Based Instance Discriminative Learning for Person Re-Identification

"You eat with your eyes first": Optimizing Yelp Image Advertising

Google Landmarks Dataset v2 -- A Large-Scale Benchmark for Instance-Level Recognition and Retrieval

An Audio-Video Deep and Transfer Learning Framework for Multimodal Emotion Recognition in the wild

Speech-Image Semantic Alignment Does Not Depend on Any Prior Classification Tasks

FaceLeaks: Inference Attacks against Transfer Learning Models via Black-box Queries

Multi-Class Zero-Shot Learning for Artistic Material Recognition

A Comparison of Few-Shot Learning Methods for Underwater Optical and Sonar Image Classification

Shared Space Transfer Learning for analyzing multi-site fMRI data

Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels

Glyph: Fast and Accurately Training Deep Neural Networks on Encrypted Data

Transfer Learning for Thermal Comfort Prediction in Multiple Cities

Optimising the Performance of Convolutional Neural Networks across Computing Systems using Transfer Learning

Bridging the gap between Natural and Medical Images through Deep Colorization

An Investigation of Feature Selection and Transfer Learning for Writer-Independent Offline Handwritten Signature Verification

Two-Level Attention-based Fusion Learning for RGB-D Face Recognition

Towards Accurate Knowledge Transfer via Target-awareness Representation Disentanglement

Deep Learning based Automated Forest Health Diagnosis from Aerial Images

P2L: Predicting Transfer Learning for Images and Semantic Relations

Interpretation of Swedish Sign Language using Convolutional Neural Networks and Transfer Learning

Adversarially Robust Few-Shot Learning: A Meta-Learning Approach

Effects of the Nonlinearity in Activation Functions on the Performance of Deep Learning Models

Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit

Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout

Which Model to Transfer? Finding the Needle in the Growing Haystack

KrakN: Transfer Learning framework for thin crack detection in infrastructure maintenance

Shape-aware Generative Adversarial Networks for Attribute Transfer

MetaMix: Improved Meta-Learning with Interpolation-based Consistency Regularization

PiaNet: A pyramid input augmented convolutional neural network for GGO detection in 3D lung CT scans

Vehicle Trajectory Prediction by Transfer Learning of Semi-Supervised Models

MARS: Mixed Virtual and Real Wearable Sensors for Human Activity Recognition with Multi-Domain Deep Learning Model

Conversion and Implementation of State-of-the-Art Deep Learning Algorithms for the Classification of Diabetic Retinopathy

Domain Adaptive Transfer Learning on Visual Attention Aware Data Augmentation for Fine-grained Visual Categorization

Privacy-preserving Transfer Learning via Secure Maximum Mean Discrepancy

Using ROC and Unlabeled Data for Increasing Low-Shot Transfer Learning Classification Accuracy

EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearner

The Costs and Benefits of Goal-Directed Attention in Deep Convolutional Neural Networks

Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks

Targeted transfer learning to improve performance in small medical physics datasets

Accelerating Multi-Model Inference by Merging DNNs of Different Weights

Towards Unsupervised Crowd Counting via Regression-Detection Bi-knowledge Transfer

Smart Irrigation IoT Solution using Transfer Learning for Neural Networks

Generating Realistic COVID19 X-rays with a Mean Teacher + Transfer Learning GAN

Unsupervised Transfer Learning for Spatiotemporal Predictive Networks

Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts

A Convolutional LSTM based Residual Network for Deepfake Video Detection

Revisiting the Threat Space for Vision-based Keystroke Inference Attacks

Classification of Industrial Control Systems screenshots using Transfer Learning

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization

SWP-Leaf NET: a novel multistage approach for plant leaf identification based on deep learning

Learning Shape Features and Abstractions in 3D Convolutional Neural Networks for Detecting Alzheimer's Disease

Real-time Plant Health Assessment Via Implementing Cloud-based Scalable Transfer Learning On AWS DeepLens

Machine Intelligence for Outcome Predictions of Trauma Patients During Emergency Department Care

A novel action recognition system for smart monitoring of elderly people using Action Pattern Image and Series CNN with transfer learning

A Generative Adversarial Approach To ECG Synthesis And Denoising

Large Dimensional Analysis and Improvement of Multi Task Learning

Transfer Learning for Protein Structure Classification at Low Resolution

Ensemble Transfer Learning for Emergency Landing Field Identification on Moderate Resource Heterogeneous Kubernetes Cluster

Physically-Constrained Transfer Learning through Shared Abundance Space for Hyperspectral Image Classification

Transfer Learning-based Road Damage Detection for Multiple Countries

Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning

A Flexible Selection Scheme for Minimum-Effort Transfer Learning

An End-to-End Attack on Text-based CAPTCHAs Based on Cycle-Consistent Generative Adversarial Network

Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction

Intelligent Condition Based Monitoring Techniques for Bearing Fault Diagnosis

Two Sides of the Same Coin: White-box and Black-box Attacks for Transfer Learning

Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction

An Improved Person Re-identification Method by light-weight convolutional neural network

Graph Neural Networks for UnsupervisedDomain Adaptation of Histopathological ImageAnalytics

Contact Area Detector using Cross View Projection Consistency for COVID-19 Projects

Siloed Federated Learning for Multi-Centric Histopathology Datasets

Not 3D Re-ID: a Simple Single Stream 2D Convolution for Robust Video Re-identification

Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models

An Efficient Confidence Measure-Based Evaluation Metric for Breast Cancer Screening Using Bayesian Neural Networks

Facial Expression Recognition Under Partial Occlusion from Virtual Reality Headsets based on Transfer Learning

Smile, Be Happy :) Emoji Embedding for Visual Sentiment Analysis

Using UNet and PSPNet to explore the reusability principle of CNN parameters

Dynamic Knowledge Distillation for Black-box Hypothesis Transfer Learning

A survey on domain adaptation theory: learning bounds and theoretical guarantees

Camera On-boarding for Person Re-identification using Hypothesis Transfer Learning

Fully Automated and Standardized Segmentation of Adipose Tissue Compartments by Deep Learning in Three-dimensional Whole-body MRI of Epidemiological Cohort Studies

Duality Diagram Similarity: a generic framework for initialization selection in task transfer learning

MultiCheXNet: A Multi-Task Learning Deep Network For Pneumonia-like Diseases Diagnosis From X-ray Scans

Cross-Domain Structure Preserving Projection for Heterogeneous Domain Adaptation

An Explainable Machine Learning Model for Early Detection of Parkinson's Disease using LIME on DaTscan Imagery

Beyond $\mathcal{H}$-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence

An Improvement for Capsule Networks using Depthwise Separable Convolution

Force myography benchmark data for hand gesture recognition and transfer learning

Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources

CloudifierNet -- Deep Vision Models for Artificial Image Processing

Transfer Learning for Improving Speech Emotion Classification Accuracy

Semi-Supervised Learning Approach to Discover Enterprise User Insights from Feedback and Support

Automating the Surveillance of Mosquito Vectors from Trapped Specimens Using Computer Vision Techniques

Deep-COVID: Predicting COVID-19 From Chest X-Ray Images Using Deep Transfer Learning

NSGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture Search

XMixup: Efficient Transfer Learning with Auxiliary Samples by Cross-domain Mixup

Fashionpedia: Ontology, Segmentation, and an Attribute Localization Dataset

Classification of Diabetic Retinopathy via Fundus Photography: Utilization of Deep Learning Approaches to Speed up Disease Detection

CovidCare: Transferring Knowledge from Existing EMR to Emerging Epidemic for Interpretable Prognosis

Vehicle Detection of Multi-source Remote Sensing Data Using Active Fine-tuning Network

Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows

The Information Complexity of Learning Tasks, their Structure and their Distance

X-ModalNet: A Semi-Supervised Deep Cross-Modal Network for Classification of Remote Sensing Data

Enhanced Behavioral Cloning Based self-driving Car Using Transfer Learning

Transfer learning extensions for the probabilistic classification vector machine

Sample-based Regularization: A Transfer Learning Strategy Toward Better Generalization

RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr

A New Channel Boosted Convolutional Neural Network using Transfer Learning

DRDr: Automatic Masking of Exudates and Microaneurysms Caused By Diabetic Retinopathy Using Mask R-CNN and Transfer Learning

On the application of transfer learning in prognostics and health management

Demographic Bias in Presentation Attack Detection of Iris Recognition Systems

A Survey on Self-supervised Pre-training for Sequential Transfer Learning in Neural Networks

Exploiting the Logits: Joint Sign Language Recognition and Spell-Correction

Primary Tumor Origin Classification of Lung Nodules in Spectral CT using Transfer Learning

QuantNet: Transferring Learning Across Systematic Trading Strategies

Adversarial Multi-Source Transfer Learning in Healthcare: Application to Glucose Prediction for Diabetic People

Deep Doubly Supervised Transfer Network for Diagnosis of Breast Cancer with Imbalanced Ultrasound Imaging Modalities

Train and You'll Miss It: Interactive Model Iteration with Weak Supervision and Pre-Trained Embeddings

Investigating and Exploiting Image Resolution for Transfer Learning-based Skin Lesion Classification

Between-Domain Instance Transition Via the Process of Gibbs Sampling in RBM

BEV-Seg: Bird's Eye View Semantic Segmentation Using Geometry and Semantic Point Cloud

Advantages of biologically-inspired adaptive neural activation in RNNs during learning

Generalized Zero and Few-Shot Transfer for Facial Forgery Detection

Learning compact generalizable neural representations supporting perceptual grouping

Self-Supervised Prototypical Transfer Learning for Few-Shot Classification

Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural Networks

Deep Multimodal Transfer-Learned Regression in Data-Poor Domains

Improving accuracy and speeding up Document Image Classification through parallel systems

Towards Defeating Misclassification Attacks Against Transfer Learning

Transfer learning based multi-fidelity physics informed deep neural network

MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and Architectures

Salienteye: Maximizing Engagement While Maintaining Artistic Style on Instagram Using Deep Neural Networks

Bayesian Experience Reuse for Learning from Multiple Demonstrators

Deep Learning for Change Detection in Remote Sensing Images: Comprehensive Review and Meta-Analysis

Syn2Real Transfer Learning for Image Deraining using Gaussian Processes

The continuous categorical: a novel simplex-valued exponential family

Knowledge transfer between bridges for drive-by monitoring using adversarial and multi-task learning

Continuous Transfer Learning with Label-informed Distribution Alignment

A Siamese Neural Network with Modified Distance Loss For Transfer Learning in Speech Emotion Recognition

Learning across label confidence distributions using Filtered Transfer Learning

Multi-Stage Transfer Learning with an Application to Selection Process

CNN-based Approach for Cervical Cancer Classification in Whole-Slide Histopathology Images

CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents

Visual Interest Prediction with Attentive Multi-Task Transfer Learning

Domain Specific, Semi-Supervised Transfer Learning for Medical Imaging

Learning to Transfer Dynamic Models of Underactuated Soft Robotic Hands

Hidden Markov Models and their Application for Predicting Failure Events

FuCiTNet: Improving the generalization of deep learning networks by the fusion of learned class-inherent transformations

DELTA: DEep Learning Transfer using Feature Map with Attention for Convolutional Networks

Personalized Automatic Sleep Staging with Single-Night Data: a Pilot Study with KL-Divergence Regularization

An Inductive Transfer Learning Approach using Cycle-consistent Adversarial Domain Adaptation with Application to Brain Tumor Segmentation

Generative Model-driven Structure Aligning Discriminative Embeddings for Transductive Zero-shot Learning

Visually Impaired Aid using Convolutional Neural Networks, Transfer Learning, and Particle Competition and Cooperation

Domain-specific loss design for unsupervised physical training: A new approach to modeling medical ML solutions

Transfer Learning and Online Learning for Traffic Forecasting under Different Data Availability Conditions: Alternatives and Pitfalls

Deep transfer learning for improving single-EEG arousal detection

The Mapillary Traffic Sign Dataset for Detection and Classification on a Global Scale

Can a powerful neural network be a teacher for a weaker neural network?

A deep learning framework for solution and discovery in solid mechanics

Understanding and Improving Information Transfer in Multi-Task Learning

Pruning artificial neural networks: a way to find well-generalizing, high-entropy sharp minima

Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL

Station-to-User Transfer Learning: Towards Explainable User Clustering Through Latent Trip Signatures Using Tidal-Regularized Non-Negative Matrix Factorization

Scalable learning for bridging the species gap in image-based plant phenotyping

Per-pixel Classification Rebar Exposures in Bridge Eye-inspection

Utilizing Mask R-CNN for Waterline Detection in Canoe Sprint Video Analysis

Unsupervised Person Re-identification via Multi-label Classification

Headless Horseman: Adversarial Attacks on Transfer Learning Models

Gaze-Net: Appearance-Based Gaze Estimation using Capsule Networks

Joint Supervised and Self-Supervised Learning for 3D Real-World Challenges

A white-box analysis on the writer-independent dichotomy transformation applied to offline handwritten signature verification

A Transfer Learning approach to Heatmap Regression for Action Unit intensity estimation

Adversary Helps: Gradient-based Device-Free Domain-Independent Gesture Recognition

Light3DPose: Real-time Multi-Person 3D PoseEstimation from Multiple Views

Binary Classification of Alzheimer Disease using sMRI Imaging modality and Deep Learning

On-Device Transfer Learning for Personalising Psychological Stress Modelling using a Convolutional Neural Network

Time-Frequency Analysis based Blind Modulation Classification for Multiple-Antenna Systems

Transfer Learning of Photometric Phenotypes in Agriculture Using Metadata

Adversarial Domain Adaptation Being Aware of Class Relationships

Joint Deep Cross-Domain Transfer Learning for Emotion Recognition

Ensembles of Deep Neural Networks for Action Recognition in Still Images

DEPARA: Deep Attribution Graph for Deep Knowledge Transferability

ActiLabel: A Combinatorial Transfer Learning Framework for Activity Recognition

Transfer Learning from Synthetic to Real-Noise Denoising with Adaptive Instance Normalization

Multi-class Semantic Segmentation of Skin Lesions via Fully Convolutional Networks

Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network

Customized Video QoE Estimation with Algorithm-Agnostic Transfer Learning

TransMatch: A Transfer-Learning Scheme for Semi-Supervised Few-Shot Learning

Implementation of Deep Neural Networks to Classify EEG Signals using Gramian Angular Summation Field for Epilepsy Diagnosis

A Deep Learning Method for Complex Human Activity Recognition Using Virtual Wearable Sensors

Generalizable semi-supervised learning method to estimate mass from sparsely annotated images

The Utility of Feature Reuse: Transfer Learning in Data-Starved Regimes

Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs

Optimal Transfer Learning Model for Binary Classification of Funduscopic Images through Simple Heuristics

SpotTheFake: An Initial Report on a New CNN-Enhanced Platform for Counterfeit Goods Detection

Weighted Empirical Risk Minimization: Sample Selection Bias Correction based on Importance Sampling

Leveraging Affect Transfer Learning for Behavior Prediction in an Intelligent Tutoring System

Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space

On transfer learning of neural networks using bi-fidelity data for uncertainty propagation

Convolutional Neural Networks and a Transfer Learning Strategy to Classify Parkinson's Disease from Speech in Three Different Languages

Hyperspectral Classification Based on 3D Asymmetric Inception Network with Data Fusion Transfer Learning

Automatic detection of rare pathologies in fundus photographs using few-shot learning

Classification Algorithm of Speech Data of Parkinsons Disease Based on Convolution Sparse Kernel Transfer Learning with Optimal Kernel and Parallel Sample Feature Selection

Unlabeled Data Deployment for Classification of Diabetic Retinopathy Images Using Knowledge Transfer

Extracting dispersion curves from ambient noise correlations using deep learning

Continuous Emotion Recognition via Deep Convolutional Autoencoder and Support Vector Regressor

A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning

Near real-time map building with multi-class image set labelling and classification of road conditions using convolutional neural networks

Automatic phantom test pattern classification through transfer learning with deep neural networks

Durocmien: A deep framework for duroc skeleton extraction in constraint environment

Towards detection and classification of microscopic foraminifera using transfer learning

To Transfer or Not to Transfer: Misclassification Attacks Against Transfer Learned Text Classifiers

Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes

Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs

TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images

Transferability of Deep Learning Algorithms for Malignancy Detection in Confocal Laser Endomicroscopy Images from Different Anatomical Locations of the Upper Gastrointestinal Tract

Decomposable Probability-of-Success Metrics in Algorithmic Search

A novel machine learning based framework for detection of Autism Spectrum Disorder (ASD)

Inter- and Intra-domain Knowledge Transfer for Related Tasks in Deep Character Recognition

Region-based Convolution Neural Network Approach for Accurate Segmentation of Pelvic Radiograph

Homogeneous Online Transfer Learning with Online Distribution Discrepancy Minimization

Adversarial Transfer Learning for Cross-domain Visual Recognition

Lightweight and Robust Representation of Economic Scales from Satellite Imagery

Self-Driving Car Steering Angle Prediction Based on Image Recognition

Transfer Learning-Based Outdoor Position Recovery with Telco Data

Decision Support System for Detection and Classification of Skin Cancer using CNN

AdaFilter: Adaptive Filter Fine-tuning for Deep Transfer Learning

Detection of Myocardial Infarction Based on Novel Deep Transfer Learning Methods for Urban Healthcare in Smart Cities

300 GHz Radar Object Recognition based on Deep Neural Networks and Transfer Learning

Transfer Learning from an Auxiliary Discriminative Task for Unsupervised Anomaly Detection

Learning Predicates as Functions to Enable Few-shot Scene Graph Prediction

Artificial Color Constancy via GoogLeNet with Angular Loss Function

Implicit Priors for Knowledge Sharing in Bayesian Neural Networks

A Unified Deep Learning Approach for Prediction of Parkinson's Disease

Parallel Distributed Logistic Regression for Vertical Federated Learning without Third-Party Coordinator

Automated Classification of Histopathology Images Using Transfer Learning

Extreme Low Resolution Activity Recognition with Spatial-Temporal Attention Transfer

Eliminating artefacts in Polarimetric Images using Deep Learning

Efficient Hardware Implementation of Incremental Learning and Inference on Chip

BiNet: Degraded-Manuscript Binarization in Diverse Document Textures and Layouts using Deep Encoder-Decoder Networks

A Smartphone-Based Skin Disease Classification Using MobileNet CNN

Missing Features Reconstruction and Its Impact on Classification Accuracy

Deep Transfer Learning for Thermal Dynamics Modeling in Smart Buildings

Towards a General Model of Knowledge for Facial Analysis by Multi-Source Transfer Learning

Extracting temporal features into a spatial domain using autoencoders for sperm video analysis

Semi-Supervised Histology Classification using Deep Multiple Instance Learning and Contrastive Predictive Coding

Improving speech emotion recognition via Transformer-based Predictive Coding through transfer learning

Transfusion: Understanding Transfer Learning for Medical Imaging

Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks

Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules

Deep Learning of Subsurface Flow via Theory-guided Neural Network

ATL: Autonomous Knowledge Transfer from Many Streaming Processes

Conservation AI: Live Stream Analysis for the Detection of Endangered Species Using Convolutional Neural Networks and Drone Technology

Brain-mediated Transfer Learning of Convolutional Neural Networks

Revisiting Classical Bagging with Modern Transfer Learning for On-the-fly Disaster Damage Detector

Transfer learning for Remaining Useful Life Prediction Based on Consensus Self-Organizing Models

Model-Based and Data-Driven Strategies in Medical Image Computing

Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning

Hydrocephalus verification on brain magnetic resonance images with deep convolutional neural networks and "transfer learning" technique

MaLTESE: Large-Scale Simulation-Driven Machine Learning for Transient Driving Cycles

Enhanced Transfer Learning with ImageNet Trained Classification Layer

RASNet: Segmentation for Tracking Surgical Instruments in Surgical Videos Using Refined Attention Segmentation Network

Transfer Learning using CNN for Handwritten Devanagari Character Recognition

Transferable Feature Representation for Visible-to-Infrared Cross-Dataset Human Action Recognition

Recognition Of Surface Defects On Steel Sheet Using Transfer Learning

Data-Efficient Classification of Birdcall Through Convolutional Neural Networks Transfer Learning

Automated Blood Cell Detection and Counting via Deep Learning for Microfluidic Point-of-Care Medical Devices

Swapped Face Detection using Deep Learning and Subjective Assessment

Transfer Reward Learning for Policy Gradient-Based Text Generation

KNEEL: Knee Anatomical Landmark Localization Using Hourglass Networks

Video Surveillance of Highway Traffic Events by Deep Learning Architectures

Network Transfer Learning via Adversarial Domain Adaptation with Graph Convolution

A CNN-based approach to classify cricket bowlers based on their bowling actions

Personalizing Smartwatch Based Activity Recognition Using Transfer Learning

Learning to Discover Novel Visual Categories via Deep Transfer Clustering

Tiered Graph Autoencoders with PyTorch Geometric for Molecular Graphs

Transfer Learning for Relation Extraction via Relation-Gated Adversarial Learning

Transfer Learning-Based Label Proportions Method with Data of Uncertainty

Feature Transfer Learning for Deep Face Recognition with Under-Represented Data

Data, Depth, and Design: Learning Reliable Models for Skin Lesion Analysis

Multitask and Transfer Learning for Autotuning Exascale Applications

DeePathology: Deep Multi-Task Learning for Inferring Molecular Pathology from Cancer Transcriptome

DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes

Fine-Tuning Models Comparisons on Garbage Classification for Recyclability

Relative Afferent Pupillary Defect Screening through Transfer Learning

Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation

Fast Enhanced CT Metal Artifact Reduction using Data Domain Deep Learning

A Survey on Deep Learning of Small Sample in Biomedical Image Analysis

A Computer Vision Application for Assessing Facial Acne Severity from Selfie Images

Increasing Shape Bias in ImageNet-Trained Networks Using Transfer Learning and Domain-Adversarial Methods

Apple Leaf Disease Identification through Region-of-Interest-Aware Deep Convolutional Neural Network

Learning Invariant Representations for Sentiment Analysis: The Missing Material is Datasets

Deep Metric Transfer for Label Propagation with Limited Annotated Data

Transfer Learning Using Ensemble Neural Networks for Organic Solar Cell Screening

Semisupervised Adversarial Neural Networks for Cyber Security Transfer Learning

Low-Shot Classification: A Comparison of Classical and Deep Transfer Machine Learning Approaches

Efficient Neural Task Adaptation by Maximum Entropy Initialization

A Deep Learning Approach for Real-Time 3D Human Action Recognition from Skeletal Data

Blending-target Domain Adaptation by Adversarial Meta-Adaptation Networks

Transfer learning enhanced physics informed neural network for phase-field modeling of fracture

Applying Transfer Learning To Deep Learned Models For EEG Analysis

Automatic Colon Polyp Detection using Region based Deep CNN and Post Learning Approaches

End-to-End 3D-PointCloud Semantic Segmentation for Autonomous Driving

Deep Learning for Large-Scale Real-World ACARS and ADS-B Radio Signal Classification

Transfer Learning for Segmenting Dimensionally-Reduced Hyperspectral Images

Can Synthetic Faces Undo the Damage of Dataset Bias to Face Recognition and Facial Landmark Detection?

Crop Lodging Prediction from UAV-Acquired Images of Wheat and Canola using a DCNN Augmented with Handcrafted Texture Features

Deep Transfer Learning for Single-Channel Automatic Sleep Staging with Channel Mismatch

Mechanisms for Integrated Feature Normalization and Remaining Useful Life Estimation Using LSTMs Applied to Hard-Disks

Pay Attention to Convolution Filters: Towards Fast and Accurate Fine-Grained Transfer Learning

Transfer Learning for Ultrasound Tongue Contour Extraction with Different Domains

HalalNet: A Deep Neural Network that Classifies the Halalness Slaughtered Chicken from their Images

An Empirical Evaluation of Adversarial Robustness under Transfer Learning

Transfer Learning with intelligent training data selection for prediction of Alzheimer's Disease

Differential Private Stack Generalization with an Application to Diabetes Prediction

3DPalsyNet: A Facial Palsy Grading and Motion Recognition Framework using Fully 3D Convolutional Neural Networks

Leveraging Medical Visual Question Answering with Supporting Facts

Style transfer-based image synthesis as an efficient regularization technique in deep learning

Regula Sub-rosa: Latent Backdoor Attacks on Deep Neural Networks

A general method for regularizing tensor decomposition methods via pseudo-data

A Comprehensive Study of ImageNet Pre-Training for Historical Document Image Analysis

Transfer Learning based Detection of Diabetic Retinopathy from Small Dataset

Deep Transfer Learning Methods for Colon Cancer Classification in Confocal Laser Microscopy Images

Recent Advances in Transfer Learning for Cross-Dataset Visual Recognition: A Problem-Oriented Perspective

Fonts-2-Handwriting: A Seed-Augment-Train framework for universal digit classification

SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy Labels

Tuned Inception V3 for Recognizing States of Cooking Ingredients

A Transfer-Learning Approach for Accelerated MRI using Deep Neural Networks

Migrating Knowledge between Physical Scenarios based on Artificial Neural Networks

Understanding Unconventional Preprocessors in Deep Convolutional Neural Networks for Face Identification

Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing

Large-scale weakly-supervised pre-training for video action recognition

SEALion: a Framework for Neural Network Inference on Encrypted Data

Solo or Ensemble? Choosing a CNN Architecture for Melanoma Classification

Representation Similarity Analysis for Efficient Task taxonomy & Transfer Learning

Predicting Food Security Outcomes Using Convolutional Neural Networks (CNNs) for Satellite Tasking

Double Transfer Learning for Breast Cancer Histopathologic Image Classification

Funnelling: A New Ensemble Method for Heterogeneous Transfer Learning and its Application to Cross-Lingual Text Classification

Weakly-Supervised White and Grey Matter Segmentation in 3D Brain Ultrasound

Training Data Independent Image Registration With GANs Using Transfer Learning And Segmentation Information

Learned 3D Shape Representations Using Fused Geometrically Augmented Images: Application to Facial Expression and Action Unit Detection

Heterogeneous Multi-task Metric Learning across Multiple Domains

Transferring Knowledge Fragments for Learning Distance Metric from A Heterogeneous Domain

Improving Image Classification Robustness through Selective CNN-Filters Fine-Tuning

Decomposition-Based Transfer Distance Metric Learning for Image Classification

Transfer Learning via Unsupervised Task Discovery for Visual Question Answering

Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation

Learning Implicit Generative Models by Matching Perceptual Features

Transfer Learning for Performance Modeling of Deep Neural Network Systems

Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model For Hyperspectral Image Classification

Enhance Visual Recognition under Adverse Conditions via Deep Networks

Identifying disease-free chest X-ray images with deep transfer learning

Transfer Learning for Brain-Computer Interfaces: A Euclidean Space Data Alignment Approach

Cross-Subject Transfer Learning in Human Activity Recognition Systems using Generative Adversarial Networks

Segmentation of Skin Lesions and their Attributes Using Multi-Scale Convolutional Neural Networks and Domain Specific Augmentations

Colorectal cancer diagnosis from histology images: A comparative study

Unsupervised Deep Transfer Feature Learning for Medical Image Classification

Manifold Criterion Guided Transfer Learning via Intermediate Domain Generation

Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning

What Synthesis is Missing: Depth Adaptation Integrated with Weak Supervision for Indoor Scene Parsing

Deep Radiomics for Brain Tumor Detection and Classification from Multi-Sequence MRI

PPGnet: Deep Network for Device Independent Heart Rate Estimation from Photoplethysmogram

HWNet v2: An Efficient Word Image Representation for Handwritten Documents

Improving Prostate Cancer Detection with Breast Histopathology Images

Paradox in Deep Neural Networks: Similar yet Different while Different yet Similar

PROPS: Probabilistic personalization of black-box sequence models

Transfer Learning and Meta Classification Based Deep Churn Prediction System for Telecom Industry

Wasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis

Active Transfer Learning for Persian Offline Signature Verification

Learning Representations from Persian Handwriting for Offline Signature Verification, a Deep Transfer Learning Approach

FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning

Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning

Bengali Handwritten Character Classification using Transfer Learning on Deep Convolutional Neural Network

K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning

A visual encoding model based on deep neural networks and transfer learning

Estimating Buildings' Parameters over Time Including Prior Knowledge

LapEPI-Net: A Laplacian Pyramid EPI structure for Learning-based Dense Light Field Reconstruction

Machine Learning on Biomedical Images: Interactive Learning, Transfer Learning, Class Imbalance, and Beyond

Towards Automatic Lesion Classification in the Upper Aerodigestive Tract Using OCT and Deep Transfer Learning Methods

Generative Image Translation for Data Augmentation of Bone Lesion Pathology

Transfer Learning From Sound Representations For Anger Detection in Speech

Real-world Mapping of Gaze Fixations Using Instance Segmentation for Road Construction Safety Applications

Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification

Generalization of feature embeddings transferred from different video anomaly detection domains

Putting a bug in ML: The moth olfactory network learns to read MNIST

Evaluation of Transfer Learning for Classification of: (1) Diabetic Retinopathy by Digital Fundus Photography and (2) Diabetic Macular Edema, Choroidal Neovascularization and Drusen by Optical Coherence Tomography

Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning

Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data

Predicting Parkinson's Disease using Latent Information extracted from Deep Neural Networks

Human-centric Transfer Learning Explanation via Knowledge Graph [Extended Abstract]

A novel database of Children's Spontaneous Facial Expressions (LIRIS-CSE)

Lung and Pancreatic Tumor Characterization in the Deep Learning Era: Novel Supervised and Unsupervised Learning Approaches

Virtual-to-Real-World Transfer Learning for Robots on Wilderness Trails

Transfer Learning of Artist Group Factors to Musical Genre Classification

Cats or CAT scans: transfer learning from natural or medical image source datasets?

An analytic theory of generalization dynamics and transfer learning in deep linear networks

Weightless Neural Network with Transfer Learning to Detect Distress in Asphalt

Optical Character Recognition (OCR) for Telugu: Database, Algorithm and Application

An Integrated Transfer Learning and Multitask Learning Approach for Pharmacokinetic Parameter Prediction

A General Approach to Domain Adaptation with Applications in Astronomy

Adaptive Transfer Learning in Deep Neural Networks: Wind Power Prediction using Knowledge Transfer from Region to Region and Between Different Task Domains

FDSNet: Finger dorsal image spoof detection network using light field camera

Transfer learning to model inertial confinement fusion experiments

Combating Uncertainty with Novel Losses for Automatic Left Atrium Segmentation

When Semi-Supervised Learning Meets Transfer Learning: Training Strategies, Models and Datasets

Towards Ophthalmologist Level Accurate Deep Learning System for OCT Screening and Diagnosis

ECG Arrhythmia Classification Using Transfer Learning from 2-Dimensional Deep CNN Features

Deep Learning Approach in Automatic Iceberg - Ship Detection with SAR Remote Sensing Data

Efficient transfer learning and online adaptation with latent variable models for continuous control

Deep Variational Transfer: Transfer Learning through Semi-supervised Deep Generative Models

Surgical Phase Recognition of Short Video Shots Based on Temporal Modeling of Deep Features

Disjoint Label Space Transfer Learning with Common Factorised Space

Feasibility of Colon Cancer Detection in Confocal Laser Microscopy Images Using Convolution Neural Networks

Crowd Sourcing based Active Learning Approach for Parking Sign Recognition

Learning to Unlearn: Building Immunity to Dataset Bias in Medical Imaging Studies

Cross-database non-frontal facial expression recognition based on transductive deep transfer learning

From Known to the Unknown: Transferring Knowledge to Answer Questions about Novel Visual and Semantic Concepts

On the Transferability of Representations in Neural Networks Between Datasets and Tasks

Cross-domain Deep Feature Combination for Bird Species Classification with Audio-visual Data

CNN based dense underwater 3D scene reconstruction by transfer learning using bubble database

Slum Segmentation and Change Detection : A Deep Learning Approach

Transfer Learning with Deep CNNs for Gender Recognition and Age Estimation

Performance Estimation of Synthesis Flows cross Technologies using LSTMs and Transfer Learning

MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction

Interactive dimensionality reduction using similarity projections

Cross-position Activity Recognition with Stratified Transfer Learning

Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks

A Fully Automated System for Sizing Nasal PAP Masks Using Facial Photographs

M2M-GAN: Many-to-Many Generative Adversarial Transfer Learning for Person Re-Identification

A Cross-Modal Distillation Network for Person Re-identification in RGB-Depth

Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs

Adapted Deep Embeddings: A Synthesis of Methods for $k$-Shot Inductive Transfer Learning

Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data

Named-Entity Linking Using Deep Learning For Legal Documents: A Transfer Learning Approach

Feature Representation Analysis of Deep Convolutional Neural Network using Two-stage Feature Transfer -An Application for Diffuse Lung Disease Classification-

Posture recognition using an RGB-D camera : exploring 3D body modeling and deep learning approaches

Bird Species Classification using Transfer Learning with Multistage Training

Virtual Battery Parameter Identification using Transfer Learning based Stacked Autoencoder

Using Multi-task and Transfer Learning to Solve Working Memory Tasks

Weakly-Supervised Localization and Classification of Proximal Femur Fractures

Parameter Transfer Extreme Learning Machine based on Projective Model

Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis

Investigation of Multimodal Features, Classifiers and Fusion Methods for Emotion Recognition

Ensemble of Convolutional Neural Networks for Automatic Grading of Diabetic Retinopathy and Macular Edema

Structured Probabilistic Pruning for Convolutional Neural Network Acceleration

Driving Experience Transfer Method for End-to-End Control of Self-Driving Cars

Towards Efficient Convolutional Neural Network for Domain-Specific Applications on FPGA

Detection and Segmentation of Manufacturing Defects with Convolutional Neural Networks and Transfer Learning

The Impact of Preprocessing on Deep Representations for Iris Recognition on Unconstrained Environments

DADA: Deep Adversarial Data Augmentation for Extremely Low Data Regime Classification

Automatic Plaque Detection in IVOCT Pullbacks Using Convolutional Neural Networks

Transfer Learning for Estimating Causal Effects using Neural Networks

CellLineNet: End-to-End Learning and Transfer Learning For Multiclass Epithelial Breast cell Line Classification via a Convolutional Neural Network

Building medical image classifiers with very limited data using segmentation networks

Ensemble of Convolutional Neural Networks for Dermoscopic Images Classification

Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation

A Transfer Learning based Feature-Weak-Relevant Method for Image Clustering

Semantic Segmentation of Human Thigh Quadriceps Muscle in Magnetic Resonance Images

Language Model Supervision for Handwriting Recognition Model Adaptation

Brain MRI Image Super Resolution using Phase Stretch Transform and Transfer Learning

Visual Analogies between Atari Games for Studying Transfer Learning in RL

Graph Distillation for Action Detection with Privileged Modalities

Chest X-rays Classification: A Multi-Label and Fine-Grained Problem

Bio-Measurements Estimation and Support in Knee Recovery through Machine Learning

CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement

Metric Embedding Autoencoders for Unsupervised Cross-Dataset Transfer Learning

Towards Single-phase Single-stage Detection of Pulmonary Nodules in Chest CT Imaging

State-of-the-art and gaps for deep learning on limited training data in remote sensing

Bringing Cartoons to Life: Towards Improved Cartoon Face Detection and Recognition Systems

Transfer Learning From Synthetic To Real Images Using Variational Autoencoders For Precise Position Detection

Neural Networks Trained to Solve Differential Equations Learn General Representations

A probabilistic constrained clustering for transfer learning and image category discovery

Data Efficient Lithography Modeling with Transfer Learning and Active Data Selection

Domain Adaptation for Infection Prediction from Symptoms Based on Data from Different Study Designs and Contexts

TernausNetV2: Fully Convolutional Network for Instance Segmentation

Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning

Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks

Explicit Inductive Bias for Transfer Learning with Convolutional Networks

Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-ray Segmentation

Study and development of a Computer-Aided Diagnosis system for classification of chest x-ray images using convolutional neural networks pre-trained for ImageNet and data augmentation

Domain Adaptation for MRI Organ Segmentation using Reverse Classification Accuracy

Investigating the Impact of Data Volume and Domain Similarity on Transfer Learning Applications

Hyperspectral Imaging Technology and Transfer Learning Utilized in Identification Haploid Maize Seeds

Object Recognition from very few Training Examples for Enhancing Bicycle Maps

Transductive Label Augmentation for Improved Deep Network Learning

Comparison of Semantic Segmentation Approaches for Horizon/Sky Line Detection

Cross-domain attribute representation based on convolutional neural network

Optimization of Transfer Learning for Sign Language Recognition Targeting Mobile Platform

Active Semi-supervised Transfer Learning (ASTL) for Offline BCI Calibration

Multi-label Learning Based Deep Transfer Neural Network for Facial Attribute Classification

3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning from a 2D Trained Network

A Unified Framework for Domain Adaptation using Metric Learning on Manifolds

Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification

Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate

CactusNets: Layer Applicability as a Metric for Transfer Learning

Deep Transfer Network with Joint Distribution Adaptation: A New Intelligent Fault Diagnosis Framework for Industry Application

Network Signatures from Image Representation of Adjacency Matrices: Deep/Transfer Learning for Subgraph Classification

Plaque Classification in Coronary Arteries from IVOCT Images Using Convolutional Neural Networks and Transfer Learning

Impact of ultrasound image reconstruction method on breast lesion classification with neural transfer learning

Boosting Handwriting Text Recognition in Small Databases with Transfer Learning

Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Cars

Class Subset Selection for Transfer Learning using Submodularity

Improve the performance of transfer learning without fine-tuning using dissimilarity-based multi-view learning for breast cancer histology images

Revisiting knowledge transfer for training object class detectors

Consensus-Based Transfer Linear Support Vector Machines for Decentralized Multi-Task Multi-Agent Learning

Towards Highly Accurate Coral Texture Images Classification Using Deep Convolutional Neural Networks and Data Augmentation

CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise

MirBot: A collaborative object recognition system for smartphones using convolutional neural networks

Joint Recognition of Handwritten Text and Named Entities with a Neural End-to-end Model

Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatial-Temporal Patterns

Diagnostic Classification Of Lung Nodules Using 3D Neural Networks

Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction

Learning to cluster in order to transfer across domains and tasks

Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data

Multi-Task Domain Adaptation for Deep Learning of Instance Grasping from Simulation

Classification of breast cancer histology images using transfer learning

Gaussian Process Classification with Privileged Information by Soft-to-Hard Labeling Transfer

Optimize transfer learning for lung diseases in bronchoscopy using a new concept: sequential fine-tuning

A Good Practice Towards Top Performance of Face Recognition: Transferred Deep Feature Fusion

Fusarium Damaged Kernels Detection Using Transfer Learning on Deep Neural Network Architecture

Visual aesthetic analysis using deep neural network: model and techniques to increase accuracy without transfer learning

Overcoming Catastrophic Forgetting by Incremental Moment Matching

Personalized Human Activity Recognition Using Convolutional Neural Networks

A Foreground Inference Network for Video Surveillance Using Multi-View Receptive Field

Transfer learning for diagnosis of congenital abnormalities of the kidney and urinary tract in children based on Ultrasound imaging data

Stratified Transfer Learning for Cross-domain Activity Recognition

Transfer Learning for OCRopus Model Training on Early Printed Books

Learning Modality-Invariant Representations for Speech and Images

Stacked Denoising Autoencoders and Transfer Learning for Immunogold Particles Detection and Recognition

r-BTN: Cross-domain Face Composite and Synthesis from Limited Facial Patches

Distribution-Based Categorization of Classifier Transfer Learning

Label Efficient Learning of Transferable Representations across Domains and Tasks

Towards Alzheimer's Disease Classification through Transfer Learning

Deep Learning for identifying radiogenomic associations in breast cancer

Convolutional Neural Networks for Breast Cancer Screening: Transfer Learning with Exponential Decay

Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ

Exposing Computer Generated Images by Using Deep Convolutional Neural Networks

Expectation maximization transfer learning and its application for bionic hand prostheses

Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic Imagery

Transfer learning for multi-center classification of chronic obstructive pulmonary disease

Temporal 3D ConvNets: New Architecture and Transfer Learning for Video Classification

Gaussian Process Decentralized Data Fusion Meets Transfer Learning in Large-Scale Distributed Cooperative Perception

All-Transfer Learning for Deep Neural Networks and its Application to Sepsis Classification

Transductive Zero-Shot Hashing via Coarse-to-Fine Similarity Mining

Robust and Efficient Transfer Learning with Hidden-Parameter Markov Decision Processes

Group-level Emotion Recognition using Transfer Learning from Face Identification

Neural Stain-Style Transfer Learning using GAN for Histopathological Images

Improving Accuracy of Nonparametric Transfer Learning via Vector Segmentation

Distributed Deep Transfer Learning by Basic Probability Assignment

Convolutional Neural Networks for Histopathology Image Classification: Training vs. Using Pre-Trained Networks

Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision

Subspace Selection to Suppress Confounding Source Domain Information in AAM Transfer Learning

Deep Convolutional Neural Networks for Interpretable Analysis of EEG Sleep Stage Scoring

Deep Learning for Automatic Stereotypical Motor Movement Detection using Wearable Sensors in Autism Spectrum Disorders

Best Practices in Convolutional Networks for Forward-Looking Sonar Image Recognition

Transfer Learning for Performance Modeling of Configurable Systems: An Exploratory Analysis

The Devil is in the Tails: Fine-grained Classification in the Wild

Multi-task Dictionary Learning based Convolutional Neural Network for Computer aided Diagnosis with Longitudinal Images

Stacked transfer learning for tropical cyclone intensity prediction

A Data Driven Approach for Compound Figure Separation Using Convolutional Neural Networks

Modality-bridge Transfer Learning for Medical Image Classification

Probabilistic Neural Network with Complex Exponential Activation Functions in Image Recognition using Deep Learning Framework

Fully Convolutional Networks for Diabetic Foot Ulcer Segmentation

Sensing Urban Land-Use Patterns By Integrating Google Tensorflow And Scene-Classification Models

Using Transfer Learning for Image-Based Cassava Disease Detection

Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach

Relative Camera Pose Estimation Using Convolutional Neural Networks

A Novel Transfer Learning Approach upon Hindi, Arabic, and Bangla Numerals using Convolutional Neural Networks

Boosted Zero-Shot Learning with Semantic Correlation Regularization

Exploiting Convolutional Representations for Multiscale Human Settlement Detection

Transforming Sensor Data to the Image Domain for Deep Learning - an Application to Footstep Detection

Improving speaker turn embedding by crossmodal transfer learning from face embedding

Application of Transfer Learning Approaches in Multimodal Wearable Human Activity Recognition

What's Mine is Yours: Pretrained CNNs for Limited Training Sonar ATR

Bayesian Joint Modelling for Object Localisation in Weakly Labelled Images

Pruning Convolutional Neural Networks for Resource Efficient Inference

Borrowing Treasures from the Wealthy: Deep Transfer Learning through Selective Joint Fine-tuning

Classifying Documents within Multiple Hierarchical Datasets using Multi-Task Learning

Deep-Learning Convolutional Neural Networks for scattered shrub detection with Google Earth Imagery

Robust Data Geometric Structure Aligned Close yet Discriminative Domain Adaptation

An Out-of-the-box Full-network Embedding for Convolutional Neural Networks

WebVision Challenge: Visual Learning and Understanding With Web Data

Transfer Learning by Ranking for Weakly Supervised Object Annotation

Risk Stratification of Lung Nodules Using 3D CNN-Based Multi-task Learning

Understanding the Mechanisms of Deep Transfer Learning for Medical Images

Cutting the Error by Half: Investigation of Very Deep CNN and Advanced Training Strategies for Document Image Classification

Transfer Learning for Melanoma Detection: Participation in ISIC 2017 Skin Lesion Classification Challenge

Transfer Learning by Asymmetric Image Weighting for Segmentation across Scanners

Skin cancer reorganization and classification with deep neural network

Adaptive Learning to Speed-Up Control of Prosthetic Hands: a Few Things Everybody Should Know

Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

Analyzing Learned Convnet Features with Dirichlet Process Gaussian Mixture Models

Switching EEG Headsets Made Easy: Reducing Offline Calibration Effort Using Active Weighted Adaptation Regularization

Driver Drowsiness Estimation from EEG Signals Using Online Weighted Adaptation Regularization for Regression (OwARR)

Transfer from Multiple Linear Predictive State Representations (PSR)

Latent Hinge-Minimax Risk Minimization for Inference from a Small Number of Training Samples

PCA-Initialized Deep Neural Networks Applied To Document Image Analysis

Semi-supervised Learning using Denoising Autoencoders for Brain Lesion Detection and Segmentation

Multi-Task Curriculum Transfer Deep Learning of Clothing Attributes

Disentangling Space and Time in Video with Hierarchical Variational Auto-encoders

Multi-source Transfer Learning with Convolutional Neural Networks for Lung Pattern Analysis

Transfer Learning via Latent Factor Modeling to Improve Prediction of Surgical Complications

Breast Mass Classification from Mammograms using Deep Convolutional Neural Networks

Transfer Learning Across Patient Variations with Hidden Parameter Markov Decision Processes

Self-learning Scene-specific Pedestrian Detectors using a Progressive Latent Model

Beyond Fine Tuning: A Modular Approach to Learning on Small Data

DeepGaze II: Reading fixations from deep features trained on object recognition

Transfer Learning for Material Classification using Convolutional Networks

Towards Automated Melanoma Screening: Exploring Transfer Learning Schemes

A novel transfer learning method based on common space mapping and weighted domain matching

Hyperparameter Transfer Learning through Surrogate Alignment for Efficient Deep Neural Network Training

Iterative Multi-domain Regularized Deep Learning for Anatomical Structure Detection and Segmentation from Ultrasound Images

Identifying individual facial expressions by deconstructing a neural network

Efficient Pairwise Learning Using Kernel Ridge Regression: an Exact Two-Step Method

Cross Domain Adaptation by Learning Partially Shared Classifiers and Weighting Source Data Points in the Shared Subspaces

Personalized Risk Scoring for Critical Care Patients using Mixtures of Gaussian Process Experts

Learning to Select Pre-Trained Deep Representations with Bayesian Evidence Framework

Automatic Graphic Logo Detection via Fast Region-based Convolutional Networks

Evaluation of Deep Learning based Pose Estimation for Sign Language Recognition

Transfer Learning Based on AdaBoost for Feature Selection from Multiple ConvNet Layer Features

Transferring Learned Microcalcification Group Detection from 2D Mammography to 3D Digital Breast Tomosynthesis Using a Hierarchical Model and Scope-based Normalization Features

Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping

PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

Self-Transfer Learning for Fully Weakly Supervised Object Localization

Implicit Look-alike Modelling in Display Ads: Transfer Collaborative Filtering to CTR Estimation

Basic Level Categorization Facilitates Visual Object Recognition

Minimally Supervised Feature Selection for Classification (Master's Thesis, University Politehnica of Bucharest)

Learn on Source, Refine on Target:A Model Transfer Learning Framework with Random Forests

Estimating Posterior Ratio for Classification: Transfer Learning from Probabilistic Perspective

Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets for Future Tasks

Data-selective Transfer Learning for Multi-Domain Speech Recognition

Transfer Learning for Video Recognition with Scarce Training Data for Deep Convolutional Neural Network

Dual Memory Architectures for Fast Deep Learning of Stream Data via an Online-Incremental-Transfer Strategy

Bounds on the Minimax Rate for Estimating a Prior over a VC Class from Independent Learning Tasks

Subset Feature Learning for Fine-Grained Category Classification

Visual Sentiment Prediction with Deep Convolutional Neural Networks

Multi-View Priors for Learning Detectors from Sparse Viewpoint Data

Tensor Representation and Manifold Learning Methods for Remote Sensing Images

Learning Tensors in Reproducing Kernel Hilbert Spaces with Multilinear Spectral Penalties

Controlling the Precision-Recall Tradeoff in Differential Dependency Network Analysis

Bayesian Discovery of Multiple Bayesian Networks via Transfer Learning

Transfer Learning for Content-Based Recommender Systems using Tree Matching

Inverse Density as an Inverse Problem: The Fredholm Equation Approach

Transfer Learning for Voice Activity Detection: A Denoising Deep Neural Network Perspective

Visual Transfer Learning: Informal Introduction and Literature Overview

A Slice Sampler for Restricted Hierarchical Beta Process with Applications to Shared Subspace Learning

Improving accuracy and power with transfer learning using a meta-analytic database

On spatial selectivity and prediction across conditions with fMRI

Convex Point Estimation using Undirected Bayesian Transfer Hierarchies

An Optimization Framework for Semi-Supervised and Transfer Learning using Multiple Classifiers and Clusterers

Relative Density-Ratio Estimation for Robust Distribution Comparison

Multi-parametric Solution-path Algorithm for Instance-weighted Support Vector Machines

Unsupervised Supervised Learning II: Training Margin Based Classifiers without Labels

A Comprehensive Survey and Performance Analysis of Activation Functions in Deep Learning

CCTrans: Simplifying and Improving Crowd Counting with Transformer

UFO-ViT: High Performance Linear Vision Transformer without Softmax

Infrared Small-Dim Target Detection with Transformer under Complex Backgrounds

Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration

Localizing Objects with Self-Supervised Transformers and no Labels

An Information Theory-inspired Strategy for Automatic Network Pruning

Geometry-Entangled Visual Semantic Transformer for Image Captioning

GTNet:Guided Transformer Network for Detecting Human-Object Interactions

VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding

Semi-Empirical Objective Functions for Neural MCMC Proposal Optimization

baller2vec++: A Look-Ahead Multi-Entity Transformer For Modeling Coordinated Agents

baller2vec: A Multi-Entity Transformer For Multi-Agent Spatiotemporal Modeling

Robust Mitosis Detection Using a Cascade Mask-RCNN Approach With Domain-Specific Residual Cycle-GAN Data Augmentation

Turning old models fashion again: Recycling classical CNN networks using the Lattice Transformation

Generalisable and distinctive 3D local deep descriptors for point cloud registration

Confusion-based rank similarity filters for computationally-efficient machine learning on high dimensional data

Self-Supervised Learning in Multi-Task Graphs through Iterative Consensus Shift

Learning from Small Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales

TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models

WarpedGANSpace: Finding non-linear RBF paths in GAN latent space

Multimodal Integration of Human-Like Attention in Visual Question Answering

An End-to-end Entangled Segmentation and Classification Convolutional Neural Network for Periodontitis Stage Grading from Periapical Radiographic Images

Optimising for Interpretability: Convolutional Dynamic Alignment Networks

Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift

Research on facial expression recognition based on Multimodal data fusion and neural network

Siamese Network Training Using Artificial Triplets By Sampling and Image Transformation

PETA: Photo Albums Event Recognition using Transformers Attention

TEMGNet: Deep Transformer-based Decoding of Upperlimb sEMG for Hand Gestures Recognition

A Method for Medical Data Analysis Using the LogNNet for Clinical Decision Support Systems and Edge Computing in Healthcare

MLIM: Vision-and-Language Model Pre-training with Masked Language and Image Modeling

Using Persistent Homology Topological Features to Characterize Medical Images: Case Studies on Lung and Brain Cancers

Attentive Contractive Flow: Improved Contractive Flows with Lipschitz-constrained Self-Attention

Description-based Label Attention Classifier for Explainable ICD-9 Classification

Is the Number of Trainable Parameters All That Actually Matters?

Frequency Pooling: Shift-Equivalent and Anti-Aliasing Downsampling

Multi-view analysis of unregistered medical images using cross-view transformers

Stochastic Normalizing Flows for Inverse Problems: a Markov Chains Viewpoint

Improving 360 Monocular Depth Estimation via Non-local Dense Prediction Transformer and Joint Supervised and Self-supervised Learning

OH-Former: Omni-Relational High-Order Transformer for Person Re-Identification

Towards Adversarially Robust and Domain Generalizable Stereo Matching by Rethinking DNN Feature Backbones

CC-Cert: A Probabilistic Approach to Certify General Robustness of Neural Networks

Adaptive Neural Message Passing for Inductive Learning on Hypergraphs

TA2N: Two-Stage Action Alignment Network for Few-shot Action Recognition

Self-Supervised Learning to Prove Equivalence Between Programs via Semantics-Preserving Rewrite Rules

Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction

Homography augumented momentum constrastive learning for SAR image retrieval

SemCal: Semantic LiDAR-Camera Calibration using Neural MutualInformation Estimator

CDN-MEDAL: Two-stage Density and Difference Approximation Framework for Motion Analysis

DS-Net++: Dynamic Weight Slicing for Efficient Inference in CNNs and Transformers

Multi-Tensor Network Representation for High-Order Tensor Completion

Higher Order Recurrent Space-Time Transformer for Video Action Prediction

Multi-Domain Few-Shot Learning and Dataset for Agricultural Applications

Prediction of severe thunderstorm events with ensemble deep learning and radar data

Understanding neural networks with reproducing kernel Banach spaces

MFEViT: A Robust Lightweight Transformer-based Network for Multimodal 2D+3D Facial Expression Recognition

Audio-Visual Speech Recognition is Worth 32$\times$32$\times$8 Voxels

GhostShiftAddNet: More Features from Energy-Efficient Operations

Dyadformer: A Multi-modal Transformer for Long-Range Modeling of Dyadic Interactions

Unsupervised domain adaptation for cross-modality liver segmentation via joint adversarial learning and self-learning

Reveal of Vision Transformers Robustness against Adversarial Attacks

Scalable Multi-Task Gaussian Processes with Neural Embedding of Coregionalization

Generalized Translation and Scale Invariant Online Algorithm for Adversarial Multi-Armed Bandits

Action-Conditioned 3D Human Motion Synthesis with Transformer VAE

PluGeN: Multi-Label Conditional Generation From Pre-Trained Models

Geometric Interpretation of Running Nyström-Based Kernel Machines and Error Analysis

SDTP: Semantic-aware Decoupled Transformer Pyramid for Dense Image Prediction

Towards High-Quality Temporal Action Detection with Sparse Proposals

An Empirical Evaluation of the t-SNE Algorithm for Data Visualization in Structural Engineering

Quantum-Classical Hybrid Machine Learning for Image Classification (ICCAD Special Session Paper)

TSS: Transformation-Specific Smoothing for Robustness Certification

Expression Snippet Transformer for Robust Video-based Facial Expression Recognition

KATANA: Simple Post-Training Robustness Using Test Time Augmentations

TANet: A new Paradigm for Global Face Super-resolution via Transformer-CNN Aggregation Network

Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks

Label-Attention Transformer with Geometrically Coherent Objects for Image Captioning

Pose Transformers (POTR): Human Motion Prediction with Non-Autoregressive Transformers

Neural Human Performer: Learning Generalizable Radiance Fields for Human Performance Rendering

Sampling Network Guided Cross-Entropy Method for Unsupervised Point Cloud Registration

New Encoder Learning for Captioning Heavy Rain Images via Semantic Visual Feature Matching

Integrating Sensing and Communication in Cellular Networks via NR Sidelink

RobustART: Benchmarking Robustness on Architecture Design and Training Techniques

See, Hear, Read: Leveraging Multimodality with Guided Attention for Abstractive Text Summarization

Learnable Discrete Wavelet Pooling (LDW-Pooling) For Convolutional Networks

How to Simplify Search: Classification-wise Pareto Evolution for One-shot Neural Architecture Search

High-Resolution Image Harmonization via Collaborative Dual Transformations

Scale-covariant and scale-invariant Gaussian derivative networks

Sum-Product-Attention Networks: Leveraging Self-Attention in Probabilistic Circuits

Semi-Supervised Wide-Angle Portraits Correction by Multi-Scale Transformer

A Machine Learning Modelling Benchmark for Temperature Field Reconstruction of Heat-Source Systems

Policy Optimization Using Semiparametric Models for Dynamic Pricing

CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation

Lipschitz Normalization for Self-Attention Layers with Application to Graph Neural Networks

Improving Robustness of Adversarial Attacks Using an Affine-Invariant Gradient Estimator

FINet: Dual Branches Feature Interaction for Partial-to-Partial Point Cloud Registration

DSNet: A Dual-Stream Framework for Weakly-Supervised Gigapixel Pathology Image Analysis

Automatic selection of clustering algorithms using supervised graph embedding

Fine-Grained Few Shot Learning with Foreground Object Transformation

VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows

OMNet: Learning Overlapping Mask for Partial-to-Partial Point Cloud Registration

ArtiBoost: Boosting Articulated 3D Hand-Object Pose Estimation via Online Exploration and Synthesis

Multi-source Heterogeneous Domain Adaptation with Conditional Weighting Adversarial Network

Sparse MLP for Image Recognition: Is Self-Attention Really Necessary?

DeepPyram: Enabling Pyramid View and Deformable Pyramid Reception for Semantic Segmentation in Cataract Surgery Videos

BGT-Net: Bidirectional GRU Transformer Network for Scene Graph Generation

Understanding Guided Image Captioning Performance across Domains

Convolutional Hough Matching Networks for Robust and Efficient Visual Correspondence

Bornon: Bengali Image Captioning with Transformer-based Deep learning approach

Effects of Parameter Norm Growth During Transformer Training: Inductive Bias from Gradient Descent

A Unifying View on Implicit Bias in Training Linear Neural Networks

Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer

GCsT: Graph Convolutional Skeleton Transformer for Action Recognition

Copy-Move Image Forgery Detection Based on Evolving Circular Domains Coverage

SensiX++: Bringing MLOPs and Multi-tenant Model Serving to Sensory Edge Devices

Spectral clustering on spherical coordinates under the degree-corrected stochastic blockmodel

Sparse-MLP: A Fully-MLP Architecture with Conditional Computation

Automated LoD-2 Model Reconstruction from Very-HighResolution Satellite-derived Digital Surface Model and Orthophoto

FIDNet: LiDAR Point Cloud Semantic Segmentation with Fully Interpolation Decoding

Pose-guided Inter- and Intra-part Relational Transformer for Occluded Person Re-Identification

Signal-domain representation of symbolic music for learning embedding spaces

Interpretable and Efficient Heterogeneous Graph Convolutional Network

The Animation Transformer: Visual Correspondence via Segment Matching

GANSER: A Self-supervised Data Augmentation Framework for EEG-based Emotion Recognition

Rendezvous: Attention Mechanisms for the Recognition of Surgical Action Triplets in Endoscopic Videos

Efficient Vision Transformers via Fine-Grained Manifold Distillation

Sequential Diagnosis Prediction with Transformer and Ontological Representation

Predicting Mood Disorder Symptoms with Remotely Collected Videos Using an Interpretable Multimodal Dynamic Attention Fusion Network

FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting

Semi-Relaxed Quantization with DropBits: Training Low-Bit Neural Networks via Bit-wise Regularization

Deep Collaborative Multi-Modal Learning for Unsupervised Kinship Estimation

Puzzle Solving without Search or Human Knowledge: An Unnatural Language Approach

Quick Learning Mechanism with Cross-Domain Adaptation for Intelligent Fault Diagnosis

Automatic Landmarks Correspondence Detection in Medical Images with an Application to Deformable Image Registration

Graph Attention Layer Evolves Semantic Segmentation for Road Pothole Detection: A Benchmark and Algorithms

3D Human Texture Estimation from a Single Image with Transformers

The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers

Self-supervised Product Quantization for Deep Unsupervised Image Retrieval

GeneAnnotator: A Semi-automatic Annotation Tool for Visual Scene Graph

Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution

ParamCrop: Parametric Cubic Cropping for Video Contrastive Learning

Structural Optimization Makes Graph Classification Simpler and Better

Weakly Supervised Relative Spatial Reasoning for Visual Question Answering

Representing Shape Collections with Alignment-Aware Linear Models

Rethinking Content and Style: Exploring Bias for Unsupervised Disentanglement

Layer Folding: Neural Network Depth Reduction using Activation Linearization

LG4AV: Combining Language Models and Graph Neural Networks for Author Verification

Dive into Layers: Neural Network Capacity Bounding using Algebraic Geometry

Access Control Using Spatially Invariant Permutation of Feature Maps for Semantic Segmentation Models

Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models

DeepTracks: Geopositioning Maritime Vehicles in Video Acquired from a Moving Platform

Leaf Recognition Using Convolutional Neural Networks Based Features

Pulmonary Disease Classification Using Globally Correlated Maximum Likelihood: an Auxiliary Attention mechanism for Convolutional Neural Networks

Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction

Dirac Delta Regression: Conditional Density Estimation with Clinical Trials

BVMatch: Lidar-based Place Recognition Using Bird's-eye View Images

A Protection Method of Trained CNN Model Using Feature Maps Transformed With Secret Key From Unauthorized Access

You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors

ScatSimCLR: self-supervised contrastive learning with pretext task regularization for small-scale datasets

InSeGAN: A Generative Approach to Segmenting Identical Instances in Depth Images

Is cell ratio important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: from convolutional neural networks to visual transformers

Medical SANSformers: Training self-supervised transformers without attention for Electronic Medical Records

PTT: Point-Track-Transformer Module for 3D Single Object Tracking in Point Clouds

From General to Specific: Informative Scene Graph Generation via Balance Adjustment

Object-aware Long-short-range Spatial Alignment for Few-Shot Fine-Grained Image Classification

A Battle of Network Structures: An Empirical Study of CNN, Transformer, and MLP

3DStyleNet: Creating 3D Shapes with Geometric and Texture Style Variations

FeatureEnVi: Visual Analytics for Feature Engineering Using Stepwise Selection and Semi-Automatic Extraction Approaches

Deep composition of tensor-trains using squared inverse Rosenblatt transports

GroupFormer: Group Activity Recognition with Clustered Spatial-Temporal Transformer

Generalized Huber Loss for Robust Learning and its Efficient Minimization for a Robust Statistics

Towards Fine-grained Image Classification with Generative Adversarial Networks and Facial Landmark Detection

On the Significance of Question Encoder Sequence Model in the Out-of-Distribution Performance in Visual Question Answering

AMMASurv: Asymmetrical Multi-Modal Attention for Accurate Survival Analysis with Whole Slide Images and Gene Expression Data

A review of on-device fully neural end-to-end automatic speech recognition algorithms

Adaptive wavelet distillation from neural networks through interpretations

Can the Transformer Be Used as a Drop-in Replacement for RNNs in Text-Generating GANs?

Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformers

Certified Defense to Image Transformations via Randomized Smoothing

OpenMatch: Open-set Consistency Regularization for Semi-supervised Learning with Outliers

Greenformers: Improving Computation and Memory Efficiency in Transformer Models via Low-Rank Approximation

Color2Embed: Fast Exemplar-Based Image Colorization using Color Embeddings

Improving Generalization of Batch Whitening by Convolutional Unit Optimization

Auto-Parsing Network for Image Captioning and Visual Question Answering

Discovering Spatial Relationships by Transformers for Domain Generalization

Genetic Programming for Manifold Learning: Preserving Local Topology

Detection of Illicit Drug Trafficking Events on Instagram: A Deep Multimodal Multilabel Learning Approach

CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification

Guiding Query Position and Performing Similar Attention for Transformer-Based Detection Heads

Rotationally Equivariant Neural Operators for Learning Transformations on Tensor Fields (eg 3D Images and Vector Fields)

Construction material classification on imbalanced datasets for construction monitoring automation using Vision Transformer (ViT) architecture

3D Object Localization Using 2D Estimates for Computer Vision Applications

Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model

CLIMAT: Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting from Multi-modal Data

Extracting Qualitative Causal Structure with Transformer-Based NLP

Trans4Trans: Efficient Transformer for Transparent Object Segmentation to Help Visually Impaired People Navigate in the Real World

Trans4Trans: Efficient Transformer for Transparent Object and Semantic Scene Segmentation in Real-World Navigation Assistance

Convolutional Neural Network (CNN) vs Visual Transformer (ViT) for Digital Holography

Is it Time to Replace CNNs with Transformers for Medical Images?

GAN Inversion for Out-of-Range Images with Geometric Transformations

Spatio-Temporal Inception Graph Convolutional Networks for Skeleton-Based Action Recognition

Visual Relationship Detection Using Part-and-Sum Transformers with Composite Queries

Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators

PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers

Efficient remedies for outlier detection with variational autoencoders

Real-time Image Enhancer via Learnable Spatial-aware 3D Lookup Tables

Relaxed Transformer Decoders for Direct Action Proposal Generation

Using Multilevel Circulant Matrix Approximate to Speed Up Kernel Logistic Regression

MixerGAN: An MLP-Based Architecture for Unpaired Image-to-Image Translation

BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search

Blockchain Phishing Scam Detection via Multi-channel Graph Classification

TransCenter: Transformers with Dense Queries for Multiple-Object Tracking

A Sparse Coding Interpretation of Neural Networks and Theoretical Implications

An Unpaired Shape Transforming Method for Image Translation and Cross-Domain Retrieval

M6-UFC: Unifying Multi-Modal Controls for Conditional Image Synthesis

Semantic Perturbations with Normalizing Flows for Improved Generalization

HiT: Hierarchical Transformer with Momentum Contrast for Video-Text Retrieval

Appearance Based Deep Domain Adaptation for the Classification of Aerial Images

MVTN: Multi-View Transformation Network for 3D Shape Recognition

A Latent Transformer for Disentangled Face Editing in Images and Videos

FaPN: Feature-aligned Pyramid Network for Dense Image Prediction

Direct domain adaptation through reciprocal linear transformations

GLiT: Neural Architecture Search for Global and Local Image Transformer

Investigating transformers in the decomposition of polygonal shapes as point collections

MOI-Mixer: Improving MLP-Mixer with Multi Order Interactions in Sequential Recommendation

Learning Canonical View Representation for 3D Shape Recognition with Arbitrary Views

Scene Designer: a Unified Model for Scene Search and Synthesis from Sketch

An Empirical Study of Training Self-Supervised Vision Transformers

Escaping the Gradient Vanishing: Periodic Alternatives of Softmax in Attention Mechanism

Exploring Transferable and Robust Adversarial Perturbation Generation from the Perspective of Network Hierarchy

Detecting Adversarial Examples by Input Transformations, Defense Perturbations, and Voting

Flying Guide Dog: Walkable Path Discovery for the Visually Impaired Utilizing Drones and Transformer-based Semantic Segmentation

I3CL:Intra- and Inter-Instance Collaborative Learning for Arbitrary-shaped Scene Text Detection

AMITE: A Novel Polynomial Expansion for Analyzing Neural Network Nonlinearities

Signal Processing on the Permutahedron: Tight Spectral Frames for Ranked Data Analysis

UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial Vehicles

Exploring Temporal Coherence for More General Video Face Forgery Detection

Inclusion of Domain-Knowledge into GNNs using Mode-Directed Inverse Entailment

Towards Category and Domain Alignment: Category-Invariant Feature Enhancement for Adversarial Domain Adaptation

Exploiting a Joint Embedding Space for Generalized Zero-Shot Semantic Segmentation

Disease-oriented image embedding with pseudo-scanner standardization for content-based image retrieval on 3D brain MRI

Soccer line mark segmentation with stochastic watershed transform

FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Cameras

LSG-CPD: Coherent Point Drift with Local Surface Geometry for Point Cloud Registration

VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text

CODEs: Chamfer Out-of-Distribution Examples against Overconfidence Issue

TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation

An Overview of Machine Learning-aided Optical Performance Monitoring Techniques

Multiview Detection with Shadow Transformer (and View-Coherent Data Augmentation)

Just Ask: Learning to Answer Questions from Millions of Narrated Videos

UniFaceGAN: A Unified Framework for Temporally Consistent Facial Video Editing

DANA: Dimension-Adaptive Neural Architecture for Multivariate Sensor Data

Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer

Vision-Language Transformer and Query Generation for Referring Segmentation

Video Transformer for Deepfake Detection with Incremental Learning

Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution

Mounting Video Metadata on Transformer-based Language Model for Open-ended Video Question Answering

DeepACC:Automate Chromosome Classification based on Metaphase Images using Deep Learning Framework Fused with Prior Knowledge

Automatic Polyp Segmentation via Multi-scale Subtraction Network

Learning Fair Face Representation With Progressive Cross Transformer

BERTHop: An Effective Vision-and-Language Model for Chest X-ray Disease Diagnosis

Embodied BERT: A Transformer Model for Embodied, Language-guided Visual Task Completion

DVM-CAR: A large-scale automotive dataset for visual marketing research and applications

UIBert: Learning Generic Multimodal Representations for UI Understanding

SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer

FT-TDR: Frequency-guided Transformer and Top-Down Refinement Network for Blind Face Inpainting

RaftMLP: Do MLP-based Models Dream of Winning Over Computer Vision?

Team PyKale (xy9) Submission to the EPIC-Kitchens 2021 Unsupervised Domain Adaptation Challenge for Action Recognition

Product1M: Towards Weakly Supervised Instance-Level Product Retrieval via Cross-modal Pretraining

TransForensics: Image Forgery Localization with Dense Self-Attention

Alternating linear scheme in a Bayesian framework for low-rank tensor approximation

Joint Inductive and Transductive Learning for Video Object Segmentation

Pro-UIGAN: Progressive Face Hallucination from Occluded Thumbnails

OSCAR-Net: Object-centric Scene Graph Attention for Image Attribution

Simultaneous Face Hallucination and Translation for Thermal to Visible Face Verification using Axial-GAN

PSViT: Better Vision Transformer via Token Pooling and Attention Sharing

HetEmotionNet: Two-Stream Heterogeneous Graph Recurrent Neural Network for Multi-modal Emotion Recognition

Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-valued Optimization Problem

Complex Transformer: A Framework for Modeling Complex-Valued Sequence

Bird's-Eye-View Panoptic Segmentation Using Monocular Frontal View Images

SELM: Siamese Extreme Learning Machine with Application to Face Biometrics

STR-GQN: Scene Representation and Rendering for Unknown Cameras Based on Spatial Transformation Routing

Photoacoustic Reconstruction Using Sparsity in Curvelet Frame: Image versus Data Domain

Improving Contrastive Learning by Visualizing Feature Transformation

Visual Domain Adaptation for Monocular Depth Estimation on Resource-Constrained Hardware

Householder Activations for Provable Robustness against Adversarial Attacks

Automatic Detection of Rail Components via A Deep Convolutional Transformer Network

Dual Graph Convolutional Networks with Transformer and Curriculum Learning for Image Captioning

FMMformer: Efficient and Flexible Transformer via Decomposed Near-field and Far-field Attention

TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization

Dynamic Feature Regularized Loss for Weakly Supervised Semantic Segmentation

Domain Adaptation for Autoencoder-Based End-to-End Communication Over Wireless Channels

Learn to Match: Automatic Matching Network Design for Visual Tracking

StarEnhancer: Learning Real-Time and Style-Aware Image Enhancement

Applications of Artificial Neural Networks in Microorganism Image Analysis: A Comprehensive Review from Conventional Multilayer Perceptron to Popular Convolutional Neural Network and Potential Visual Transformer

BoA-PTA, A Bayesian Optimization Accelerated Error-Free SPICE Solver

Word2Pix: Word to Pixel Cross Attention Transformer in Visual Grounding

AI Choreographer: Music Conditioned 3D Dance Generation with AIST++

Margin-Aware Intra-Class Novelty Identification for Medical Images

Multi-Head Self-Attention via Vision Transformer for Zero-Shot Learning

Boosting Few-Shot Classification with View-Learnable Contrastive Learning

CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks

On the interpretation of linear Riemannian tangent space model parameters in M/EEG

ADeLA: Automatic Dense Labeling with Attention for Viewpoint Adaptation in Semantic Segmentation

A Unified Efficient Pyramid Transformer for Semantic Segmentation

Enhancing Adversarial Robustness via Test-time Transformation Ensembling

PPT Fusion: Pyramid Patch Transformerfor a Case Study in Image Fusion

Cross-Camera Feature Prediction for Intra-Camera Supervised Person Re-identification across Distant Scenes

I2UV-HandNet: Image-to-UV Prediction Network for Accurate and High-fidelity 3D Hand Mesh Modeling

Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection

Clustering by Orthogonal NMF Model and Non-Convex Penalty Optimization

WaveCNet: Wavelet Integrated CNNs to Suppress Aliasing Effect for Noise-Robust Image Classification

TransAction: ICL-SJTU Submission to EPIC-Kitchens Action Anticipation Challenge 2021

Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers

CAPE: Encoding Relative Positions with Continuous Augmented Positional Embeddings

Long-Short Transformer: Efficient Transformers for Language and Vision

Efficient Large Scale Inlier Voting for Geometric Vision Problems

Learning with Neural Tangent Kernels in Near Input Sparsity Time

PiSLTRc: Position-informed Sign Language Transformer with Content-aware Convolution

From Implicit to Explicit feedback: A deep neural network for modeling sequential behaviours and long-short term preferences of online users

Towards the Unseen: Iterative Text Recognition by Distilling from Errors

Mixed SIGNals: Sign Language Production via a Mixture of Motion Primitives

An Energy-Efficient Edge Computing Paradigm for Convolution-based Image Upsampling

Implicit bias of gradient descent for mean squared error regression with wide neural networks

Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Graph Convolutional Network with Generalized Factorized Bilinear Aggregation

Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering

Two Headed Dragons: Multimodal Fusion and Cross Modal Transactions

Class-Incremental Domain Adaptation with Smoothing and Calibration for Surgical Report Generation

WaveFill: A Wavelet-based Generation Network for Image Inpainting

Query2Label: A Simple Transformer Way to Multi-Label Classification

ExplAIn: Explanatory Artificial Intelligence for Diabetic Retinopathy Diagnosis

Exploiting Temporal Contexts with Strided Transformer for 3D Human Pose Estimation

A Comparison of Deep Learning Classification Methods on Small-scale Image Data set: from Convolutional Neural Networks to Visual Transformers

A variational approximate posterior for the deep Wishart process

Looking for the Signs: Identifying Isolated Sign Instances in Continuous Video Footage

Delving Into Deep Walkers: A Convergence Analysis of Random-Walk-Based Vertex Embeddings

Integration of Autoencoder and Functional Link Artificial Neural Network for Multi-label Classification

A Comparison for Patch-level Classification of Deep Learning Methods on Transparent Environmental Microorganism Images: from Convolutional Neural Networks to Visual Transformers

Significant Wave Height Prediction based on Wavelet Graph Neural Network

Attention-Guided NIR Image Colorization via Adaptive Fusion of Semantic and Texture Clues

Riemannian Manifold Optimization for Discriminant Subspace Learning

Fair Preprocessing: Towards Understanding Compositional Fairness of Data Transformers in Machine Learning Pipeline

A New Clustering-Based Technique for the Acceleration of Deep Convolutional Networks

GenRadar: Self-supervised Probabilistic Camera Synthesis based on Radar Frequencies

Feature-Filter: Detecting Adversarial Examples through Filtering off Recessive Features

Precise Aerial Image Matching based on Deep Homography Estimation

Domain Generalization via Inference-time Label-Preserving Target Projections

GraphGen-Redux: a Fast and Lightweight Recurrent Model for labeled Graph Generation

RAMS-Trans: Recurrent Attention Multi-scale Transformer forFine-grained Image Recognition

Is attention to bounding boxes all you need for pedestrian action prediction?

Efficient automated U-Net based tree crown delineation using UAV multi-spectral imagery on embedded devices

Learning Vision Transformer with Squeeze and Excitation for Facial Expression Recognition

Exact Backpropagation in Binary Weighted Networks with Group Weight Transformations

CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped Windows

Double-Uncertainty Assisted Spatial and Temporal Regularization Weighting for Learning-based Registration

Mean Embeddings with Test-Time Data Augmentation for Ensembling of Representations

ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias

Looking Outside the Window: Wide-Context Transformer for the Semantic Segmentation of High-Resolution Remote Sensing Images

Referring Transformer: A One-step Approach to Multi-task Visual Grounding

Distance-based Hyperspherical Classification for Multi-source Open-Set Domain Adaptation

HAT: Hierarchical Aggregation Transformers for Person Re-identification

Developmental Stage Classification of Embryos Using Two-Stream Neural Network with Linear-Chain Conditional Random Field

Learning a Discriminant Latent Space with Neural Discriminant Analysis

Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data

A Novel Deep Learning Method for Thermal to Annotated Thermal-Optical Fused Images

Artificial Intelligence in Drug Discovery: Applications and Techniques

Combiner: Full Attention Transformer with Sparse Computation Cost

MaX-DeepLab: End-to-End Panoptic Segmentation with Mask Transformers

Bayesian Atlas Building with Hierarchical Priors for Subject-specific Regularization

Multi-view Depth Estimation using Epipolar Spatio-Temporal Networks

GiT: Graph Interactive Transformer for Vehicle Re-identification

AxonEM Dataset: 3D Axon Instance Segmentation of Brain Cortical Regions

Scenes and Surroundings: Scene Graph Generation using Relation Transformer

General Invertible Transformations for Flow-based Generative Modeling

Trans-SVNet: Accurate Phase Recognition from Surgical Videos via Hybrid Embedding Aggregation Transformer

RBM-Flow and D-Flow: Invertible Flows with Discrete Energy Base Spaces

Spatial and Temporal Networks for Facial Expression Recognition in the Wild Videos

More Reliable AI Solution: Breast Ultrasound Diagnosis Using Multi-AI Combination

The DEformer: An Order-Agnostic Distribution Estimating Transformer

A Cloud-Edge-Terminal Collaborative System for Temperature Measurement in COVID-19 Prevention

Re-understanding Finite-State Representations of Recurrent Policy Networks

HOMRS: High Order Metamorphic Relations Selector for Deep Neural Networks

MVT: Mask Vision Transformer for Facial Expression Recognition in the wild

SleepTransformer: Automatic Sleep Staging with Interpretability and Uncertainty Quantification

Combining Transformer Generators with Convolutional Discriminators

Information-Theoretic Registration with Explicit Reorientation of Diffusion-Weighted Images

Generalization of the Change of Variables Formula with Applications to Residual Flows

Wavelet Transform-assisted Adaptive Generative Modeling for Colorization

Quantile-Quantile Embedding for Distribution Transformation and Manifold Embedding with Ability to Choose the Embedding Distribution

EEG-ConvTransformer for Single-Trial EEG based Visual Stimuli Classification

Manifold Hypothesis in Data Analysis: Double Geometrically-Probabilistic Approach to Manifold Dimension Estimation

Digitizing Handwriting with a Sensor Pen: A Writer-Independent Recognizer

Multi-frame Collaboration for Effective Endoscopic Video Polyp Detection via Spatial-Temporal Feature Transformation

Predicting Opioid Use Disorder from Longitudinal Healthcare Data using Multi-stream Transformer

Rotation Transformation Network: Learning View-Invariant Point Cloud for Classification and Segmentation

Feature Fusion Vision Transformer for Fine-Grained Visual Categorization

SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers

Learn to Learn Metric Space for Few-Shot Segmentation of 3D Shapes

Few-Shot Learning by Integrating Spatial and Frequency Representation

Universal Approximation for Log-concave Distributions using Well-conditioned Normalizing Flows

Automatic size and pose homogenization with spatial transformer network to improve and accelerate pediatric segmentation

Combining EfficientNet and Vision Transformers for Video Deepfake Detection

Point Cloud Registration using Representative Overlapping Points

Depth-Aware Multi-Grid Deep Homography Estimation with Contextual Correlation

Action Transformer: A Self-Attention Model for Short-Time Human Action Recognition

GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization

The Hidden Convex Optimization Landscape of Two-Layer ReLU Neural Networks: an Exact Characterization of the Optimal Solutions

TransformerFusion: Monocular RGB Scene Reconstruction using Transformers

Test-Time Personalization with a Transformer for Human Pose Estimation

Styleformer: Transformer based Generative Adversarial Networks with Style Vector

Sparse Linear Networks with a Fixed Butterfly Structure: Theory and Practice

AdaL: Adaptive Gradient Transformation Contributes to Convergences and Generalizations

Exploring Corruption Robustness: Inductive Biases in Vision Transformers and MLP-Mixers

An Efficient Cervical Whole Slide Image Analysis Framework Based on Multi-scale Semantic and Spatial Deep Features

BERT-Based Sentiment Analysis: A Software Engineering Perspective

DeformRS: Certifying Input Deformations with Randomized Smoothing

Ultrasound Video Transformers for Cardiac Ejection Fraction Estimation

Feature Encoding with AutoEncoders for Weakly-supervised Anomaly Detection

Fourier Transform Approximation as an Auxiliary Task for Image Classification

Fast Walsh-Hadamard Transform and Smooth-Thresholding Based Binary Layers in Deep Neural Networks

VideoLightFormer: Lightweight Action Recognition using Transformers

Are Convolutional Neural Networks or Transformers more like human vision?

Egocentric Image Captioning for Privacy-Preserved Passive Dietary Intake Monitoring

A Consistency-Based Loss for Deep Odometry Through Uncertainty Propagation

Scalable and Adaptive Graph Neural Networks with Self-Label-Enhanced training

E-DSSR: Efficient Dynamic Surgical Scene Reconstruction with Transformer-based Stereoscopic Depth Perception

Small in-distribution changes in 3D perspective and lighting fool both CNNs and Transformers

Challenges and Opportunities in High-dimensional Variational Inference

Evolving Metric Learning for Incremental and Decremental Features

Human Activity Recognition using Continuous Wavelet Transform and Convolutional Neural Networks

Unified Questioner Transformer for Descriptive Question Generation in Goal-Oriented Visual Dialogue

Attention-guided Progressive Mapping for Profile Face Recognition

Test-Time Adaptation to Distribution Shift by Confidence Maximization and Input Transformation

TENT: Tensorized Encoder Transformer for Temperature Forecasting

Fast computation of mutual information in the frequency domain with applications to global multimodal image alignment

Accurate Learning of Graph Representations with Graph Multiset Pooling

Complexity-based partitioning of CSFI problem instances with Transformers

Dizygotic Conditional Variational AutoEncoder for Multi-Modal and Partial Modality Absent Few-Shot Learning

Feature Combination Meets Attention: Baidu Soccer Embeddings and Transformer based Temporal Detection

Certified Robustness via Randomized Smoothing over Multiplicative Parameters

Probing Inter-modality: Visual Parsing with Self-Attention for Vision-Language Pre-training

Mitigating severe over-parameterization in deep convolutional neural networks through forced feature abstraction and compression with an entropy-based heuristic

The Story in Your Eyes: An Individual-difference-aware Model for Cross-person Gaze Estimation

SymbolicGPT: A Generative Transformer Model for Symbolic Regression

OffRoadTranSeg: Semi-Supervised Segmentation using Transformers on OffRoad environments

Minimum sharpness: Scale-invariant parameter-robustness of neural networks

Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport

A Picture May Be Worth a Hundred Words for Visual Question Answering

Countering Adversarial Examples: Combining Input Transformation and Noisy Training

GaussiGAN: Controllable Image Synthesis with 3D Gaussians from Unposed Silhouettes

Differential Morph Face Detection using Discriminative Wavelet Sub-bands

A Transformer-based Cross-modal Fusion Model with Adversarial Training for VQA Challenge 2021

Unsupervised Deep Image Stitching: Reconstructing Stitched Features to Images

Learnable Fourier Features for Multi-Dimensional Spatial Positional Encoding

IA-RED$^2$: Interpretability-Aware Redundancy Reduction for Vision Transformers

Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding

Vision Permutator: A Permutable MLP-Like Architecture for Visual Recognition

Instance-based Vision Transformer for Subtyping of Papillary Renal Cell Carcinoma in Histopathological Image

Deep Neural Network Based Respiratory Pathology Classification Using Cough Sounds

LegoFormer: Transformers for Block-by-Block Multi-view 3D Reconstruction

Towards Consistent Predictive Confidence through Fitted Ensembles

BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models

Skeleton-based Action Recognition via Spatial and Temporal Transformer Networks

Associating Objects with Transformers for Video Object Segmentation

Self-Supervised Iterative Contextual Smoothing for Efficient Adversarial Defense against Gray- and Black-Box Attack

Zero-Shot Chinese Character Recognition with Stroke-Level Decomposition

Hi-BEHRT: Hierarchical Transformer-based model for accurate prediction of clinical events using multimodal longitudinal electronic health records

Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning

Multivariate Data Explanation by Jumping Emerging Patterns Visualization

Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT

Friendly Training: Neural Networks Can Adapt Data To Make Learning Easier

3D Object Classification on Partial Point Clouds: A Practical Perspective

Solution for Large-scale Long-tailed Recognition with Noisy Labels

Practical Assessment of Generalization Performance Robustness for Deep Networks via Contrastive Examples

EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization

Group-CAM: Group Score-Weighted Visual Explanations for Deep Convolutional Networks

Cloud based Scalable Object Recognition from Video Streams using Orientation Fusion and Convolutional Neural Networks

LEGAN: Disentangled Manipulation of Directional Lighting and Facial Expressions by Leveraging Human Perceptual Judgements

Delving Deep into the Generalization of Vision Transformers under Distribution Shifts

Structured Dropout Variational Inference for Bayesian Neural Networks

Training or Architecture? How to Incorporate Invariance in Neural Networks

End-to-End 3D Point Cloud Learning for Registration Task Using Virtual Correspondences

JOKR: Joint Keypoint Representation for Unsupervised Cross-Domain Motion Retargeting

Generating Data Augmentation samples for Semantic Segmentation of Salt Bodies in a Synthetic Seismic Image Dataset

Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels

Seeing Differently, Acting Similarly: Imitation Learning with Heterogeneous Observations

Algorithm to Compilation Co-design: An Integrated View of Neural Network Sparsity

Identifiability-Guaranteed Simplex-Structured Post-Nonlinear Mixture Learning via Autoencoder

Eigen Analysis of Self-Attention and its Reconstruction from Partial Computation

Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling

Shuffle Transformer with Feature Alignment for Video Face Parsing

Discrete Auto-regressive Variational Attention Models for Text Modeling

Detection of Morphed Face Images Using Discriminative Wavelet Sub-bands

Unsupervised-learning-based method for chest MRI-CT transformation using structure constrained unsupervised generative attention networks

Selection of Source Images Heavily Influences the Effectiveness of Adversarial Attacks

Imperfect ImaGANation: Implications of GANs Exacerbating Biases on Facial Data Augmentation and Snapchat Selfie Lenses

Scene Transformer: A unified multi-task model for behavior prediction and planning

Embarrassingly parallel MCMC using deep invertible transformations

Scaling Neural Tangent Kernels via Sketching and Random Features

Phase Transitions, Distance Functions, and Implicit Neural Representations

Partial success in closing the gap between human and machine vision

2rd Place Solutions in the HC-STVG track of Person in Context Challenge 2021

Achieving Efficiency in Black Box Simulation of Distribution Tails with Self-structuring Importance Samplers

TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up

LocalTrans: A Multiscale Local Transformer Network for Cross-Resolution Homography Estimation

Robust Image Classification Using A Low-Pass Activation Function and DCT Augmentation

PVRED: A Position-Velocity Recurrent Encoder-Decoder for Human Motion Prediction

The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data

Scalable Low-Rank Tensor Learning for Spatiotemporal Traffic Data Imputation

Cycle4Completion: Unpaired Point Cloud Completion using Cycle Transformation with Missing Region Coding

Dynamic Clone Transformer for Efficient Convolutional Neural Netwoks

Quantitative Understanding of VAE as a Non-linearly Scaled Isometric Embedding

Learning disentangled representations via product manifold projection

CATE: Computation-aware Neural Architecture Encoding with Transformers

Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns

HR-NAS: Searching Efficient High-Resolution Neural Architectures with Lightweight Transformers

Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks

Hurricane Forecasting: A Novel Multimodal Machine Learning Framework

Scale-invariant scale-channel networks: Deep networks that generalise to previously unseen scales

Twins: Revisiting the Design of Spatial Attention in Vision Transformers

Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification

Generate, Annotate, and Learn: Generative Models Advance Self-Training and Knowledge Distillation

Signed Graph Metric Learning via Gershgorin Disc Perfect Alignment

Towards Real-World Blind Face Restoration with Generative Facial Prior

Domain Transformer: Predicting Samples of Unseen, Future Domains

Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning

Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images

Transformed CNNs: recasting pre-trained convolutional layers with self-attention

Align, then memorise: the dynamics of learning with feedback alignment

GBHT: Gradient Boosting Histogram Transform for Density Estimation

To The Point: Correspondence-driven monocular 3D category reconstruction

Relative Positional Encoding for Transformers with Linear Complexity

ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases

Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at Reliable OOD Detection

Chasing Sparsity in Vision Transformers: An End-to-End Exploration

Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers

Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows

Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time

On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty

All Tokens Matter: Token Labeling for Training Better Vision Transformers

Grounding inductive biases in natural images:invariance stems from variations in data

Learning normal form autoencoders for data-driven discovery of universal,parameter-dependent governing equations

ProtoRes: Proto-Residual Architecture for Deep Modeling of Human Pose

Towards Training Stronger Video Vision Transformers for EPIC-KITCHENS-100 Action Recognition

Salient Positions based Attention Network for Image Classification

A Canonical Transform for Strengthening the Local $L^p$-Type Universal Approximation Property

Self-supervision of Feature Transformation for Further Improving Supervised Learning

Self-supervised Feature Enhancement: Applying Internal Pretext Task to Supervised Learning

A Comparison for Anti-noise Robustness of Deep Learning Classification Methods on a Tiny Object Image Dataset: from Convolutional Neural Network to Visual Transformer and Performer

Ghosts in Neural Networks: Existence, Structure and Role of Infinite-Dimensional Null Space

Predicting Deep Neural Network Generalization with Perturbation Response Curves

GasHis-Transformer: A Multi-scale Visual Transformer Approach for Gastric Histopathology Image Classification

CogTree: Cognition Tree Loss for Unbiased Scene Graph Generation

Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer

Predicting Vehicles Trajectories in Urban Scenarios with Transformer Networks and Augmented Information

Rotating spiders and reflecting dogs: a class conditional approach to learning data augmentation distributions

Batch Normalization Orthogonalizes Representations in Deep Random Networks

A Runtime-Based Computational Performance Predictor for Deep Neural Network Training

Efficient Training of Visual Transformers with Small-Size Datasets

Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds

X-volution: On the unification of convolution and self-attention

DINs: Deep Interactive Networks for Neurofibroma Segmentation in Neurofibromatosis Type 1 on Whole-Body MRI

Learning to Embed Categorical Features without Embedding Tables for Recommendation

Evaluating State-of-the-Art Classification Models Against Bayes Optimality

Video Instance Segmentation using Inter-Frame Communication Transformers

A Deep Joint Sparse Non-negative Matrix Factorization Framework for Identifying the Common and Subject-specific Functional Units of Tongue Motion During Speech

SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

Constructive Universal High-Dimensional Distribution Generation through Deep ReLU Networks

Spectral Temporal Graph Neural Network for Trajectory Prediction

Relative stability toward diffeomorphisms indicates performance in deep nets

A Variational Perspective on Diffusion-Based Generative Models and Score Matching

Low-rank Characteristic Tensor Density Estimation Part I: Foundations

On the Robustness of Vision Transformers to Adversarial Examples

Increasing Depth Leads to U-Shaped Test Risk in Over-parameterized Convolutional Networks

Layered gradient accumulation and modular pipeline parallelism: fast and efficient training of large language models

A Hybrid Inference System for Improved Curvature Estimation in the Level-Set Method Using Machine Learning

A Novel Semi-supervised Framework for Call Center Agent Malpractice Detection via Neural Feature Learning

Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learning

Communication-Efficient Distributed SVD via Local Power Iterations

Empirical observations on the effects of data transformation in machine learning classification of geological domains

A Little Robustness Goes a Long Way: Leveraging Universal Features for Targeted Transfer Attacks

DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification

Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation

RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning

Image-Audio Encoding to Improve C2 Decision-Making in Multi-Domain Environment

SCTN: Sparse Convolution-Transformer Network for Scene Flow Estimation

Heterogeneous Noisy Short Signal Camouflage in Multi-Domain Environment Decision-Making

Matrix factorisation and the interpretation of geodesic distance

Assessing the Reliability of Deep Learning Classifiers Through Robustness Evaluation and Operational Profiles

When Liebig's Barrel Meets Facial Landmark Detection: A Practical Model

Human-centric Spatio-Temporal Video Grounding With Visual Transformers

TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classication

Transformation Models for Flexible Posteriors in Variational Bayes

The Care Label Concept: A Certification Suite for Trustworthy and Resource-Aware Machine Learning

Towards Efficient Cross-Modal Visual Textual Retrieval using Transformer-Encoder Deep Features

TransLoc3D : Point Cloud based Large-scale Place Recognition using Adaptive Receptive Fields

ConvTransformer: A Convolutional Transformer Network for Video Frame Synthesis

Diverse Image Inpainting with Bidirectional and Autoregressive Transformers

A general multi-modal data learning method for Person Re-identification

CVaR-based Flight Energy Risk Assessment for Multirotor UAVs using a Deep Energy Model

A Pseudo-labelling Auto-Encoder for unsupervised image classification

Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model

Not All Images are Worth 16x16 Words: Dynamic Vision Transformers with Adaptive Sequence Length

Learning curves of generic features maps for realistic datasets with a teacher-student model

VidFace: A Full-Transformer Solver for Video FaceHallucination with Unaligned Tiny Snapshots

A Protection Method of Trained CNN Model with Secret Key from Unauthorized Access

A Study On the Effects of Pre-processing On Spatio-temporal Action Recognition Using Spiking Neural Networks Trained with STDP

Federated Learning for Industrial Internet of Things in Future Industries

SVT-Net: Super Light-Weight Sparse Voxel Transformer for Large Scale Place Recognition

PatentSBERTa: A Deep NLP based Hybrid Model for Patent Distance and Classification using Augmented SBERT

Local Convolutions Cause an Implicit Bias towards High Frequency Adversarial Examples

CRT-Net: A Generalized and Scalable Framework for the Computer-Aided Diagnosis of Electrocardiogram Signals

Investigating Code-Mixed Modern Standard Arabic-Egyptian to English Machine Translation

Inertial Sensor Data To Image Encoding For Human Action Recognition

Empirical Study of Multi-Task Hourglass Model for Semantic Segmentation Task

Disentangled Face Attribute Editing via Instance-Aware Latent Space Search

The Imaginative Generative Adversarial Network: Automatic Data Augmentation for Dynamic Skeleton-Based Hand Gesture and Human Action Recognition

RSCA: Real-time Segmentation-based Context-Aware Scene Text Detection

Exploring dual information in distance metric learning for clustering

Linear Optimal Transport Embedding: Provable Wasserstein classification for certain rigid transformations and perturbations

CAP-GAN: Towards Adversarial Robustness with Cycle-consistent Attentional Purification

HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference

Incorporating Transformer and LSTM to Kalman Filter with EM algorithm for state estimation

A hybrid quantum-classical neural network with deep residual learning

AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly

Rotation invariant CNN using scattering transform for image classification

A Multi-Branch Hybrid Transformer Networkfor Corneal Endothelial Cell Segmentation

VisualSparta: An Embarrassingly Simple Approach to Large-scale Text-to-Image Search with Weighted Bag-of-words

Identity-Free Facial Expression Recognition using conditional Generative Adversarial Network

Beware the Black-Box: on the Robustness of Recent Defenses to Adversarial Examples

XGBoost energy consumption prediction based on multi-system data HVAC

An Empirical Study of Vehicle Re-Identification on the AI City Challenge

A low-rank representation for unsupervised registration of medical images

SAFIN: Arbitrary Style Transfer With Self-Attentive Factorized Instance Normalization

Explainable Health Risk Predictor with Transformer-based Medicare Claim Encoder

Tool- and Domain-Agnostic Parameterization of Style Transfer Effects Leveraging Pretrained Perceptual Metrics

High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network

Single-Layer Vision Transformers for More Accurate Early Exits with Less Overhead

Learning optimally separated class-specific subspace representations using convolutional autoencoder

img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation

Constructing fast approximate eigenspaces with application to the fast graph Fourier transforms

Only a Matter of Style: Age Transformation Using a Style-Based Regression Model

IntFormer: Predicting pedestrian intention with the aid of the Transformer architecture

Vision Transformer for Fast and Efficient Scene Text Recognition

SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Models

Understanding when spatial transformer networks do not support invariance, and what to do about it

HCRF-Flow: Scene Flow from Point Clouds with Continuous High-order CRFs and Position-aware Flow Embedding

Generating Synthetic Handwritten Historical Documents With OCR Constrained GANs

Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer

Mask-Guided Discovery of Semantic Manifolds in Generative Models

AgeFlow: Conditional Age Progression and Regression with Normalizing Flows

TabAug: Data Driven Augmentation for Enhanced Table Structure Recognition

Rethinking Skip Connection with Layer Normalization in Transformers and ResNets

FDDH: Fast Discriminative Discrete Hashing for Large-Scale Cross-Modal Retrieval

Post-processing Multi-Model Medium-Term Precipitation Forecasts Using Convolutional Neural Networks

The Location of Optimal Object Colors with More Than Two Transitions (Preprint)

Adapting deep generative approaches for getting synthetic data with realistic marginal distributions

Multi-task Graph Convolutional Neural Network for Calcification Morphology and Distribution Analysis in Mammograms

On the capacity of deep generative networks for approximating distributions

Superevents: Towards Native Semantic Segmentation for Event-based Cameras

Deep and Shallow Covariance Feature Quantization for 3D Facial Expression Recognition

PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clouds

Analysis of One-Hidden-Layer Neural Networks via the Resolvent Method

A Novel Transformer based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images

BikNN: Anomaly Estimation in Bilateral Domains with k-Nearest Neighbors

A Feature Fusion-Net Using Deep Spatial Context Encoder and Nonstationary Joint Statistical Model for High Resolution SAR Image Classification

Local Frequency Domain Transformer Networks for Video Prediction

Deep Neural Networks as Point Estimates for Deep Gaussian Processes

RelationTrack: Relation-aware Multiple Object Tracking with Decoupled Representation

Event-LSTM: An Unsupervised and Asynchronous Learning-based Representation for Event-based Data

Unsupervised Human Pose Estimation through Transforming Shape Templates

Matching Visual Features to Hierarchical Semantic Topics for Image Paragraph Captioning

Improving Transformation-based Defenses against Adversarial Examples with First-order Perturbations

Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification

Trajectory Prediction for Autonomous Driving with Topometric Map

Tensor Programs IIb: Architectural Universality of Neural Tangent Kernel Training Dynamics

Human-Aided Saliency Maps Improve Generalization of Deep Learning

Autoencoder Based Inter-Vehicle Generalization for In-Cabin Occupant Classification

Laplace Matching for fast Approximate Inference in Generalized Linear Models

LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference

Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet

CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints

Attention for Image Registration (AiR): an unsupervised Transformer approach

Proposal-free One-stage Referring Expression via Grid-Word Cross-Attention

Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet Autoencoder

Sequential Encryption of Sparse Neural Networks Toward Optimum Representation of Irregular Sparsity

TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval

Efficient Semantic Image Synthesis via Class-Adaptive Normalization

Nonparametric Trace Regression in High Dimensions via Sign Series Representation

Texture for Colors: Natural Representations of Colors Using Variable Bit-Depth Textures

ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing

Moving Towards Centers: Re-ranking with Attention and Memory for Re-identification

From the Expectation Maximisation Algorithm to Autoencoded Variational Bayes

Deep Manifold Transformation for Nonlinear Dimensionality Reduction

CorrNet3D: Unsupervised End-to-end Learning of Dense Correspondence for 3D Point Clouds

Cloud Transformers: A Universal Approach To Point Cloud Processing Tasks

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Anatomy-Guided Parallel Bottleneck Transformer Network for Automated Evaluation of Root Canal Therapy

Stochastic Mutual Information Gradient Estimation for Dimensionality Reduction Networks

Explaining a Series of Models by Propagating Local Feature Attributions

Self-supervised Augmentation Consistency for Adapting Semantic Segmentation

Randomized Histogram Matching: A Simple Augmentation for Unsupervised Domain Adaptation in Overhead Imagery

Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation

An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering

Chop Chop BERT: Visual Question Answering by Chopping VisualBERT's Heads

HandsFormer: Keypoint Transformer for Monocular 3D Pose Estimation ofHands and Object in Interaction

A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection

Using Adaptive Gradient for Texture Learning in Single-View 3D Reconstruction

Locality Constrained Analysis Dictionary Learning via K-SVD Algorithm

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning

Semantic Consistency and Identity Mapping Multi-Component Generative Adversarial Network for Person Re-Identification

Segmentation-Based Bounding Box Generation for Omnidirectional Pedestrian Detection

DCT-Mask: Discrete Cosine Transform Mask Representation for Instance Segmentation

Structured Sparse Non-negative Matrix Factorization with L20-Norm for scRNA-seq Data Analysis

MDETR -- Modulated Detection for End-to-End Multi-Modal Understanding

Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays

RelTransformer: Balancing the Visual Relationship Detection from Local Context, Scene and Memory

Fourier-based and Rational Graph Filters for Spectral Processing

A Framework for Unsupervised Classificiation and Data Mining of Tweets about Cyber Vulnerabilities

Efficient and Model-Based Infrared and Visible Image Fusion Via Algorithm Unrolling

DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning

On Geodesic Distances and Contextual Embedding Compression for Text Classification

Equivariant Wavelets: Fast Rotation and Translation Invariant Wavelet Scattering Transforms

Robust 360-8PA: Redesigning The Normalized 8-point Algorithm for 360-FoV Images

Clustering Introductory Computer Science Exercises Using Topic Modeling Methods

From a Fourier-Domain Perspective on Adversarial Examples to a Wiener Filter Defense for Semantic Segmentation

Discrete-continuous Action Space Policy Gradient-based Attention for Image-Text Matching

SRWarp: Generalized Image Super-Resolution under Arbitrary Transformation

Neural Networks for Learning Counterfactual G-Invariances from Single Environments

VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization

Estimating Traffic Speeds using Probe Data: A Deep Neural Network Approach

Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning

Restoration of Video Frames from a Single Blurred Image with Motion Understanding

Supervised deep learning of elastic SRV distances on the shape space of curves

Multimodal Deception Detection in Videos via Analyzing Emotional State-based Feature

Learning from Subjective Ratings Using Auto-Decoded Deep Latent Embeddings

Locally Aware Piecewise Transformation Fields for 3D Human Mesh Registration

Orthogonal Features Based EEG Signals Denoising Using Fractional and Compressed One-Dimensional CNN AutoEncoder

RobustPointSet: A Dataset for Benchmarking Robustness of Point Cloud Classifiers

Skeletal Feature Compensation for Imitation Learning with Embodiment Mismatch

Semisupervised Manifold Alignment of Multimodal Remote Sensing Images

PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layers

TransRPPG: Remote Photoplethysmography Transformer for 3D Mask Face Presentation Attack Detection

Multilingual Multimodal Pre-training for Zero-Shot Cross-Lingual Transfer of Vision-Language Models

Change Detection in Synthetic Aperture Radar Images Using a Dual-Domain Network

Generation of Virtual Dual Energy Images from Standard Single-Shot Radiographs using Multi-scale and Conditional Adversarial Network

Discrete Cosine Transform Network for Guided Depth Map Super-Resolution

A Biologically Interpretable Two-stage Deep Neural Network (BIT-DNN) For Vegetation Recognition From Hyperspectral Imagery

Dewarping Document Image By Displacement Flow Estimation with Fully Convolutional Network

Weakly But Deeply Supervised Occlusion-Reasoned Parametric Layouts

A Semi-Supervised Classification Method of Apicomplexan Parasites and Host Cell Using Contrastive Learning Strategy

UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-identification

Recurrent Multi-view Alignment Network for Unsupervised Surface Registration

Simpler Certified Radius Maximization by Propagating Covariances

Unsupervised Point Cloud Pre-Training via View-Point Occlusion, Completion

Graph matching between bipartite and unipartite networks: to collapse, or not to collapse, that is the question

Unsupervised Lane-Change Identification for On-Ramp Merge Analysis in Naturalistic Driving Data

Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation

RPSRNet: End-to-End Trainable Rigid Point Set Registration Network using Barnes-Hut $2^D$-Tree Representation

CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities

A Learnable Self-supervised Task for Unsupervised Domain Adaptation on Point Clouds

Local-HDP: Interactive Open-Ended 3D Object Categorization in Real-Time Robotic Scenarios

Description of Structural Biases and Associated Data in Sensor-Rich Environments

SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration

Deep learning based registration using spatial gradients and noisy segmentation labels

Piracy-Resistant DNN Watermarking by Block-Wise Image Transformation with Secret Key

SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size

SNARF: Differentiable Forward Skinning for Animating Non-Rigid Neural Implicit Shapes

Affine-modeled video extraction from a single motion blurred image

SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks

Deep Monocular 3D Human Pose Estimation via Cascaded Dimension-Lifting

Born Identity Network: Multi-way Counterfactual Map Generation to Explain a Classifier's Decision

DeepI2P: Image-to-Point Cloud Registration via Deep Classification

Attribute-Guided Adversarial Training for Robustness to Natural Perturbations

InverseForm: A Loss Function for Structured Boundary-Aware Segmentation

MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition

Point2Skeleton: Learning Skeletal Representations from Point Clouds

Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units

Facial Attribute Transformers for Precise and Robust Makeup Transfer

Deep Transformers for Fast Small Intestine Grounding in Capsule Endoscope Video

Lattice-Free MMI Adaptation Of Self-Supervised Pretrained Acoustic Models

Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression

Understanding Medical Conversations: Rich Transcription, Confidence Scores & Information Extraction

HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimation

A Video Is Worth Three Views: Trigeminal Transformers for Video-based Person Re-identification

Double-Adversarial Activation Anomaly Detection: Adversarial Autoencoders are Anomaly Generators

Augmented Equivariant Attention Networks for Microscopy Image Reconstruction

Aggregated Contextual Transformations for High-Resolution Image Inpainting

M-Evolve: Structural-Mapping-Based Data Augmentation for Graph Classification

Deepfake Detection Scheme Based on Vision Transformer and Distillation

TransMOT: Spatial-Temporal Graph Transformer for Multiple Object Tracking

Bayesian Structural Learning for an Improved Diagnosis of Cyber-Physical Systems

Augmented Skeleton Based Contrastive Action Learning with Momentum LSTM for Unsupervised Action Recognition

Reconciling the Discrete-Continuous Divide: Towards a Mathematical Theory of Sparse Communication

ProcessTransformer: Predictive Business Process Monitoring with Transformer Network

A Federated Learning Framework for Smart Grids: Securing Power Traces in Collaborative Learning

TrajeVAE -- Controllable Human Motion Generation from Trajectories

Image-Based Place Recognition on Bucolic Environment Across Seasons From Semantic Edge Description

DF^2AM: Dual-level Feature Fusion and Affinity Modeling for RGB-Infrared Cross-modality Person Re-identification

Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning

Convolutional Dynamic Alignment Networks for Interpretable Classifications

Layout-Guided Novel View Synthesis from a Single Indoor Panorama

Generating Multi-scale Maps from Remote Sensing Images via Series Generative Adversarial Networks

Fast and Robust Matching for Multimodal Remote Sensing Image Registration

RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation

PointShuffleNet: Learning Non-Euclidean Features with Homotopy Equivalence and Mutual Information

A Closer Look at the Robustness of Vision-and-Language Pre-trained Models

Thinking Fast and Slow: Efficient Text-to-Visual Retrieval with Transformers

SD-6DoF-ICLK: Sparse and Deep Inverse Compositional Lucas-Kanade Algorithm on SE(3)

Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training

Beltrami Signature: A Novel Invariant 2D Shape Representation for Object Classification

Generalized Organ Segmentation by Imitating One-shot Reasoning using Anatomical Correlation

Learning Parallel Dense Correspondence from Spatio-Temporal Descriptors for Efficient and Robust 4D Reconstruction

Q-NET: A Network for Low-Dimensional Integrals of Neural Proxies

Joint Generative and Contrastive Learning for Unsupervised Person Re-identification

Augmented Transformer with Adaptive Graph for Temporal Action Proposal Generation

Self-supervised Image-text Pre-training With Mixed Data In Chest X-rays

TransFill: Reference-guided Image Inpainting by Merging Multiple Color and Spatial Transformations

Domain-robust VQA with diverse datasets and methods but no target labels

Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases

AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation

Distilling a Powerful Student Model via Online Knowledge Distillation

Transitive Learning: Exploring the Transitivity of Degradations for Blind Super-Resolution

A Low-cost Fault Corrector for Deep Neural Networks through Range Restriction

SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation

Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation

Privacy-preserving Collaborative Learning with Automatic Transformation Search

TransFG: A Transformer Architecture for Fine-grained Recognition

Looking Beyond Two Frames: End-to-End Multi-Object Tracking Using Spatial and Temporal Transformers

Learning Efficient Photometric Feature Transform for Multi-view Stereo

Understanding Robustness of Transformers for Image Classification

Model-based Reconstruction with Learning: From Unsupervised to Supervised and Beyond

GraphSpeech: Syntax-Aware Graph Attention Network For Neural Speech Synthesis

Spectrally-Encoded Single-Pixel Machine Vision Using Diffractive Networks

Inductive Mutual Information Estimation: A Convex Maximum-Entropy Copula Approach

Boosting Binary Masks for Multi-Domain Learning through Affine Transformations

On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines

Efficient Feature Transformations for Discriminative and Generative Continual Learning

Recovery of Joint Probability Distribution from one-way marginals: Low rank Tensors and Random Projections

Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning

Hetero-Modal Learning and Expansive Consistency Constraints for Semi-Supervised Detection from Multi-Sequence Data

BoXHED 2.0: Scalable boosting of functional data in survival analysis

$\mathcal{G}$-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space

IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression

An Efficient Shared-memory Parallel Sinkhorn-Knopp Algorithm to Compute the Word Mover's Distance

3D Reconstruction and Alignment by Consumer RGB-D Sensors and Fiducial Planar Markers for Patient Positioning in Radiation Therapy

Combining Ensembles and Data Augmentation can Harm your Calibration

Fast Approximate Spectral Normalization for Robust Deep Neural Networks

Hardware Acceleration of Explainable Machine Learning using Tensor Processing Units

Retrieve Fast, Rerank Smart: Cooperative and Joint Approaches for Improved Cross-Modal Retrieval

What and Where: Modeling Skeletons from Semantic and Spatial Perspectives for Action Recognition

Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

Brain Image Synthesis with Unsupervised Multivariate Canonical CSC$\ell_4$Net

Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs

Adjoint Rigid Transform Network: Task-conditioned Alignment of 3D Shapes

Privacy-Preserving Deep Action Recognition: An Adversarial Learning Framework and A New Dataset

Confidence-aware Non-repetitive Multimodal Transformers for TextCaps

Progressive Semantic-Aware Style Transformation for Blind Face Restoration

Paying Attention to Multiscale Feature Maps in Multimodal Image Matching

3DMNDT:3D multi-view registration method based on the normal distributions transform

Classification of Motor Imagery EEG Signals by Using a Divergence Based Convolutional Neural Network

Enhancing Robustness of On-line Learning Models on Highly Noisy Data

Hexagonal Image Processing in the Context of Machine Learning: Conception of a Biologically Inspired Hexagonal Deep Learning Framework

Stochastic Security: Adversarial Defense Using Long-Run Dynamics of Energy-Based Models

Unsupervised Doppler Radar-Based Activity Recognition for e-healthcare

PC-HMR: Pose Calibration for 3D Human Mesh Recovery from 2D Images/Videos

The Case for High-Accuracy Classification: Think Small, Think Many!

Focal Inverse Distance Transform Maps for Crowd Localization and Counting in Dense Crowd

Look, Cast and Mold: Learning 3D Shape Manifold from Single-view Synthetic Data

Generating Adversarial Computer Programs using Optimized Obfuscations

The Geometry of Deep Generative Image Models and its Applications

Enhancing Transformer for Video Understanding Using Gated Multi-Level Attention and Temporal Adversarial Training

DAFAR: Defending against Adversaries by Feedback-Autoencoder Reconstruction

Fourier Transform of Percoll Gradients Boosts CNN Classification of Hereditary Hemolytic Anemias

Incorporating Symmetry into Deep Dynamics Models for Improved Generalization

Knowledge driven Description Synthesis for Floor Plan Interpretation

GRIHA: Synthesizing 2-Dimensional Building Layouts from Images Captured using a Smart Phone

R-PointHop: A Green, Accurate and Unsupervised Point Cloud Registration Method

Towards Generalizable and Robust Face Manipulation Detection via Bag-of-local-feature

Principled Ultrasound Data Augmentation for Classification of Standard Planes

A Better Alternative to Error Feedback for Communication-Efficient Distributed Learning

A Novel Visualization System of Using Augmented Reality in Knee Replacement Surgery: Enhanced Bidirectional Maximum Correntropy Algorithm

Generating Unrestricted Adversarial Examples via Three Parameters

Learning Defense Transformers for Counterattacking Adversarial Examples

Machine Learning Assisted Orthonormal Basis Selection for Functional Data Analysis

Network Bending: Expressive Manipulation of Deep Generative Models

Learning Long-Term Style-Preserving Blind Video Temporal Consistency

AutoDO: Robust AutoAugment for Biased Data with Label Noise via Scalable Probabilistic Implicit Differentiation

Continuous 3D Multi-Channel Sign Language Production via Progressive Transformers and Mixture Density Networks

On Improving Deep Learning Trace Analysis with System Call Arguments

For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash Functions

BODAME: Bilevel Optimization for Defense Against Model Extraction

Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies

CreativeGAN: Editing Generative Adversarial Networks for Creative Design Synthesis

Isometric Transformation Invariant and Equivariant Graph Convolutional Networks

Multi-Pretext Attention Network for Few-shot Learning with Self-supervision

Face Frontalization Based on Robustly Fitting a Deformable Shape Model to 3D Landmarks

TransMed: Transformers Advance Multi-modal Medical Image Classification

TOAN: Target-Oriented Alignment Network for Fine-Grained Image Categorization with Few Labeled Samples

PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency

QPIC: Query-Based Pairwise Human-Object Interaction Detection with Image-Wide Contextual Information

Enhancing Medical Image Registration via Appearance Adjustment Networks

Generative Transition Mechanism to Image-to-Image Translation via Encoded Transformation

Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining

Efficient Causal Inference from Combined Observational and Interventional Data through Causal Reductions

Fully Convolutional Geometric Features for Category-level Object Alignment

Pose Discrepancy Spatial Transformer Based Feature Disentangling for Partial Aspect Angles SAR Target Recognition

Detecting Adversarial Examples from Sensitivity Inconsistency of Spatial-Transform Domain

Robust Point Cloud Registration Framework Based on Deep Graph Matching

DiffPrune: Neural Network Pruning with Deterministic Approximate Binary Gates and $L_0$ Regularization

Perspectives and Prospects on Transformer Architecture for Cross-Modal Tasks with Language and Vision

On the mapping between Hopfield networks and Restricted Boltzmann Machines

DyCo3D: Robust Instance Segmentation of 3D Point Clouds through Dynamic Convolution

Analytical Characterization and Design Space Exploration for Optimization of CNNs

OperA: Attention-Regularized Transformers for Surgical Phase Recognition

Attention is Not All You Need: Pure Attention Loses Rank Doubly Exponentially with Depth

BiTe-GCN: A New GCN Architecture via BidirectionalConvolution of Topology and Features on Text-Rich Networks

Learning High Fidelity Depths of Dressed Humans by Watching Social Media Dance Videos

VIVO: Visual Vocabulary Pre-Training for Novel Object Captioning

Single-View 3D Object Reconstruction from Shape Priors in Memory

Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework

Information Bottleneck Constrained Latent Bidirectional Embedding for Zero-Shot Learning

Dynamic Fusion Module Evolves Drivable Area and Road Anomaly Detection: A Benchmark and Algorithms

A Mathematical Principle of Deep Learning: Learn the Geodesic Curve in the Wasserstein Space

When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework

Fine-grained Visual Textual Alignment for Cross-Modal Retrieval using Transformer Encoders

Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation

Graph Information Vanishing Phenomenon inImplicit Graph Neural Networks

A HINT from Arithmetic: On Systematic Generalization of Perception, Syntax, and Semantics

Coordination Among Neural Modules Through a Shared Global Workspace

Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC

Detection and Rectification of Arbitrary Shaped Scene Texts by using Text Keypoints and Links

Dictionary Learning with Low-rank Coding Coefficients for Tensor Completion

Fast Symmetric Diffeomorphic Image Registration with Convolutional Neural Networks

Transformers with Competitive Ensembles of Independent Mechanisms

Generative chemical transformer: attention makes neural machine learn molecular geometric structures via text

Knowledge Distillation Circumvents Nonlinearity for Optical Convolutional Neural Networks

Class Knowledge Overlay to Visual Feature Learning for Zero-Shot Image Classification

A Reconfigurable Winograd CNN Accelerator with Nesting Decomposition Algorithm for Computing Convolution with Large Filters

Partitioning signal classes using transport transforms for data analysis and machine learning

Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care Unit

Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration

Learning unbiased group-wise registration (LUGR) and joint segmentation: evaluation on longitudinal diffusion MRI

On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness

Image Captioning using Deep Stacked LSTMs, Contextual Word Embeddings and Data Augmentation

Contour Loss for Instance Segmentation via k-step Distance Transformation Image

Dissecting the Diffusion Process in Linear Graph Convolutional Networks

Improving Action Quality Assessment using ResNets and Weighted Aggregation

Learning Deep Features for Shape Correspondence with Domain Invariance

Towards Accurate and Compact Architectures via Neural Architecture Transformer

Point Transformer for Shape Classification and Retrieval of 3D and ALS Roof PointClouds

FAT: Learning Low-Bitwidth Parametric Representation via Frequency-Aware Transformation

Adaptable Deformable Convolutions for Semantic Segmentation of Fisheye Images in Autonomous Driving Systems

StickyPillars: Robust and Efficient Feature Matching on Point Clouds using Graph Neural Networks

A Deep Graph Wavelet Convolutional Neural Network for Semi-supervised Node Classification

Ridge Regression with Over-Parametrized Two-Layer Networks Converge to Ridgelet Spectrum

Quantum spectral analysis: frequency in time, with applications to signal and image processing

Modelling Paralinguistic Properties in Conversational Speech to Detect Bipolar Disorder and Borderline Personality Disorder

Online Learning via Offline Greedy Algorithms: Applications in Market Design and Optimization

Domain Adaptive Learning Based on Sample-Dependent and Learnable Kernels

Improved Point Transformation Methods For Self-Supervised Depth Prediction

Distributed Algorithms for Linearly-Solvable Optimal Control in Networked Multi-Agent Systems

CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices

GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training

A Sub-band Approach to Deep Denoising Wavelet Networks and a Frequency-adaptive Loss for Perceptual Quality

A Survey of Machine Learning for Computer Architecture and Systems

The gap between theory and practice in function approximation with deep neural networks

Using Data Assimilation to Train a Hybrid Forecast System that Combines Machine-Learning and Knowledge-Based Components

Modeling of Spatio-Temporal Hawkes Processes with Randomized Kernels

Image Captioning using Multiple Transformers for Self-Attention Mechanism

Neural Architecture Search as Program Transformation Exploration

PipeTransformer: Automated Elastic Pipelining for Distributed Training of Transformers

Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networks

CHEETAH: An Ultra-Fast, Approximation-Free, and Privacy-Preserved Neural Network Framework based on Joint Obscure Linear and Nonlinear Computations

More Is More -- Narrowing the Generalization Gap by Adding Classification Heads

Exploring Contrastive Learning in Human Activity Recognition for Healthcare

Development of Crop Yield Estimation Model using Soil and Environmental Parameters

Addressing the Topological Defects of Disentanglement via Distributed Operators

On Theory-training Neural Networks to Infer the Solution of Highly Coupled Differential Equations

Using Deep LSD to build operators in GANs latent space with meaning in real space

Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures

Learning Unsupervised Cross-domain Image-to-Image Translation Using a Shared Discriminator

ABCDP: Approximate Bayesian Computation with Differential Privacy

Curse of Dimensionality for TSK Fuzzy Neural Networks: Explanation and Solutions

A Convergence Theory Towards Practical Over-parameterized Deep Neural Networks

Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU

Interpretable Neural Networks based classifiers for categorical inputs

Modeling Text with Decision Forests using Categorical-Set Splits

Regularization for convolutional kernel tensors to avoid unstable gradient problem in convolutional neural networks

FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning

MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records

OPAM: Online Purchasing-behavior Analysis using Machine learning

Deep Attentive Study Session Dropout Prediction in Mobile Learning Environment

EnAET: A Self-Trained framework for Semi-Supervised and Supervised Learning with Ensemble Transformations

Scaling Federated Learning for Fine-tuning of Large Language Models

Dynamic Texture Recognition via Nuclear Distances on Kernelized Scattering Histogram Spaces

Characterizing and comparing external measures for the assessment of cluster analysis and community detection

Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing

Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network

A fast method for simultaneous reconstruction and segmentation in X-ray CT application

VX2TEXT: End-to-End Learning of Video-Based Text Generation From Multimodal Inputs

BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data

PIG-Net: Inception based Deep Learning Architecture for 3D Point Cloud Segmentation

An explainable Transformer-based deep learning model for the prediction of incident heart failure

Homogeneous Vector Capsules Enable Adaptive Gradient Descent in Convolutional Neural Networks

Transformer Reasoning Network for Image-Text Matching and Retrieval

Hybrid Trilinear and Bilinear Programming for Aligning Partially Overlapping Point Sets

Weakly Supervised Thoracic Disease Localization via Disease Masks

MathNet: Haar-Like Wavelet Multiresolution-Analysis for Graph Representation and Learning

Group-based Learning of Disentangled Representations with Generalizability for Novel Contents

Texture image classification based on a pseudo-parabolic diffusion model

Fixed Viewpoint Mirror Surface Reconstruction under an Uncalibrated Camera

A Convenient Infinite Dimensional Framework for Generative Adversarial Learning

Interpretable, similarity-driven multi-view embeddings from high-dimensional biomedical data

Generative Autoencoder Kernels on Deep Learning for Brain Activity Analysis

Low-Rank Tensor Recovery with Euclidean-Norm-Induced Schatten-p Quasi-Norm Regularization

Aesthetics, Personalization and Recommendation: A survey on Deep Learning in Fashion

A Similarity Measure of Gaussian Process Predictive Distributions

Hyperspectral Image Restoration via Multi-mode and Double-weighted Tensor Nuclear Norm Minimization

Latent Fingerprint Registration via Matching Densely Sampled Points

Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula

Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction

Resolution-invariant Person ReID Based on Feature Transformation and Self-weighted Attention

Dealing with Nuisance Parameters using Machine Learning in High Energy Physics: a Review

PolyTransform: Deep Polygon Transformer for Instance Segmentation

ACP: Automatic Channel Pruning via Clustering and Swarm Intelligence Optimization for CNN

LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning

A Novel Prediction Approach for Exploring PM2.5 Spatiotemporal Propagation Based on Convolutional Recursive Neural Networks

Training data-efficient image transformers & distillation through attention

Reasoning over Vision and Language: Exploring the Benefits of Supplemental Knowledge

Neuron Linear Transformation: Modeling the Domain Shift for Crowd Counting

Pose Augmentation: Class-agnostic Object Pose Transformation for Object Recognition

Telling BERT's full story: from Local Attention to Global Aggregation

Evaluating Deep Learning Approaches for Covid19 Fake News Detection

Explicit homography estimation improves contrastive self-supervised learning

Random Transformation of Image Brightness for Adversarial Attack

ProLab: perceptually uniform projective colour coordinate system

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

Individual Mobility Prediction: An Interpretable Activity-based Hidden Markov Approach

A Framework for Assurance of Medication Safety using Machine Learning

Investigating the Vision Transformer Model for Image Retrieval Tasks

Understanding Implicit Regularization in Over-Parameterized Nonlinear Statistical Model

Consistency Regularization for Certified Robustness of Smoothed Classifiers

Spatial Information Guided Convolution for Real-Time RGBD Semantic Segmentation

Bridging In- and Out-of-distribution Samples for Their Better Discriminability

Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate

SLAP: Improving Physical Adversarial Examples with Short-Lived Adversarial Perturbations

Adversarial Robustness by Design through Analog Computing and Synthetic Gradients

A Loss Function for Generative Neural Networks Based on Watson's Perceptual Model

Weighting-Based Treatment Effect Estimation via Distribution Learning

AutoDropout: Learning Dropout Patterns to Regularize Deep Networks

Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps

Identifying centres of interest in paintings using alignment and edge detection: Case studies on works by Luc Tuymans

Deep Feature Space Trojan Attack of Neural Networks by Controlled Detoxification

Learning Neural Networks on SVD Boosted Latent Spaces for Semantic Classification

Uncertainty-sensitive Activity Recognition: a Reliability Benchmark and the CARING Models

A Robust Color Edge Detection Algorithm Based on Quaternion Hardy Filter

Deep Preset: Blending and Retouching Photos with Color Style Transfer

The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimation

Rethinking Road Surface 3D Reconstruction and Pothole Detection: From Perspective Transformation to Disparity Map Segmentation

Sparse encoding for more-interpretable feature-selecting representations in probabilistic matrix factorization

Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations

Self-Supervised Human Activity Recognition by Augmenting Generative Adversarial Networks

Context-Aware Personality Inference in Dyadic Scenarios: Introducing the UDIVA Dataset

Deep Learning Framework Applied for Predicting Anomaly of Respiratory Sounds

Adaptively Solving the Local-Minimum Problem for Deep Neural Networks

SPIN: Structure-Preserving Inner Offset Network for Scene Text Recognition

Convolutional Neural Network for Elderly Wandering Prediction in Indoor Scenarios

MG-SAGC: A multiscale graph and its self-adaptive graph convolution network for 3D point clouds

Adaptive Exploitation of Pre-trained Deep Convolutional Neural Networks for Robust Visual Tracking

Gaussian Process Regression constrained by Boundary Value Problems

Towards an Automatic System for Extracting Planar Orientations from Software Generated Point Clouds

Predicting the Critical Number of Layers for Hierarchical Support Vector Regression

Cross-modal Retrieval and Synthesis (X-MRS): Closing the modality gap in shared subspace

SENTRY: Selective Entropy Optimization via Committee Consistency for Unsupervised Domain Adaptation

A Fast Graph Neural Network-Based Method for Winner Determination in Multi-Unit Combinatorial Auctions

Variational Autoencoders and Nonlinear ICA: A Unifying Framework

KRISP: Integrating Implicit and Symbolic Knowledge for Open-Domain Knowledge-Based VQA

Early Bird: Loop Closures from Opposing Viewpoints for Perceptually-Aliased Indoor Environments

$O(n)$ Connections are Expressive Enough: Universal Approximability of Sparse Transformers

Transformation-based Adversarial Video Prediction on Large-Scale Data

Artificial Neural Networks to Impute Rounded Zeros in Compositional Data

End-to-end Deep Object Tracking with Circular Loss Function for Rotated Bounding Box

A fully pipelined FPGA accelerator for scale invariant feature transform keypoint descriptor matching,

On the Limitations of Denoising Strategies as Adversarial Defenses

Image Quality Assessment: Unifying Structure and Texture Similarity

On $O( \max \{n_1, n_2 \}\log ( \max \{ n_1, n_2 \} n_3) )$ Sample Entries for $n_1 \times n_2 \times n_3$ Tensor Completion via Unitary Transformation

Canny-VO: Visual Odometry with RGB-D Cameras based on Geometric 3D-2D Edge Alignment

Policy Manifold Search for Improving Diversity-based Neuroevolution

The Monte Carlo Transformer: a stochastic self-attention model for sequence prediction

SSD-GAN: Measuring the Realness in the Spatial and Spectral Domains

Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback

Articulated Shape Matching Using Laplacian Eigenfunctions and Unsupervised Point Registration

INSPIRE: Intensity and Spatial Information-Based Deformable Image Registration

CoShaRP: A Convex Program for Single-shot Tomographic Shape Sensing

Improving Image Captioning by Leveraging Intra- and Inter-layer Global Representation in Transformer Network

On the achievability of blind source separation for high-dimensional nonlinear source mixtures

Effective multi-view registration of point sets based on student's t mixture model

Exploiting Local Indexing and Deep Feature Confidence Scores for Fast Image-to-Video Search

Physics-Informed Machine Learning Simulator for Wildfire Propagation

Interpreting Deep Neural Networks with Relative Sectional Propagation by Analyzing Comparative Gradients and Hostile Activations

Learning Consistent Deep Generative Models from Sparse Data via Prediction Constraints

TabTransformer: Tabular Data Modeling Using Contextual Embeddings

Disentangling images with Lie group transformations and sparse coding

A New Neural Network Architecture Invariant to the Action of Symmetry Subgroups

Spatial Temporal Transformer Network for Skeleton-based Action Recognition

We Learn Better Road Pothole Detection: from Attention Aggregation to Adversarial Domain Adaptation

Learning Edge-Preserved Image Stitching from Large-Baseline Deep Homography

Multi-Model Learning for Real-Time Automotive Semantic Foggy Scene Understanding via Domain Adaptation

Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps

Contrastive Transformation for Self-supervised Correspondence Learning

Inference of Stochastic Dynamical Systems from Cross-Sectional Population Data

Lipschitz Regularized CycleGAN for Improving Semantic Robustness in Unpaired Image-to-image Translation

Warped Gaussian Processes in Remote Sensing Parameter Estimation and Causal Inference

Transformer Guided Geometry Model for Flow-Based Unsupervised Visual Odometry

Performance Analysis of Keypoint Detectors and Binary Descriptors Under Varying Degrees of Photometric and Geometric Transformations

GenScan: A Generative Method for Populating Parametric 3D Scan Datasets

IHashNet: Iris Hashing Network based on efficient multi-index hashing

Computing flood probabilities using Twitter: application to the Houston urban area during Harvey

Spectral band selection for vegetation properties retrieval using Gaussian processes regression

Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks

Spatially-Adaptive Pixelwise Networks for Fast Image Translation

Cosine-Pruned Medial Axis: A new method for isometric equivariant and noise-free medial axis extraction

Evolutionary NAS with Gene Expression Programming of Cellular Encoding

Semi-Supervised Learning for Multi-Task Scene Understanding by Neural Graph Consensus

Towards Defending Multiple Adversarial Perturbations via Gated Batch Normalization

Deep Semantic Parsing of Freehand Sketches with Homogeneous Transformation, Soft-Weighted Loss, and Staged Learning

TRACE: Early Detection of Chronic Kidney Disease Onset with Transformer-Enhanced Feature Embedding

Active Learning for Video Description With Cluster-Regularized Ensemble Ranking

Increased performance in DDM analysis by calculating structure functions through Fourier transform in time

Contour Transformer Network for One-shot Segmentation of Anatomical Structures

Aligning Hyperbolic Representations: an Optimal Transport-based approach

A compact sequence encoding scheme for online human activity recognition in HRI applications

Towards a Kernel based Uncertainty Decomposition Framework for Data and Models

Concentration bounds for linear Monge mapping estimation and optimal transport domain adaptation

Revisiting Unsupervised Meta-Learning: Amplifying or Compensating for the Characteristics of Few-Shot Tasks

Dynamic Image for 3D MRI Image Alzheimer's Disease Classification

Flood Detection via Twitter Streams using Textual and Visual Features

Deterministic Certification to Adversarial Attacks via Bernstein Polynomial Approximation

Generalized Pose-and-Scale Estimation using 4-Point Congruence Constraints

LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis

Robust Attacks on Deep Learning Face Recognition in the Physical World

Everybody Sign Now: Translating Spoken Language to Photo Realistic Sign Language Video

Quantifying and Learning Disentangled Representations with Limited Supervision

Deep Convolutional Neural Networks: A survey of the foundations, selected improvements, and some current applications

Information Theory Measures via Multidimensional Gaussianization

Scattering Transform Based Image Clustering using Projection onto Orthogonal Complement

SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks

CAFE-GAN: Arbitrary Face Attribute Editing with Complementary Attention Feature

Discovering Causal Structure with Reproducing-Kernel Hilbert Space $ε$-Machines

Learnable Gabor modulated complex-valued networks for orientation robustness

A Learning-based Optimization Algorithm:Image Registration Optimizer Network

Detection and Classification of mental illnesses on social media using RoBERTa

Radon cumulative distribution transform subspace modeling for image classification

Three-Dimensional Fourier Scattering Transform and Classification of Hyperspectral Images

Integrating Multimodal Information in Large Pretrained Transformers

DeepPhaseCut: Deep Relaxation in Phase for Unsupervised Fourier Phase Retrieval

Attention-Based Transformers for Instance Segmentation of Cells in Microstructures

Visual Transformers: Token-based Image Representation and Processing for Computer Vision

Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins?

Convolutional Autoencoder for Blind Hyperspectral Image Unmixing

RSINet: Rotation-Scale Invariant Network for Online Visual Tracking

A sparse code increases the speed and efficiency of neuro-dynamic programming for optimal control tasks with correlated inputs

Semi-supervised Learning of Galaxy Morphology using Equivariant Transformer Variational Autoencoders

Learning color space adaptation from synthetic to real images of cirrus clouds

Ensemble of Models Trained by Key-based Transformed Images for Adversarially Robust Defense Against Black-box Attacks

SoftFlow: Probabilistic Framework for Normalizing Flow on Manifolds

Towards transformation-resilient provenance detection of digital media

Reducing Inference Latency with Concurrent Architectures for Image Recognition

Rank consistent ordinal regression for neural networks with application to age estimation

Predicting Length of Stay in the Intensive Care Unit with Temporal Pointwise Convolutional Networks

Adversarial Robustness Against Image Color Transformation within Parametric Filter Space

Statistical stability indices for LIME: obtaining reliable explanations for Machine Learning models

Tensor Canonical Correlation Analysis with Convergence and Statistical Guarantees

Linear Dilation-Erosion Perceptron Trained Using a Convex-Concave Procedure

Learned Equivariant Rendering without Transformation Supervision

DeepSim: Semantic similarity metrics for learned image registration

Invariant Deep Compressible Covariance Pooling for Aerial Scene Categorization

FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification

A novel method for Causal Structure Discovery from EHR data, a demonstration on type-2 diabetes mellitus

A New Framework for Registration of Semantic Point Clouds from Stereo and RGB-D Cameras

Learning GPLVM with arbitrary kernels using the unscented transformation

HyperCon: Image-To-Video Model Transfer for Video-To-Video Translation Tasks

Learning Data Augmentation with Online Bilevel Optimization for Image Classification

Point Cloud Registration Based on Consistency Evaluation of Rigid Transformation in Parameter Space

DeConFuse : A Deep Convolutional Transform based Unsupervised Fusion Framework

Improving Classifier Confidence using Lossy Label-Invariant Transformations

Feature Whitening via Gradient Transformation for Improved Convergence

HOI Analysis: Integrating and Decomposing Human-Object Interaction

SurReal: Complex-Valued Learning as Principled Transformations on a Scaling and Rotation Manifold

On the Realization and Analysis of Circular Harmonic Transforms for Feature Detection

Transforming Facial Weight of Real Images by Editing Latent Space of StyleGAN

Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving

When We First Met: Visual-Inertial Person Localization for Co-Robot Rendezvous

Rotational Rectification Network: Enabling Pedestrian Detection for Mobile Vision

Do ideas have shape? Plato's theory of forms as the continuous limit of artificial neural networks

Multitask Learning and Joint Optimization for Transformer-RNN-Transducer Speech Recognition

Unsupervised Metric Relocalization Using Transform Consistency Loss

Exploring Severe Occlusion: Multi-Person 3D Pose Estimation with Gated Convolution

SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows

Perception Improvement for Free: Exploring Imperceptible Black-box Adversarial Attacks on Image Classification

Perception Matters: Exploring Imperceptible and Transferable Anti-forensics for GAN-generated Fake Face Imagery Detection

Generalizing Universal Adversarial Attacks Beyond Additive Perturbations

Asynchronous Corner Tracking Algorithm based on Lifetime of Events for DAVIS Cameras

Night vision obstacle detection and avoidance based on Bio-Inspired Vision Sensors

CNN based Multistage Gated Average Fusion (MGAF) for Human Action Recognition Using Depth and Inertial Sensors

A Novel Anomaly Detection Algorithm for Hybrid Production Systems based on Deep Learning and Timed Automata

Point Cloud Attribute Compression via Successive Subspace Graph Transform

Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel

When Deep Learning Meets Data Alignment: A Review on Deep Registration Networks (DRNs)

Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model

MMFT-BERT: Multimodal Fusion Transformer with BERT Encodings for Visual Question Answering

Thinking in Frequency: Face Forgery Detection by Mining Frequency-aware Clues

Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 Network

Controlled Molecule Generator for Optimizing Multiple Chemical Properties

Application of sequential processing of computer vision methods for solving the problem of detecting the edges of a honeycomb block

Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax

Joint Architecture and Knowledge Distillation in CNN for Chinese Text Recognition

Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous Graph Neural Networks

Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities

Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping

Extending DeepSDF for automatic 3D shape retrieval and similarity transform estimation

Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond

Learning Group Structure and Disentangled Representations of Dynamical Environments

Detecting Lane and Road Markings at A Distance with Perspective Transformer Layers

WaveFuse: A Unified Deep Framework for Image Fusion with Discrete Wavelet Transform

ACTNET: end-to-end learning of feature activations and multi-stream aggregation for effective instance image retrieval

Continuous Object Representation Networks: Novel View Synthesis without Target View Supervision

LoopReg: Self-supervised Learning of Implicit Surface Correspondences, Pose and Shape for 3D Human Mesh Registration

DLDL: Dynamic Label Dictionary Learning via Hypergraph Regularization

SAHDL: Sparse Attention Hypergraph Regularized Dictionary Learning

Effective Dimension Adaptive Sketching Methods for Faster Regularized Least-Squares Optimization

Self-Learning Transformations for Improving Gaze and Head Redirection

Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks

NanoFlow: Scalable Normalizing Flows with Sublinear Parameter Complexity

Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study

Robust Low-tubal-rank Tensor Completion based on Tensor Factorization and Maximum Correntopy Criterion

Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions

Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network Embedding

3D Meta-Registration: Learning to Learn Registration of 3D Point Clouds

N-ODE Transformer: A Depth-Adaptive Variant of the Transformer Using Neural Ordinary Differential Equations

Manifold GPLVMs for discovering non-Euclidean latent structure in neural data

Deep Transform and Metric Learning Network: Wedding Deep Dictionary Learning and Neural Networks

Large Scale Indexing of Generic Medical Image Data using Unbiased Shallow Keypoints and Deep CNN Features

BERT2DNN: BERT Distillation with Massive Unlabeled Data for Online E-Commerce Search

A Neural Approach to Ordinal Regression for the Preventive Assessment of Developmental Dyslexia

Self-Supervised Learning of Non-Rigid Residual Flow and Ego-Motion

SL-DML: Signal Level Deep Metric Learning for Multimodal One-Shot Action Recognition

FourierNet: Compact mask representation for instance segmentation using differentiable shape decoders

Estimating Stochastic Linear Combination of Non-linear Regressions Efficiently and Scalably

Extraction of Discrete Spectra Modes from Video Data Using a Deep Convolutional Koopman Network

Gait Recognition using Multi-Scale Partial Representation Transformation with Capsules

Distribution-Based Invariant Deep Networks for Learning Meta-Features

Temporal Binary Representation for Event-Based Action Recognition

Difference-in-Differences: Bridging Normalization and Disentanglement in PG-GAN

Neural Reverse Engineering of Stripped Binaries using Augmented Control Flow Graphs

Video2Commonsense: Generating Commonsense Descriptions to Enrich Video Captioning

Explaining Neural Network Predictions for Functional Data Using Principal Component Analysis and Feature Importance

On Convergence of Nearest Neighbor Classifiers over Feature Transformations

On Large-Scale Dynamic Topic Modeling with Nonnegative CP Tensor Decomposition

Attn-HybridNet: Improving Discriminability of Hybrid Features with Attention Fusion

Toward Few-step Adversarial Training from a Frequency Perspective

Improving Road Signs Detection performance by Combining the Features of Hough Transform and Texture

Three-Dimensional Lip Motion Network for Text-Independent Speaker Recognition

A Scale and Rotational Invariant Key-point Detector based on Sparse Coding

Self-Supervised Multi-View Synchronization Learning for 3D Pose Estimation

Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation

Gradient-based adversarial attacks on categorical sequence models via traversing an embedded world

A Progressive Conditional Generative Adversarial Network for Generating Dense and Colored 3D Point Clouds

On the Computational Power of Transformers and its Implications in Sequence Modeling

Paying down metadata debt: learning the representation of concepts using topic models

Fast Fourier Transformation for Optimizing Convolutional Neural Networks in Object Recognition

Gaussian MRF Covariance Modeling for Efficient Black-Box Adversarial Attacks

Interlocking Backpropagation: Improving depthwise model-parallelism

Where Does the Robustness Come from? A Study of the Transformation-based Ensemble Defence

FetchSGD: Communication-Efficient Federated Learning with Sketching

Improving Sequential Latent Variable Models with Autoregressive Flows

Compressing Deep Convolutional Neural Networks by Stacking Low-dimensional Binary Convolution Filters

A Note on High-Probability versus In-Expectation Guarantees of Generalization Bounds in Machine Learning

On the Universality of Rotation Equivariant Point Cloud Networks

SMILE: Semantically-guided Multi-attribute Image and Layout Editing

DCT-SNN: Using DCT to Distribute Spatial Information over Time for Learning Low-Latency Spiking Neural Networks

How Effective is Task-Agnostic Data Augmentation for Pretrained Transformers?

MDReg-Net: Multi-resolution diffeomorphic image registration using fully convolutional networks with deep self-supervision

Encoded Prior Sliced Wasserstein AutoEncoder for learning latent manifold representations

Uncertainty driven probabilistic voxel selection for image registration

RISA-Net: Rotation-Invariant Structure-Aware Network for Fine-Grained 3D Shape Retrieval

CNN Detection of GAN-Generated Face Images based on Cross-Band Co-occurrences Analysis

Discriminative and Generative Models for Anatomical Shape Analysison Point Clouds with Deep Neural Networks

Block-wise Image Transformation with Secret Key for Adversarially Robust Defense

Cycle-Consistent Adversarial Autoencoders for Unsupervised Text Style Transfer

Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers

Password-conditioned Anonymization and Deanonymization with Face Identity Transformers

Deep-3DAligner: Unsupervised 3D Point Set Registration Network With Optimizable Latent Vector

ConiVAT: Cluster Tendency Assessment and Clustering with Partial Background Knowledge

A complete character recognition and transliteration technique for Devanagari script

Extending the Morphological Hit-or-Miss Transform to Deep Neural Networks

Bayesian Topological Learning for Classifying the Structure of Biological Networks

Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data

BiteNet: Bidirectional Temporal Encoder Network to Predict Medical Outcomes

A deep learning pipeline for identification of motor units in musculoskeletal ultrasound

Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves

Visible fingerprint of X-ray images of epoxy resins using singular value decomposition of deep learning features

Hamming OCR: A Locality Sensitive Hashing Neural Network for Scene Text Recognition

Efficient DWT-based fusion techniques using genetic algorithm for optimal parameter estimation

An Exponential Factorization Machine with Percentage Error Minimization to Retail Sales Forecasting

Conditional Sequential Modulation for Efficient Global Image Retouching

An adaptive transport framework for joint and conditional density estimation

Improving Graph Property Prediction with Generalized Readout Functions

A survey on Kornia: an Open Source Differentiable Computer Vision Library for PyTorch

Learning Representation for Mixed Data Types with a Nonlinear Deep Encoder-Decoder Framework

Towards Evaluating Gaussian Blurring in Perceptual Hashing as a Facial Image Filter

Interaction-Transformation Evolutionary Algorithm for Symbolic Regression

Transform Domain Pyramidal Dilated Convolution Networks For Restoration of Under Display Camera Images

Real-time Lane detection and Motion Planning in Raspberry Pi and Arduino for an Autonomous Vehicle Prototype

Novel View Synthesis from Single Images via Point Cloud Transformation

Late Temporal Modeling in 3D CNN Architectures with BERT for Action Recognition

Smartphone Camera De-identification while Preserving Biometric Utility

Word Segmentation from Unconstrained Handwritten Bangla Document Images using Distance Transform

Cross-Modal Alignment with Mixture Experts Neural Network for Intral-City Retail Recommendation

Skeletonization and Reconstruction based on Graph Morphological Transformations

Red Carpet to Fight Club: Partially-supervised Domain Transfer for Face Recognition in Violent Videos

Robust Person Re-Identification through Contextual Mutual Boosting

UniVL: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation

360-Degree Gaze Estimation in the Wild Using Multiple Zoom Scales

A Self Contour-based Rotation and Translation-Invariant Transformation for Point Clouds Recognition

3DPVNet: Patch-level 3D Hough Voting Network for 6D Pose Estimation

The Exact Equivalence of Distance and Kernel Methods for Hypothesis Testing

Cosine meets Softmax: A tough-to-beat baseline for visual grounding

Pairwise-GAN: Pose-based View Synthesis through Pair-Wise Training

Automatic Target Recognition (ATR) from SAR Imaginary by Using Machine Learning Techniques

Enabling Image Recognition on Constrained Devices Using Neural Network Pruning and a CycleGAN

A Rigorous Machine Learning Analysis Pipeline for Biomedical Binary Classification: Application in Pancreatic Cancer Nested Case-control Studies with Implications for Bias Assessments

Improving Emergency Response during Hurricane Season using Computer Vision

Explanation of Unintended Radiated Emission Classification via LIME

Learning more expressive joint distributions in multimodal variational methods

From deep to Shallow: Equivalent Forms of Deep Networks in Reproducing Kernel Krein Space and Indefinite Support Vector Machines

Black Box to White Box: Discover Model Characteristics Based on Strategic Probing

Unfolding by Folding: a resampling approach to the problem of matrix inversion without actually inverting any matrix

FLFE: A Communication-Efficient and Privacy-Preserving Federated Feature Engineering Framework

Efficient Computation of Higher Order 2D Image Moments using the Discrete Radon Transform

A Universal Representation Transformer Layer for Few-Shot Image Classification

Unsupervised Point Cloud Registration via Salient Points Analysis (SPA)

Evaluation of Deep Convolutional Generative Adversarial Networks for data augmentation of chest X-ray images

Privacy Leakage of SIFT Features via Deep Generative Model based Image Reconstruction

To augment or not to augment? Data augmentation in user identification based on motion sensors

Multi-channel Transformers for Multi-articulatory Sign Language Translation

LodoNet: A Deep Neural Network with 2D Keypoint Matchingfor 3D LiDAR Odometry Estimation

A Generic Graph-based Neural Architecture Encoding Scheme for Predictor-based NAS

Efficient and Sparse Neural Networks by Pruning Weights in a Multiobjective Learning Approach

Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention

Rate-Distortion Optimization Guided Autoencoder for Isometric Embedding in Euclidean Latent Space

Optimal Quantization for Batch Normalization in Neural Network Deployments and Beyond

Self-Organized Operational Neural Networks for Severe Image Restoration Problems

Gauges, Loops, and Polynomials for Partition Functions of Graphical Models

A Fast and Easy Regression Technique for k-NN Classification Without Using Negative Pairs

Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows

Region-Wise Attack: On Efficient Generation of Robust Physical Adversarial Examples

Transforming and Projecting Images into Class-conditional Generative Networks

Think about boundary: Fusing multi-level boundary information for landmark heatmap regression

Data Science for Motion and Time Analysis with Modern Motion Sensor Data

Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers

Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning

Memory-Efficient Incremental Learning Through Feature Adaptation

SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates

Multidomain Multimodal Fusion For Human Action Recognition Using Inertial Sensors

Towards Improved Human Action Recognition Using Convolutional Neural Networks and Multimodal Fusion of Depth and Inertial Sensor Data

Robustness and Overfitting Behavior of Implicit Background Models

Defending Distributed Classifiers Against Data Poisoning Attacks

DeepGMR: Learning Latent Gaussian Mixture Models for Registration

Online Pricing with Offline Data: Phase Transition and Inverse Square Law

Retargetable AR: Context-aware Augmented Reality in Indoor Scenes based on 3D Scene Graph

InfiniteWalk: Deep Network Embeddings as Laplacian Embeddings with a Nonlinearity

Multiple View Generation and Classification of Mid-wave Infrared Images using Deep Learning

Nonparametric Conditional Density Estimation In A Deep Learning Framework For Short-Term Forecasting

Understanding Brain Dynamics for Color Perception using Wearable EEG headband

Spherical coordinates transformation pre-processing in Deep Convolution Neural Networks for brain tumor segmentation in MRI

Model Patching: Closing the Subgroup Performance Gap with Data Augmentation

Efficiently Constructing Adversarial Examples by Feature Watermarking

Graph Polish: A Novel Graph Generation Paradigm for Molecular Optimization

Learning Non-Parametric Invariances from Data with Permanent Random Connectomes

3D Bird Reconstruction: a Dataset, Model, and Shape Recovery from a Single View

End-to-end Contextual Perception and Prediction with Interaction Transformer

An Exploration of Target-Conditioned Segmentation Methods for Visual Object Trackers

An Ensemble of Knowledge Sharing Models for Dynamic Hand Gesture Recognition

ISIA Food-500: A Dataset for Large-Scale Food Recognition via Stacked Global-Local Attention Network

Multi-level Stress Assessment Using Multi-domain Fusion of ECG Signal

Look here! A parametric learning based approach to redirect visual attention

Towards Geometry Guided Neural Relighting with Flash Photography

Retrieval Guided Unsupervised Multi-domain Image-to-Image Translation

PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions

A Better Use of Audio-Visual Cues: Dense Video Captioning with Bi-modal Transformer

Unsupervised Deep Metric Learning with Transformed Attention Consistency and Contrastive Clustering Loss

Driving among Flatmobiles: Bird-Eye-View occupancy grids from a monocular camera for holistic trajectory planning

Projected-point-based Segmentation: A New Paradigm for LiDAR Point Cloud Segmentation

Domain Private and Agnostic Feature for Modality Adaptive Face Recognition

Learning Spatially Structured Image Transformations Using Planar Neural Networks

SOFA-Net: Second-Order and First-order Attention Network for Crowd Counting

Differentiable Manifold Reconstruction for Point Cloud Denoising

LiDAR Data Enrichment Using Deep Learning Based on High-Resolution Image: An Approach to Achieve High-Performance LiDAR SLAM Using Low-cost LiDAR

Forming Local Intersections of Projections for Classifying and Searching Histopathology Images

Global Context Aware Convolutions for 3D Point Cloud Understanding

Universal Differential Equations for Scientific Machine Learning

Joint Self-Attention and Scale-Aggregation for Self-Calibrated Deraining Network

Distortion Robust Image Classification using Deep Convolutional Neural Network with Discrete Cosine Transform

Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes

Self-supervised learning using consistency regularization of spatio-temporal data augmentation for action recognition

Multimodality Biomedical Image Registration using Free Point Transformer Networks

Rotation-Invariant Gait Identification with Quaternion Convolutional Neural Networks

Detection of 3D Bounding Boxes of Vehicles Using Perspective Transformation for Accurate Speed Measurement

Importance of Self-Consistency in Active Learning for Semantic Segmentation

Making Sense of CNNs: Interpreting Deep Representations & Their Invariances with INNs

Addressing the Cold-Start Problem in Outfit Recommendation Using Visual Preference Modelling

Color Texture Image Retrieval Based on Copula Multivariate Modeling in the Shearlet Domain

GmFace: A Mathematical Model for Face Image Representation Using Multi-Gaussian

Adversarial Semantic Data Augmentation for Human Pose Estimation

PIC-Net: Point Cloud and Image Collaboration Network for Large-Scale Place Recognition

User independent Emotion Recognition with Residual Signal-Image Network

SeqDialN: Sequential Visual Dialog Networks in Joint Visual-Linguistic Representation Space

An Efficient Framework for Visible-Infrared Cross Modality Person Re-Identification

Unselfie: Translating Selfies to Neutral-pose Portraits in the Wild

ClsGAN: Selective Attribute Editing Model Based On Classification Adversarial Network

Composer Style Classification of Piano Sheet Music Images Using Language Model Pretraining

GANHopper: Multi-Hop GAN for Unsupervised Image-to-Image Translation

Ordinary Differential Equation and Complex Matrix Exponential for Multi-resolution Image Registration

Mask2CAD: 3D Shape Prediction by Learning to Segment and Retrieve

GP-Aligner: Unsupervised Non-rigid Groupwise Point Set Registration Based On Optimized Group Latent Descriptor

Interpretabilité des modèles : état des lieux des méthodes et application à l'assurance

TSIT: A Simple and Versatile Framework for Image-to-Image Translation

The Surprising Effectiveness of Linear Unsupervised Image-to-Image Translation

Finding trainable sparse networks through Neural Tangent Transfer

Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction

Anatomy-Aware Siamese Network: Exploiting Semantic Asymmetry for Accurate Pelvic Fracture Detection in X-ray Images

Harnessing spatial homogeneity of neuroimaging data: patch individual filter layers for CNNs

A Novel adaptive optimization of Dual-Tree Complex Wavelet Transform for Medical Image Fusion

VFlow: More Expressive Generative Flows with Variational Data Augmentation

Depthwise Spatio-Temporal STFT Convolutional Neural Networks for Human Action Recognition

Representative-Discriminative Learning for Open-set Land Cover Classification of Satellite Imagery

Learning Semantic Correspondence Exploiting an Object-level Prior

Learning Joint Spatial-Temporal Transformations for Video Inpainting

Progressive Transformers for End-to-End Sign Language Production

Cross-View Image Synthesis with Deformable Convolution and Attention Mechanism

A Flexible Optimization Framework for Regularized Matrix-Tensor Factorizations with Linear Couplings

Mapping in a cycle: Sinkhorn regularized unsupervised learning for point cloud shapes

FakeCatcher: Detection of Synthetic Portrait Videos using Biological Signals

Behind the Scene: Revealing the Secrets of Pre-trained Vision-and-Language Models

Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification

Surface Normal Estimation of Tilted Images via Spatial Rectifier

Wavelet Channel Attention Module with a Fusion Network for Single Image Deraining

Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs

HDNet: Human Depth Estimation for Multi-Person Camera-Space Localization

Least Angle Regression in Tangent Space and LASSO for Generalized Linear Models

Deep Learning Based Traffic Surveillance System For Missing and Suspicious Car Detection

Mixing Real and Synthetic Data to Enhance Neural Network Training -- A Review of Current Approaches

AE-Net: Autonomous Evolution Image Fusion Method Inspired by Human Cognitive Mechanism

Knowledge-Based Video Question Answering with Unsupervised Scene Descriptions

Train Your Data Processor: Distribution-Aware and Error-Compensation Coordinate Decoding for Human Pose Estimation

Geometric Wavelet Scattering Networks on Compact Riemannian Manifolds

Modern Hopfield Networks and Attention for Immune Repertoire Classification

FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning

Video-based Remote Physiological Measurement via Cross-verified Feature Disentangling

Transformation Consistency Regularization- A Semi-Supervised Paradigm for Image-to-Image Translation

End-to-end training of a two-stage neural network for defect detection

Reorganizing local image features with chaotic maps: an application to texture recognition

A Graph-based Interactive Reasoning for Human-Object Interaction Detection

Joint Layout Analysis, Character Detection and Recognition for Historical Document Digitization

Marginal Densities, Factor Graph Duality, and High-Temperature Series Expansions

Data from Model: Extracting Data from Non-robust and Robust Models

Sparse Graph to Sequence Learning for Vision Conditioned Long Textual Sequence Generation

Quantization in Relative Gradient Angle Domain For Building Polygon Estimation

Intelligent Credit Limit Management in Consumer Loans Based on Causal Inference

SARS-CoV-2 virus RNA sequence classification and geographical analysis with convolutional neural networks approach

Multi-view Orthonormalized Partial Least Squares: Regularizations and Deep Extensions

Motion-Attentive Transition for Zero-Shot Video Object Segmentation

Recurrent Neural-Linear Posterior Sampling for Non-Stationary Contextual Bandits

Inertial Measurements for Motion Compensation in Weight-bearing Cone-beam CT of the Knee

Depth-Aware Arbitrary Style Transfer Using Instance Normalization

Deep Graph Random Process for Relational-Thinking-Based Speech Recognition

Learning to Segment Anatomical Structures Accurately from One Exemplar

Unsupervised Learning of Landmarks based on Inter-Intra Subject Consistencies

Vanishing Point Detection with Direct and Transposed Fast Hough Transform inside the neural network

PhIT-Net: Photo-consistent Image Transform for Robust Illumination Invariant Matching

On the Generalization Effects of Linear Transformations in Data Augmentation

Machine Learning with the Sugeno Integral: The Case of Binary Classification

On Data Augmentation and Adversarial Risk: An Empirical Analysis

Density-embedding layers: a general framework for adaptive receptive fields

EDSL: An Encoder-Decoder Architecture with Symbol-Level Features for Printed Mathematical Expression Recognition

Auto-captions on GIF: A Large-scale Video-sentence Dataset for Vision-language Pre-training

Aligning Partially Overlapping Point Sets: an Inner Approximation Algorithm

L$^2$-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks

Successfully Applying the Stabilized Lottery Ticket Hypothesis to the Transformer Architecture

OmniNet: A unified architecture for multi-modal multi-task learning

Is Robustness To Transformations Driven by Invariant Neural Representations?

Data Movement Is All You Need: A Case Study on Optimizing Transformers

Optical Fringe Patterns Filtering Based on Multi-Stage Convolution Neural Network

Classification Confidence Estimation with Test-Time Data-Augmentation

Rethinking CNN-Based Pansharpening: Guided Colorization of Panchromatic Images via GANs

Explainable 3D Convolutional Neural Networks by Learning Temporal Transformations

Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search

Bottom-Up Human Pose Estimation by Ranking Heatmap-Guided Adaptive Keypoint Estimates

GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation

Self-Supervised Joint Learning Framework of Depth Estimation via Implicit Cues

Resisting Large Data Variations via Introspective Transformation Network

The Surprising Simplicity of the Early-Time Learning Dynamics of Neural Networks

Self-Segregating and Coordinated-Segregating Transformer for Focused Deep Multi-Modular Network for Visual Question Answering

Kinematic-Structure-Preserved Representation for Unsupervised 3D Human Pose Estimation

Unsupervised Discovery of Interpretable Directions in the GAN Latent Space

Defending against adversarial attacks on medical imaging AI system, classification or detection?

Disentangle Perceptual Learning through Online Contrastive Learning

Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions

Principal Component Networks: Parameter Reduction Early in Training

Applying Lie Groups Approaches for Rigid Registration of Point Clouds

Image-to-image Mapping with Many Domains by Sparse Attribute Transfer

Taming Pretrained Transformers for Extreme Multi-label Text Classification

End-to-End Face Parsing via Interlinked Convolutional Neural Networks

Convolutional neural net face recognition works in non-human-like ways

Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles

Real-time Universal Style Transfer on High-resolution Images via Zero-channel Pruning

Hybrid Spatio-Temporal Graph Convolutional Network: Improving Traffic Prediction with Navigation Data

Adding A Filter Based on The Discriminator to Improve Unconditional Text Generation

Scheduling Policy and Power Allocation for Federated Learning in NOMA Based MEC

Deep Double-Side Learning Ensemble Model for Few-Shot Parkinson Speech Recognition

Performance Evaluation of t-SNE and MDS Dimensionality Reduction Techniques with KNN, ENN and SVM Classifiers

Old is Gold: Redefining the Adversarially Learned One-Class Classifier Training Paradigm

Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions

The Dilemma Between Dimensionality Reduction and Adversarial Robustness

Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Dissecting Deep Networks into an Ensemble of Generative Classifiers for Robust Predictions

Offline detection of change-points in the mean for stationary graph signals

Frost filtered scale-invariant feature extraction and multilayer perceptron for hyperspectral image classification

Flows Succeed Where GANs Fail: Lessons from Low-Dimensional Data

Using Wavelets and Spectral Methods to Study Patterns in Image-Classification Datasets

Kernel Alignment Risk Estimator: Risk Prediction from Training Data

Unsupervised Learning of Global Registration of Temporal Sequence of Point Clouds

Robust registration of medical images in the presence of spatially-varying noise

BUZz: BUffer Zones for defending adversarial examples in image classification

Estimates on Learning Rates for Multi-Penalty Distribution Regression

Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings

Multi-Image Summarization: Textual Summary from a Set of Cohesive Images

Differentiable Neural Architecture Transformation for Reproducible Architecture Improvement

ReLGAN: Generalization of Consistency for GAN with Disjoint Constraints and Relative Learning of Generative Processes for Multiple Transformation Learning

PatchUp: A Regularization Technique for Convolutional Neural Networks

High-contrast "gaudy" images improve the training of deep neural network models of visual cortex

Fine-grained Image-to-Image Transformation towards Visual Recognition

Temporal Fusion Network for Temporal Action Localization:Submission to ActivityNet Challenge 2020 (Task E)

Defending against GAN-based Deepfake Attacks via Transformation-aware Adversarial Faces

Asymptotic Singular Value Distribution of Linear Convolutional Layers

Smartphone Transportation Mode Recognition Using a Hierarchical Machine Learning Classifier and Pooled Features From Time and Frequency Domains

Optimizing generalization on the train set: a novel gradient-based framework to train parameters and hyperparameters simultaneously

Quantification of groundnut leaf defects using image processing algorithms

Defending Against Universal Attacks Through Selective Feature Regeneration

Interferometric Graph Transform: a Deep Unsupervised Graph Representation

An Empirical Analysis of the Impact of Data Augmentation on Knowledge Distillation

Generalized Gumbel-Softmax Gradient Estimator for Various Discrete Random Variables

Ensemble Model with Batch Spectral Regularization and Data Blending for Cross-Domain Few-Shot Learning with Unlabeled Data

Adversarial Optimal Transport Through The Convolution Of Kernels With Evolving Measures

On the Continuity of Rotation Representations in Neural Networks

A fast and memory-efficient algorithm for smooth interpolation of polyrigid transformations: application to human joint tracking

GATCluster: Self-Supervised Gaussian-Attention Network for Image Clustering

Novel Object Viewpoint Estimation through Reconstruction Alignment

Segmentation of Surgical Instruments for Minimally-Invasive Robot-Assisted Procedures Using Generative Deep Neural Networks

Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing

Training Large Neural Networks with Constant Memory using a New Execution Algorithm

Improving Train Track Safety using Drones, Computer Vision and Machine Learning

A Polynomial Neural network with Controllable Precision and Human-Readable Topology II: Accelerated Approach Based on Expanded Layer

Height estimation from single aerial images using a deep ordinal regression network

3D Solid Spherical Bispectrum CNNs for Biomedical Texture Analysis

GoodPoint: unsupervised learning of keypoint detection and description

Semi-supervised deep learning for high-dimensional uncertainty quantification

From Open Set to Closed Set: Supervised Spatial Divide-and-Conquer for Object Counting

Modified Segmentation Algorithm for Recognition of Older Geez Scripts Written on Vellum

SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions

Privacy-Protection Drone Patrol System based on Face Anonymization

Dynamic Facial Expression Generation on Hilbert Hypersphere with Conditional Wasserstein Generative Adversarial Nets

ET-USB: Transformer-Based Sequential Behavior Modeling for Inbound Customer Service

Road Segmentation on low resolution Lidar point clouds for autonomous vehicles

Pay Attention to What You Read: Non-recurrent Handwritten Text-Line Recognition

Interlayer and Intralayer Scale Aggregation for Scale-invariant Crowd Counting

ProAlignNet : Unsupervised Learning for Progressively Aligning Noisy Contours

Coarse-Grain Cluster Analysis of Tensors with Application to Climate Biome Identification

Exploring Spatial-Temporal Multi-Frequency Analysis for High-Fidelity and Temporal-Consistency Video Prediction

Deep learning to discover and predict dynamics on an inertial manifold

SpotFast Networks with Memory Augmented Lateral Transformers for Lipreading

Feature Transformation Ensemble Model with Batch Spectral Regularization for Cross-Domain Few-Shot Classification

Maplets: An Efficient Approach for Cooperative SLAM Map Building Under Communication and Computation Constraints

Butterfly-Net2: Simplified Butterfly-Net and Fourier Transform Initialization

Bridging the Gap Between Training and Inference for Spatio-Temporal Forecasting

A Riemannian Primal-dual Algorithm Based on Proximal Operator and its Application in Metric Learning

Gradientless Descent: High-Dimensional Zeroth-Order Optimization

Dense RepPoints: Representing Visual Objects with Dense Point Sets

Ambient Sound Helps: Audiovisual Crowd Counting in Extreme Conditions

Encryption Inspired Adversarial Defense for Visual Classification

Data Driven Aircraft Trajectory Prediction with Deep Imitation Learning

Transformation Based Deep Anomaly Detection in Astronomical Images

CoCoPIE: Making Mobile AI Sweet As PIE --Compression-Compilation Co-Design Goes a Long Way

Noise Homogenization via Multi-Channel Wavelet Filtering for High-Fidelity Sample Generation in GANs

Exploiting Multi-Layer Grid Maps for Surround-View Semantic Segmentation of Sparse LiDAR Data

Designing a Color Filter via Optimization of Vora-Value for Making a Camera more Colorimetric

Closure Properties for Private Classification and Online Prediction

RetinotopicNet: An Iterative Attention Mechanism Using Local Descriptors with Global Context

Improving BPSO-based feature selection applied to offline WI handwritten signature verification through overfitting control

Hierarchical Attention Transformer Architecture For Syntactic Spell Correction

Non-iterative Simultaneous Rigid Registration Method for Serial Sections of Biological Tissue

A Simple and Scalable Shape Representation for 3D Reconstruction

Character Matters: Video Story Understanding with Character-Aware Relations

A Sim2Real Deep Learning Approach for the Transformation of Images from Multiple Vehicle-Mounted Cameras to a Semantically Segmented Image in Bird's Eye View

Where am I looking at? Joint Location and Orientation Estimation by Cross-View Matching

GraCIAS: Grassmannian of Corrupted Images for Adversarial Security

Graph Spectral Feature Learning for Mixed Data of Categorical and Numerical Type

Towards Accurate and Robust Domain Adaptation under Noisy Environments

A Solution for Large Scale Nonlinear Regression with High Rank and Degree at Constant Memory Complexity via Latent Tensor Reconstruction

Learning of Art Style Using AI and Its Evaluation Based on Psychological Experiments

Sum-Product-Transform Networks: Exploiting Symmetries using Invertible Transformations

Jacks of All Trades, Masters Of None: Addressing Distributional Shift and Obtrusiveness via Transparent Patch Attacks

Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models

Improving Vision-and-Language Navigation with Image-Text Pairs from the Web

Inability of spatial transformations of CNN feature maps to support invariant recognition

Tensor train rank minimization with nonlocal self-similarity for tensor completion

An Explainable Deep Learning-based Prognostic Model for Rotating Machinery

Learning Compositional Koopman Operators for Model-Based Control

Generative Temporal Link Prediction via Self-tokenized Sequence Modeling

Joint Bilateral Learning for Real-time Universal Photorealistic Style Transfer

Efficient Clustering for Stretched Mixtures: Landscape and Optimality

All you need is a second look: Towards Tighter Arbitrary shape text detection

Is rotation forest the best classifier for problems with continuous features?

Learning Spatiotemporal Features of Ride-sourcing Services with Fusion Convolutional Network

Ensemble Generative Cleaning with Feedback Loops for Defending Adversarial Attacks

Quantaized Winograd/Toom-Cook Convolution for DNNs: Beyond Canonical Polynomials Base

Fast and Robust Registration of Aerial Images and LiDAR data Based on Structrual Features and 3D Phase Correlation

Spatio-Temporal Dual Affine Differential Invariant for Skeleton-based Action Recognition

Unsupervised Image-to-Image Translation with Self-Attention Networks

Exploring Racial Bias within Face Recognition via per-subject Adversarially-Enabled Data Augmentation

ASLFeat: Learning Local Features of Accurate Shape and Localization

Adversarial Light Projection Attacks on Face Recognition Systems: A Feasibility Study

Butterfly Transform: An Efficient FFT Based Neural Architecture Design

ESResNet: Environmental Sound Classification Based on Visual Domain Models

Extreme Consistency: Overcoming Annotation Scarcity and Domain Shifts

Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion

In-Machine-Learning Database: Reimagining Deep Learning with Old-School SQL

Automatic diagnosis of the 12-lead ECG using a deep neural network

An Interpretable Compression and Classification System: Theory and Applications

RealMonoDepth: Self-Supervised Monocular Depth Estimation for General Scenes

Feature Lenses: Plug-and-play Neural Modules for Transformation-Invariant Visual Representations

Online Initialization and Extrinsic Spatial-Temporal Calibration for Monocular Visual-Inertial Odometry

MA 3 : Model Agnostic Adversarial Augmentation for Few Shot learning

Minimal Solvers for Rectifying from Radially-Distorted Scales and Change of Scales

Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation

Resonant Machine Learning Based on Complex Growth Transform Dynamical Systems

Multi-Granularity Canonical Appearance Pooling for Remote Sensing Scene Classification

Identification of splicing edges in tampered image based on Dichromatic Reflection Model

Saliency-based Weighted Multi-label Linear Discriminant Analysis

Change Detection in Heterogeneous Optical and SAR Remote Sensing Images via Deep Homogeneous Feature Fusion

Feature Re-Learning with Data Augmentation for Video Relevance Prediction

Geomstats: A Python Package for Riemannian Geometry in Machine Learning

Higher-Order Function Networks for Learning Composable 3D Object Representations

AutoToon: Automatic Geometric Warping for Face Cartoon Generation

Steering Self-Supervised Feature Learning Beyond Local Pixel Statistics

Minimal Solutions for Relative Pose with a Single Affine Correspondence

Acceleration of Convolutional Neural Network Using FFT-Based Split Convolutions

Sparse Concept Coded Tetrolet Transform for Unconstrained Odia Character Recognition

Learning to Cluster Faces via Confidence and Connectivity Estimation

Deep transformation models: Tackling complex regression problems with neural network based transformation models

Business Process Variant Analysis based on Mutual Fingerprints of Event Logs

Using a thousand optimization tasks to learn hyperparameter search strategies

The Edge of Depth: Explicit Constraints between Segmentation and Depth

Deep Semantic Matching with Foreground Detection and Cycle-Consistency

UniformAugment: A Search-free Probabilistic Data Augmentation Approach

Fourier Transform Approach to Machine Learning III: Fourier Classification

SCT: Set Constrained Temporal Transformer for Set Supervised Action Segmentation

Learning Cross-domain Semantic-Visual Relation for Transductive Zero-Shot Learning

Improving the Robustness of Capsule Networks to Image Affine Transformations

Y-net: Multi-scale feature aggregation network with wavelet structure similarity loss function for single image dehazing

Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translation

Unsupervised Model Personalization while Preserving Privacy and Scalability: An Open Problem

Nonlinear Multiview Analysis: Identifiability and Neural Network-assisted Implementation

A Quantum Computational Approach to Correspondence Problems on Point Sets

D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry

DiverseDepth: Affine-invariant Depth Prediction Using Diverse Data

Matrix Smoothing: A Regularization for DNN with Transition Matrix under Noisy Labels

Cascade EF-GAN: Progressive Facial Expression Editing with Local Focuses

Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations

Iterative Answer Prediction with Pointer-Augmented Multimodal Transformers for TextVQA

A Novel Learnable Gradient Descent Type Algorithm for Non-convex Non-smooth Inverse Problems

Solving the Robust Matrix Completion Problem via a System of Nonlinear Equations

Generalizing Spatial Transformers to Projective Geometry with Applications to 2D/3D Registration

Convolutional Neural Networks for User Identificationbased on Motion Sensors Represented as Image

Efficient sampling generation from explicit densities via Normalizing Flows

Illumination-based Transformations Improve Skin Lesion Segmentation in Dermoscopic Images

BiCANet: Bi-directional Contextual Aggregating Network for Image Semantic Segmentation

Coronavirus (COVID-19) Classification using CT Images by Machine Learning Methods

Diversified Arbitrary Style Transfer via Deep Feature Perturbation

PointAugment: an Auto-Augmentation Framework for Point Cloud Classification

Normalized and Geometry-Aware Self-Attention Network for Image Captioning

GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise Transformations

Unsupervised Multi-Modal Image Registration via Geometry Preserving Image-to-Image Translation

Rectified Meta-Learning from Noisy Labels for Robust Image-based Plant Disease Diagnosis

Sample Compression, Support Vectors, and Generalization in Deep Learning

Image Forensics: Detecting duplication of scientific images with manipulation-invariant image similarity

Characterizing and Avoiding Problematic Global Optima of Variational Autoencoders

Semi-Supervised Learning on Graphs with Feature-Augmented Graph Basis Functions

MAP Clustering under the Gaussian Mixture Model via Mixed Integer Nonlinear Optimization

SlimConv: Reducing Channel Redundancy in Convolutional Neural Networks by Weights Flipping

Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion

Multistage Curvilinear Coordinate Transform Based Document Image Dewarping using a Novel Quality Estimator

Energy-based Periodicity Mining with Deep Features for Action Repetition Counting in Unconstrained Videos

Exploring and Distilling Cross-Modal Information for Image Captioning

Learn to Augment: Joint Data Augmentation and Network Optimization for Text Recognition

Attention Convolutional Binary Neural Tree for Fine-Grained Visual Categorization

Stiffness: A New Perspective on Generalization in Neural Networks

Joint COCO and Mapillary Workshop at ICCV 2019 Keypoint Detection Challenge Track Technical Report: Distribution-Aware Coordinate Representation for Human Pose Estimation

Semantic Segmentation of highly class imbalanced fully labelled 3D volumetric biomedical images and unsupervised Domain Adaptation of the pre-trained Segmentation Network to segment another fully unlabelled Biomedical 3D Image stack

Learning to Encode Position for Transformer with Continuous Dynamical Model

A Multi-criteria Approach for Fast and Outlier-aware Representative Selection from Manifolds

Low-Rank and Total Variation Regularization and Its Application to Image Recovery

A Fourier Domain Feature Approach for Human Activity Recognition & Fall Detection

NLH: A Blind Pixel-level Non-local Method for Real-world Image Denoising

Estimation of Accurate and Calibrated Uncertainties in Deterministic models

DNNSurv: Deep Neural Networks for Survival Analysis Using Pseudo Values

On Isometry Robustness of Deep 3D Point Cloud Models under Adversarial Attacks

DymSLAM:4D Dynamic Scene Reconstruction Based on Geometrical Motion Segmentation

Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation

Registration of multi-view point sets under the perspective of expectation-maximization

Unifying Specialist Image Embedding into Universal Image Embedding

Using Panoramic Videos for Multi-person Localization and Tracking in a 3D Panoramic Coordinate

PUGeo-Net: A Geometry-centric Network for 3D Point Cloud Upsampling

TTPP: Temporal Transformer with Progressive Prediction for Efficient Action Anticipation

DETECT: Deep Trajectory Clustering for Mobility-Behavior Analysis

Energy-efficient and Robust Cumulative Training with Net2Net Transformation

Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddings

Learning Matchable Image Transformations for Long-term Metric Visual Localization

Multi-source Domain Adaptation in the Deep Learning Era: A Systematic Survey

Are Transformers universal approximators of sequence-to-sequence functions?

Adversarial Perturbations Prevail in the Y-Channel of the YCbCr Color Space

Sketchformer: Transformer-based Representation for Sketched Structure

Back-Projection based Fidelity Term for Ill-Posed Linear Inverse Problems

VisionGuard: Runtime Detection of Adversarial Inputs to Perception Systems

Interpretable Crowd Flow Prediction with Spatial-Temporal Self-Attention

Improved Calibration of Numerical Integration Error in Sigma-Point Filters

Forecaster: A Graph Transformer for Forecasting Spatial and Time-Dependent Data

MaxUp: A Simple Way to Improve Generalization of Neural Network Training

A critical analysis of self-supervision, or what we can learn from a single image

Differentially Private M-band Wavelet-Based Mechanisms in Machine Learning Environments

Computational optimization of convolutional neural networks using separated filters architecture

Deep Neural Networks for the Correction of Mie Scattering in Fourier-Transformed Infrared Spectra of Biological Samples

A Computationally Efficient Neural Network Invariant to the Action of Symmetry Subgroups

Data Transformation Insights in Self-supervision with Clustering Tasks

VL-BERT: Pre-training of Generic Visual-Linguistic Representations

Investigating the Compositional Structure Of Deep Neural Networks

Text Perceptron: Towards End-to-End Arbitrary-Shaped Text Spotting

Hybrid Embedded Deep Stacked Sparse Autoencoder with w_LPPD SVM Ensemble

Unifying Graph Convolutional Neural Networks and Label Propagation

REST: Performance Improvement of a Black Box Model via RL-based Spatial Transformation

Automated Labelling using an Attention model for Radiology reports of MRI scans (ALARM)

The Shallow End: Empowering Shallower Deep-Convolutional Networks through Auxiliary Outputs

Neural tangent kernels, transportation mappings, and universal approximation

End-to-end Learning of Object Motion Estimation from Retinal Events for Event-based Object Tracking

AGATHA: Automatic Graph-mining And Transformer based Hypothesis generation Approach

Novel tracking approach based on fully-unsupervised disentanglement of the geometrical factors of variation

A Simple General Approach to Balance Task Difficulty in Multi-Task Learning

Truncated Hilbert Transform: Uniqueness and a Chebyshev series Expansion Approach

Neural Network Approximation of Graph Fourier Transforms for Sparse Sampling of Networked Flow Dynamics

Multiple-image encryption and hiding with an optical diffractive neural network

A Framework for Semi-Automatic Precision and Accuracy Analysis for Fast and Rigorous Deep Learning

Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring In Data

One Shot Learning for Deformable Medical Image Registration and Periodic Motion Tracking

Weakly-Supervised Multi-Person Action Recognition in 360$^{\circ}$ Videos

Improved Subsampled Randomized Hadamard Transform for Linear SVM

Privacy-Preserving Image Sharing via Sparsifying Layers on Convolutional Groups

A Two-Stream Symmetric Network with Bidirectional Ensemble for Aerial Image Matching

Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform

Multistage Model for Robust Face Alignment Using Deep Neural Networks

Unsupervised Pixel-level Road Defect Detection via Adversarial Image-to-Frequency Transform

Robust Local Features for Improving the Generalization of Adversarial Training

Classification of EEG Signal based on non-Gaussian Neutral Vector

Dirichlet Mixture Model based VQ Performance Prediction for Line Spectral Frequency

Theory inspired deep network for instantaneous-frequency extraction and signal components recovery from discrete blind-source data

TCM-ICP: Transformation Compatibility Measure for Registering Multiple LIDAR Scans

Automatic marker-free registration of tree point-cloud data based on rotating projection

Enhancing Transformation-based Defenses using a Distribution Classifier

An Internal Clock Based Space-time Neural Network for Motion Speed Recognition

Predicting Regression Probability Distributions with Imperfect Data Through Optimal Transformations

DRMIME: Differentiable Mutual Information and Matrix Exponential for Multi-Resolution Image Registration

Learning Part Generation and Assembly for Structure-aware Shape Synthesis

ImageBERT: Cross-modal Pre-training with Large-scale Weak-supervised Image-Text Data

A Data Dependent Multiscale Model for Hyperspectral Unmixing With Spectral Variability

Dynamic multi-object Gaussian process models: A framework for data-driven functional modelling of human joints

An End-to-end Deep Learning Approach for Landmark Detection and Matching in Medical Images

Manifold Modeling in Embedded Space: A Perspective for Interpreting Deep Image Prior

UR2KiD: Unifying Retrieval, Keypoint Detection, and Keypoint Description without Local Correspondence Supervision

FIS-Nets: Full-image Supervised Networks for Monocular Depth Estimation

SieveNet: A Unified Framework for Robust Image-Based Virtual Try-On

An adversarial learning framework for preserving users' anonymity in face-based emotion recognition

Shifted and Squeezed 8-bit Floating Point format for Low-Precision Training of Deep Neural Networks

Newtonian Monte Carlo: single-site MCMC meets second-order gradient methods

ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data

Interpretable Complex-Valued Neural Networks for Privacy Protection

Boosting Deep Face Recognition via Disentangling Appearance and Geometry

Residual Attention Net for Superior Cross-Domain Time Sequence Modeling

A Comparative Study for Non-rigid Image Registration and Rigid Image Registration

Using Persistent Homology to Quantify a Diurnal Cycle in Hurricane Felix

RSI-CB: A Large Scale Remote Sensing Image Classification Benchmark via Crowdsource Data

Cloud-based Image Classification Service Is Not Robust To Simple Transformations: A Forgotten Battlefield

A statistical interpretation of spectral embedding: the generalised random dot product graph

Depth Restoration: A fast low-rank matrix completion via dual-graph regularization

VisionNet: A Drivable-space-based Interactive Motion Prediction Network for Autonomous Driving

Robust Facial Landmark Detection via Aggregation on Geometrically Manipulated Faces

Softmax-based Classification is k-means Clustering: Formal Proof, Consequences for Adversarial Attacks, and Improvement through Centroid Based Tailoring

STNReID : Deep Convolutional Networks with Pairwise Spatial Transformer Networks for Partial Person Re-identification

Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations

A Robust Pose Transformational GAN for Pose Guided Person Image Synthesis

End-To-End Trainable Video Super-Resolution Based on a New Mechanism for Implicit Motion Estimation and Compensation

DAF-NET: a saliency based weakly supervised method of dual attention fusion for fine-grained image classification

PPD: Permutation Phase Defense Against Adversarial Examples in Deep Learning

Discoverability in Satellite Imagery: A Good Sentence is Worth a Thousand Pictures

Learning Accurate Integer Transformer Machine-Translation Models

Video Saliency Prediction Using Enhanced Spatiotemporal Alignment Network

Why do deep convolutional networks generalize so poorly to small image transformations?

Automated Testing for Deep Learning Systems with Differential Behavior Criteria

Efficient Decremental Learning Algorithms for Broad Learning System

Using massive health insurance claims data to predict very high-cost claimants: a machine learning approach

Recognizing Instagram Filtered Images with Feature De-stylization

An Efficient Pre-processing Method to Eliminate Adversarial Effects

Is Attention All What You Need? -- An Empirical Investigation on Convolution-Based Active Memory and Self-Attention

Deep Random Splines for Point Process Intensity Estimation of Neural Population Data

FLAT: Few-Shot Learning via Autoencoding Transformation Regularizers

Cluster-wise Unsupervised Hashing for Cross-Modal Similarity Search

One Point, One Object: Simultaneous 3D Object Segmentation and 6-DOF Pose Estimation

Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro

Geometry Sharing Network for 3D Point Cloud Classification and Segmentation

JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds

Embedded Constrained Feature Construction for High-Energy Physics Data Classification

Deep Time-Frequency Representation and Progressive Decision Fusion for ECG Classification

PDQ & TMK + PDQF -- A Test Drive of Facebook's Perceptual Hashing Algorithms

RATQ: A Universal Fixed-Length Quantizer for Stochastic Optimization

Joint Embedding Learning and Low-Rank Approximation: A Framework for Incomplete Multi-view Learning

Fairness Assessment for Artificial Intelligence in Financial Industry

PointHop: An Explainable Machine Learning Method for Point Cloud Classification

A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection

Symmetric block-low-rank layers for fully reversible multilevel neural networks

Laguerre-Gauss Preprocessing: Line Profiles as Image Features for Aerial Images Classification

Elastic registration based on compliance analysis and biomechanical graph matching

Identity Preserve Transform: Understand What Activity Classification Models Have Learnt

Developing the Path Signature Methodology and its Application to Landmark-based Human Action Recognition

Counterfactuals uncover the modular structure of deep generative models

Bottleneck detection by slope difference distribution: a robust approach for separating overlapped cells

SynthText3D: Synthesizing Scene Text Images from 3D Virtual Worlds

Unsupervised Co-Learning on $\mathcal{G}$-Manifolds Across Irreducible Representations

Deep Distance Transform for Tubular Structure Segmentation in CT Scans

Weak Supervision helps Emergence of Word-Object Alignment and improves Vision-Language Tasks

Influenza Modeling Based on Massive Feature Engineering and International Flow Deconvolution

Self-Supervised Contextual Language Representation of Radiology Reports to Improve the Identification of Communication Urgency

Representing Closed Transformation Paths in Encoded Network Latent Space

Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression

Unified Vision-Language Pre-Training for Image Captioning and VQA

Better Understanding Hierarchical Visual Relationship for Image Caption

Integrating Motion into Vision Models for Better Visual Prediction

The Analysis of Projective Transformation Algorithms for Image Recognition on Mobile Devices

Floorplan-Jigsaw: Jointly Estimating Scene Layout and Aligning Partial Scans

Multi-resolution Graph Neural Network for Identifying Disease-specific Variations in Brain Connectivity

Long Distance Relationships without Time Travel: Boosting the Performance of a Sparse Predictive Autoencoder in Sequence Modeling

MSD: Multi-Self-Distillation Learning via Multi-classifiers within Deep Neural Networks

Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training

An Attribute Oriented Induction based Methodology for Data Driven Predictive Maintenance

Patchy Image Structure Classification Using Multi-Orientation Region Transform

Not All Attention Is Needed: Gated Attention Network for Sequence Data

Deep Object Co-segmentation via Spatial-Semantic Network Modulation

Spatiotemporal deep learning model for citywide air pollution interpolation and prediction

Motion Equivariance OF Event-based Camera Data with the Temporal Normalization Transform

Transform-Invariant Convolutional Neural Networks for Image Classification and Search

One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples

Copulas as High-Dimensional Generative Models: Vine Copula Autoencoders

Complex-valued neural networks for machine learning on non-stationary physical data

Unsupervised Feature Learning for Environmental Sound Classification Using Weighted Cycle-Consistent Generative Adversarial Network

Robust Feature-Based Point Registration Using Directional Mixture Model

A Robust Approach for Securing Audio Classification Against Adversarial Attacks

SparseTrain:Leveraging Dynamic Sparsity in Training DNNs on General-Purpose SIMD Processors

Pothole Detection Based on Disparity Transformation and Road Surface Modeling

Factorized Multimodal Transformer for Multimodal Sequential Learning

When Does Non-Orthogonal Tensor Decomposition Have No Spurious Local Minima?

WildMix Dataset and Spectro-Temporal Transformer Model for Monoaural Audio Source Separation

Semi-supervised Learning with Adaptive Neighborhood Graph Propagation Network

RankML: a Meta Learning-Based Approach for Pre-Ranking Machine Learning Pipelines

Video Segment Copy Detection Using Memory Constrained Hierarchical Batch-Normalized LSTM Autoencoder

Response Transformation and Profit Decomposition for Revenue Uplift Modeling

Automatic Design of CNNs via Differentiable Neural Architecture Search for PolSAR Image Classification

MarioNETte: Few-shot Face Reenactment Preserving Identity of Unseen Targets

Image-Based Size Analysis of Agglomerated and Partially Sintered Particles via Convolutional Neural Networks

An End-to-End HW/SW Co-Design Methodology to Design Efficient Deep Neural Network Systems using Virtual Models

Geometry-constrained Car Recognition Using a 3D Perspective Network

Learning Backtrackless Aligned-Spatial Graph Convolutional Networks for Graph Classification

Learning Generalized Transformation Equivariant Representations via Autoencoding Transformations

All-In-One: Facial Expression Transfer, Editing and Recognition Using A Single Network

What Will Your Child Look Like? DNA-Net: Age and Gender Aware Kin Face Synthesizer

Faster AutoAugment: Learning Augmentation Strategies using Backpropagation

SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning

A3GAN: An Attribute-aware Attentive Generative Adversarial Network for Face Aging

Towards More Realistic Human-Robot Conversation: A Seq2Seq-based Body Gesture Interaction System

Sequential Recommendation with Relation-Aware Kernelized Self-Attention

Harnessing spatial MRI normalization: patch individual filter layers for CNNs

CartoonRenderer: An Instance-based Multi-Style Cartoon Image Translator

adVAE: A self-adversarial variational autoencoder with Gaussian anomaly prior knowledge for anomaly detection

GIFT: Learning Transformation-Invariant Dense Visual Descriptors via Group CNNs

Explainable Ordinal Factorization Model: Deciphering the Effects of Attributes by Piece-wise Linear Approximation

TASTE: Temporal and Static Tensor Factorization for Phenotyping Electronic Health Records

Trainable Spectrally Initializable Matrix Transformations in Convolutional Neural Networks

Achieving Generalizable Robustness of Deep Neural Networks by Stability Training

Fairness-Aware Neural Réyni Minimization for Continuous Features

Predictive Multi-level Patient Representations from Electronic Health Records

Transformer Dissection: A Unified Understanding of Transformer's Attention via the Lens of Kernel

Preservation of Anomalous Subgroups On Machine Learning Transformed Data

Learning Deep Bilinear Transformation for Fine-grained Image Representation

Spatial Feature Extraction in Airborne Hyperspectral Images Using Local Spectral Similarity

Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO

Hierarchical Optimal Transport for Multimodal Distribution Alignment

Bayesian Inference over the Stiefel Manifold via the Givens Representation

On the One-sided Convergence of Adam-type Algorithms in Non-convex Non-concave Min-max Optimization

MO-PaDGAN: Reparameterizing Engineering Designs for Augmented Multi-objective Optimization

A novel network training approach for open set image recognition

Logo Generation Using Regional Features: A Faster R-CNN Approach to Generative Adversarial Networks

Generalized multiscale feature extraction for remaining useful life prediction of bearings with generative adversarial networks

ReGenMorph: Visibly Realistic GAN Generated Face Morphing Attacks by Attack Re-generation

Unsupervised Cycle-consistent Generative Adversarial Networks for Pan-sharpening

A deep generative model for probabilistic energy forecasting in power systems: normalizing flows

Scenario generation for market risk models using generative neural networks

RECALL: Replay-based Continual Learning in Semantic Segmentation

New Perspective on Progressive GANs Distillation for One-class Novelty Detection

A Unified Framework for Biphasic Facial Age Translation with Noisy-Semantic Guided Generative Adversarial Networks

MSGDD-cGAN: Multi-Scale Gradients Dual Discriminator Conditional Generative Adversarial Network

Semi-supervised Semantic Segmentation of Prostate and Organs-at-Risk on 3D Pelvic CT Images

Conditional Generation of Synthetic Geospatial Images from Pixel-level and Feature-level Inputs

MobileStyleGAN: A Lightweight Convolutional Neural Network for High-Fidelity Image Synthesis

Brand Label Albedo Extraction of eCommerce Products using Generative Adversarial Network

Multi-Spectral Image Synthesis for Crop/Weed Segmentation in Precision Farming

Analysis of Discriminator in RKHS Function Space for Kullback-Leibler Divergence Estimation

Solving Inverse Problems with Conditional-GAN Prior via Fast Network-Projected Gradient Descent

Creating synthetic meteorology satellite visible light images during night based on GAN method

TabFairGAN: Fair Tabular Data Generation with Generative Adversarial Networks

Eyes Tell All: Irregular Pupil Shapes Reveal GAN-generated Faces

Layout-to-Image Translation with Double Pooling Generative Adversarial Networks

Teacher-Student Adversarial Depth Hallucination to Improve Face Recognition

Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary

Stagewise Unsupervised Domain Adaptation with Adversarial Self-Training for Road Segmentation of Remote Sensing Images

XCI-Sketch: Extraction of Color Information from Images for Generation of Colored Outlines and Sketches

ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement

Adaptable GAN Encoders for Image Reconstruction via Multi-type Latent Vectors with Two-scale Attentions

Cascade Watchdog: A Multi-tiered Adversarial Guard for Outlier Detection

MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction

Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer

Indoor Scene Generation from a Collection of Semantic-Segmented Depth Images

Mitigating Greenhouse Gas Emissions Through Generative Adversarial Networks Based Wildfire Prediction

Towards Vivid and Diverse Image Colorization with Generative Color Prior

DRB-GAN: A Dynamic ResBlock Generative Adversarial Network for Artistic Style Transfer

F-Drop&Match: GANs with a Dead Zone in the High-Frequency Domain

FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning

Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data

Transferring Knowledge with Attention Distillation for Multi-Domain Image-to-Image Translation

AttentionGAN: Unpaired Image-to-Image Translation using Attention-Guided Generative Adversarial Networks

PaDGAN: A Generative Adversarial Network for Performance Augmented Diverse Designs

Text2Video: Text-driven Talking-head Video Synthesis with Personalized Phoneme-Pose Dictionary

An Image-based Generator Architecture for Synthetic Image Refinement

Temporal Sparse Adversarial Attack on Sequence-based Gait Recognition

EVGen: Adversarial Networks for Learning Electric Vehicle Charging Loads and Hidden Representations

AlphaGAN: Fully Differentiable Architecture Search for Generative Adversarial Networks

SMOTified-GAN for class imbalanced pattern classification problems

Instance Similarity Learning for Unsupervised Feature Representation

Information Stealing in Federated Learning Systems Based on Generative Adversarial Networks

An End-to-End and Accurate PPG-based Respiratory Rate Estimation Approach Using Cycle Generative Adversarial Networks

Fully-Automatic Pipeline for Document Signature Analysis to Detect Money Laundering Activities

Profile to Frontal Face Recognition in the Wild Using Coupled Conditional GAN

Improving ClusterGAN Using Self-AugmentedInformation Maximization of Disentangling LatentSpaces

Generative Adversarial User Privacy in Lossy Single-Server Information Retrieval

On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems

Facetron: Multi-speaker Face-to-Speech Model based on Cross-modal Latent Representations

P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection

Tail of Distribution GAN (TailGAN): Generative- Adversarial-Network-Based Boundary Formation

BrainNetGAN: Data augmentation of brain connectivity using generative adversarial network for dementia classification

Unrealistic Feature Suppression for Generative Adversarial Networks

Ready for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack

Characterization Multimodal Connectivity of Brain Network by Hypergraph GAN for Alzheimer's Disease Analysis

Boundary of Distribution Support Generator (BDSG): Sample Generation on the Boundary

Leverage Score Sampling for Complete Mode Coverage in Generative Adversarial Networks

$γ$-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction

RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rank

FoleyGAN: Visually Guided Generative Adversarial Network-Based Synchronous Sound Generation in Silent Videos

Evolutionary Generative Adversarial Networks with Crossover Based Knowledge Distillation

A New Distributed Method for Training Generative Adversarial Networks

Painting Style-Aware Manga Colorization Based on Generative Adversarial Networks

Privacy-preserving Spatiotemporal Scenario Generation of Renewable Energies: A Federated Deep Generative Learning Approach

ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networks

Learning Efficient GANs for Image Translation via Differentiable Masks and co-Attention Distillation

Level generation and style enhancement -- deep learning for game development overview

MCL-GAN: Generative Adversarial Networks with Multiple Specialized Discriminators

Differential-Critic GAN: Generating What You Want by a Cue of Preferences

Style-Restricted GAN: Multi-Modal Translation with Style Restriction Using Generative Adversarial Networks

Efficient, Simple and Automated Negative Sampling for Knowledge Graph Embedding

On the Performance Analysis of the Adversarial System Variant Approximation Method to Quantify Process Model Generalization

This Person (Probably) Exists. Identity Membership Attacks Against GAN Generated Faces

Stability and Generalization of Stochastic Gradient Methods for Minimax Problems

Visual-Tactile Cross-Modal Data Generation using Residue-Fusion GAN with Feature-Matching and Perceptual Losses

Generalization Error of GAN from the Discriminator's Perspective

Anomaly detection and automatic labeling for solar cell quality inspection based on Generative Adversarial Network

Semantic Segmentation Alternative Technique: Segmentation Domain Generation

Non-Exhaustive Learning Using Gaussian Mixture Generative Adversarial Networks

Uncertainty-Guided Progressive GANs for Medical Image Translation

High Resolution Face Editing with Masked GAN Latent Code Optimization

An error analysis of generative adversarial networks for learning distributions

One-class Steel Detector Using Patch GAN Discriminator for Visualising Anomalous Feature Map

Mutual-GAN: Towards Unsupervised Cross-Weather Adaptation with Mutual Information Constraint

Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions

Face Sketch Synthesis via Semantic-Driven Generative Adversarial Network

Scene Uncertainty and the Wellington Posterior of Deterministic Image Classifiers

Fostering Diversity in Spatial Evolutionary Generative Adversarial Networks

Feature Alignment for Approximated Reversibility in Neural Networks

GANMEX: One-vs-One Attributions Guided by GAN-based Counterfactual Explanation Baselines

Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editing

Particle Cloud Generation with Message Passing Generative Adversarial Networks

An Accurate Non-accelerometer-based PPG Motion Artifact Removal Technique using CycleGAN

Wallpaper Texture Generation and Style Transfer Based on Multi-label Semantics

EC-GAN: Low-Sample Classification using Semi-Supervised Algorithms and GANs

FDeblur-GAN: Fingerprint Deblurring using Generative Adversarial Network

IGANI: Iterative Generative Adversarial Networks for Imputation with Application to Traffic Data

Constructing Forest Biomass Prediction Maps from Radar Backscatter by Sequential Regression with a Conditional Generative Adversarial Network

IsMo-GAN: Adversarial Learning for Monocular Non-Rigid 3D Reconstruction

Data Assimilation Predictive GAN (DA-PredGAN): applied to determine the spread of COVID-19

Local AdaGrad-Type Algorithm for Stochastic Convex-Concave Minimax Problems

Novelty Detection via Contrastive Learning with Negative Data Augmentation

A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention

Unsupervised Training Data Generation of Handwritten Formulas using Generative Adversarial Networks with Self-Attention

Disentangling Semantic-to-visual Confusion for Zero-shot Learning

Compound Frechet Inception Distance for Quality Assessment of GAN Created Images

A Synchronized Reprojection-based Model for 3D Human Pose Estimation

Quantifying the Preferential Direction of the Model Gradient in Adversarial Training With Projected Gradient Descent

Gaze Preserving CycleGANs for Eyeglass Removal & Persistent Gaze Estimation

Game of GANs: Game Theoretical Models for Generative Adversarial Networks

More Real than Real: A Study on Human Visual Perception of Synthetic Faces

Generation of the NIR spectral Band for Satellite Images with Convolutional Neural Networks

Do Not Escape From the Manifold: Discovering the Local Coordinates on the Latent Space of GANs

A One-Shot Texture-Perceiving Generative Adversarial Network for Unsupervised Surface Inspection

A self-adapting super-resolution structures framework for automatic design of GAN

DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detection

Match What Matters: Generative Implicit Feature Replay for Continual Learning

ZoPE: A Fast Optimizer for ReLU Networks with Low-Dimensional Inputs

WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points

Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial Networks

On the use of automatically generated synthetic image datasets for benchmarking face recognition

Seismic Inverse Modeling Method based on Generative Adversarial Network

Learning to Efficiently Sample from Diffusion Probabilistic Models

PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design

Deep learning enables reference-free isotropic super-resolution for volumetric fluorescence microscopy

i3dLoc: Image-to-range Cross-domain Localization Robust to Inconsistent Environmental Conditions

From DNNs to GANs: Review of efficient hardware architectures for deep learning

PeerGAN: Generative Adversarial Networks with a Competing Peer Discriminator

Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions

Using latent space regression to analyze and leverage compositionality in GANs

Semantic Palette: Guiding Scene Generation with Class Proportions

IID-GAN: an IID Sampling Perspective for Regularizing Mode Collapse

Digital rock reconstruction with user-defined properties using conditional generative adversarial networks

Unsupervised Shadow Removal Using Target Consistency Generative Adversarial Network

D-GAN: Deep Generative Adversarial Nets for Spatio-Temporal Prediction

Data-Efficient GAN Training Beyond (Just) Augmentations: A Lottery Ticket Perspective

A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks

Pattern Detection in the Activation Space for Identifying Synthesized Content

Enhance to Read Better: An Improved Generative Adversarial Network for Handwritten Document Image Enhancement

Approximation Capabilities of Wasserstein Generative Adversarial Networks

Synthesizing Optical and SAR Imagery From Land Cover Maps and Auxiliary Raster Data

Estimates of maize plant density from UAV RGB images using Faster-RCNN detection model: impact of the spatial resolution

GAN for Vision, KG for Relation: a Two-stage Deep Network for Zero-shot Action Recognition

Face Anonymization by Manipulating Decoupled Identity Representation

Unsupervised Video Summarization with a Convolutional Attentive Adversarial Network

Unsupervised Remote Sensing Super-Resolution via Migration Image Prior

A Robust and Generalized Framework for Adversarial Graph Embedding

SmartPatch: Improving Handwritten Word Imitation with Patch Discriminators

High Fidelity Fingerprint Generation: Quality, Uniqueness, and Privacy

Behind the leaves -- Estimation of occluded grapevine berries with conditional generative adversarial networks

Anomaly Detection of Test-Time Evasion Attacks using Class-conditional Generative Adversarial Networks

Physically-Consistent Generative Adversarial Networks for Coastal Flood Visualization

Image to Image Translation : Generating maps from satellite images

Semantic Relation Preserving Knowledge Distillation for Image-to-Image Translation

Fast-GANFIT: Generative Adversarial Network for High Fidelity 3D Face Reconstruction

Verification of Image-based Neural Network Controllers Using Generative Models

Salient Feature Extractor for Adversarial Defense on Deep Neural Networks

Label Geometry Aware Discriminator for Conditional Generative Networks

Exploiting the Hidden Tasks of GANs: Making Implicit Subproblems Explicit

Uncover Common Facial Expressions in Terracotta Warriors: A Deep Learning Approach

Learning High-Dimensional Distributions with Latent Neural Fokker-Planck Kernels

Generation For Adaption: A GAN-Based Approach for 3D Domain Adaption with Point Cloud Data

BIM Hyperreality: Data Synthesis Using BIM and Hyperrealistic Rendering for Deep Learning

HAD-GAN: A Human-perception Auxiliary Defense GAN to Defend Adversarial Examples

Multimodal Image-to-Image Translation via Mutual Information Estimation and Maximization

Digital twins based on bidirectional LSTM and GAN for modelling the COVID-19 pandemic

Toward Interactive Modulation for Photo-Realistic Image Restoration

Brain Multigraph Prediction using Topology-Aware Adversarial Graph Neural Network

Roof-GAN: Learning to Generate Roof Geometry and Relations for Residential Houses

Stabilization of generative adversarial networks via noisy scale-space

GRNN: Generative Regression Neural Network -- A Data Leakage Attack for Federated Learning

Feature Disentanglement in generating three-dimensional structure from two-dimensional slice with sliceGAN

Distilling and Transferring Knowledge via cGAN-generated Samples for Image Classification and Regression

Data-driven Full-waveform Inversion Surrogate using Conditional Generative Adversarial Networks

End-to-End Video-To-Speech Synthesis using Generative Adversarial Networks

Preserving Semantic Consistency in Unsupervised Domain Adaptation Using Generative Adversarial Networks

Two-stage generative adversarial networks for document image binarization with color noise and background removal

Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation Generative Adversarial Networks

Inner-ear Augmented Metal Artifact Reduction with Simulation-based 3D Generative Adversarial Networks

One-shot Face Reenactment Using Appearance Adaptive Normalization

VCGAN: Video Colorization with Hybrid Generative Adversarial Network

ICE-GAN: Identity-aware and Capsule-Enhanced GAN with Graph-based Reasoning for Micro-Expression Recognition and Synthesis

Continuous Conversion of CT Kernel using Switchable CycleGAN with AdaIN

Supervised Anomaly Detection via Conditional Generative Adversarial Network and Ensemble Active Learning

Ano-Graph: Learning Normal Scene Contextual Graphs to Detect Video Anomalies

Causal-TGAN: Generating Tabular Data Using Causal Generative Adversarial Networks

Federated Traffic Synthesizing and Classification Using Generative Adversarial Networks

Disentangled Face Identity Representations for joint 3D Face Recognition and Expression Neutralisation

Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering

Semantic Segmentation by Improved Generative Adversarial Networks

Bias-Free FedGAN: A Federated Approach to Generate Bias-Free Datasets

Generative Compositional Augmentations for Scene Graph Prediction

Convergence dynamics of Generative Adversarial Networks: the dual metric flows

Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models

Machine-learned 3D Building Vectorization from Satellite Imagery

Masked GANs for Unsupervised Depth and Pose Prediction with Scale Consistency

Understanding Overparameterization in Generative Adversarial Networks

Diamond in the rough: Improving image realism by traversing the GAN latent space

ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning

An Empirical Study of the Effects of Sample-Mixing Methods for Efficient Training of Generative Adversarial Networks

Why Spectral Normalization Stabilizes GANs: Analysis and Improvements

MIPGAN -- Generating Strong and High Quality Morphing Attacks Using Identity Prior Driven GAN

Deep learning for prediction of complex geology ahead of drilling

Generalization of GANs under Lipschitz continuity and data augmentation

pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis

Double cycle-consistent generative adversarial network for unsupervised conditional generation

An Adversarial Human Pose Estimation Network Injected with Graph Structure

Human Action Recognition in Drone Videos using a Few Aerial Training Examples

LatentCLR: A Contrastive Learning Approach for Unsupervised Discovery of Interpretable Directions

MR Slice Profile Estimation by Learning to Match Internal Patch Distributions

Attention Map-guided Two-stage Anomaly Detection using Hard Augmentation

IUP: An Intelligent Utility Prediction Scheme for Solid-State Fermentation in 5G IoT

Continuous Conditional Generative Adversarial Networks (cGAN) with Generator Regularization

Learning Layout and Style Reconfigurable GANs for Controllable Image Synthesis

Adversarial Multiscale Feature Learning for Overlapping Chromosome Segmentation

Matched sample selection with GANs for mitigating attribute confounding

FD-GAN: Generative Adversarial Networks with Fusion-discriminator for Single Image Dehazing

CDE-GAN: Cooperative Dual Evolution Based Generative Adversarial Network

Evaluating Post-Training Compression in GANs using Locality-Sensitive Hashing

Conditional Generative Adversarial Networks for Speed Control in Trajectory Simulation

Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-Informed Deep Generative Models

Efficient Subsampling for Generating High-Quality Images from Conditional Generative Adversarial Networks

Are High-Frequency Components Beneficial for Training of Generative Adversarial Networks

More than just an auxiliary loss: Anti-spoofing Backbone Training via Adversarial Pseudo-depth Generation

Large Scale Image Completion via Co-Modulated Generative Adversarial Networks

Rapid treatment planning for low-dose-rate prostate brachytherapy with TP-GAN

High Perceptual Quality Image Denoising with a Posterior Sampling CGAN

Contrastive Divergence Learning is a Time Reversal Adversarial Game

GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators

Graph Regularized Autoencoder and its Application in Unsupervised Anomaly Detection

Face Images as Jigsaw Puzzles: Compositional Perception of Human Faces for Machines Using Generative Adversarial Networks

Range-GAN: Range-Constrained Generative Adversarial Network for Conditioned Design Synthesis

Weather GAN: Multi-Domain Weather Translation Using Generative Adversarial Networks

Fully Automatic Electrocardiogram Classification System based on Generative Adversarial Network with Auxiliary Classifier

A Novel Application of Image-to-Image Translation: Chromosome Straightening Framework by Learning from a Single Image

A Robust Adversarial Network-Based End-to-End Communications System With Strong Generalization Ability Against Adversarial Attacks

Vanishing Twin GAN: How training a weak Generative Adversarial Network can improve semi-supervised image classification

PathGAN: Local Path Planning with Attentive Generative Adversarial Networks

BeCAPTCHA-Mouse: Synthetic Mouse Trajectories and Improved Bot Detection

Road Surface Translation Under Snow-covered and Semantic Segmentation for Snow Hazard Index

Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training

MosAIc: Finding Artistic Connections across Culture with Conditional Image Retrieval

A Novel Adaptive Deep Network for Building Footprint Segmentation

GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences

Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency

Disentangling brain heterogeneity via semi-supervised deep-learning and MRI: dimensional representations of Alzheimer's Disease

A Plug-in Method for Representation Factorization in Connectionist Models

Interpreting the Latent Space of Generative Adversarial Networks using Supervised Learning

Multi-class Generative Adversarial Nets for Semi-supervised Image Classification

Bidirectional Mapping Coupled GAN for Generalized Zero-Shot Learning

Alternating the Population and Control Neural Networks to Solve High-Dimensional Stochastic Mean-Field Games

Making Method of Moments Great Again? -- How can GANs learn distributions

DO-GAN: A Double Oracle Framework for Generative Adversarial Networks

MITNet: GAN Enhanced Magnetic Induction Tomography Based on Complex CNN

Generating 3D structures from a 2D slice with GAN-based dimensionality expansion

On the Existence of Optimal Transport Gradient for Learning Generative Models

Training Federated GANs with Theoretical Guarantees: A Universal Aggregation Approach

Real-World Super-Resolution of Face-Images from Surveillance Cameras

Robust pedestrian detection in thermal imagery using synthesized images

Leveraging Regular Fundus Images for Training UWF Fundus Diagnosis Models via Adversarial Learning and Pseudo-Labeling

System-reliability based multi-ensemble of GAN and one-class joint Gaussian distributions for unsupervised real-time structural health monitoring

RoutingGAN: Routing Age Progression and Regression with Disentangled Learning

Improving Augmentation and Evaluation Schemes for Semantic Image Synthesis

An adaptive artificial neural network-based generative design method for layout designs

A General Framework Combining Generative Adversarial Networks and Mixture Density Networks for Inverse Modeling in Microstructural Materials Design

A Transferable Anti-Forensic Attack on Forensic CNNs Using A Generative Adversarial Network

Continual Learning of Generative Models with Limited Data: From Wasserstein-1 Barycenter to Adaptive Coalescence

Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions

Intelligent Icing Detection Model of Wind Turbine Blades Based on SCADA data

Illuminating the Space of Beatable Lode Runner Levels Produced By Various Generative Adversarial Networks

Detection of Makeup Presentation Attacks based on Deep Face Representations

JigsawGAN: Self-supervised Learning for Solving Jigsaw Puzzles with Generative Adversarial Networks

Galaxy Image Translation with Semi-supervised Noise-reconstructed Generative Adversarial Networks

Fast and accurate learned multiresolution dynamical downscaling for precipitation

High Fidelity Face Manipulation with Extreme Poses and Expressions

Brainstorming Generative Adversarial Networks (BGANs): Towards Multi-Agent Generative Models with Distributed Private Datasets

Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy

Sequential IoT Data Augmentation using Generative Adversarial Networks

Road images augmentation with synthetic traffic signs using neural networks

Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis

Data Augmentation using Generative Adversarial Networks (GANs) for GAN-based Detection of Pneumonia and COVID-19 in Chest X-ray Images

StrokeGAN: Reducing Mode Collapse in Chinese Font Generation via Stroke Encoding

InMoDeGAN: Interpretable Motion Decomposition Generative Adversarial Network for Video Generation

Deep Generative Model for Efficient 3D Airfoil Parameterization and Generation

MIM-Based GAN: Information Metric to Amplify Small Probability Events Importance in Generative Adversarial Networks

OAAE: Adversarial Autoencoders for Novelty Detection in Multi-modal Normality Case via Orthogonalized Latent Space

Minibatch optimal transport distances; analysis and applications

Application-driven Privacy-preserving Data Publishing with Correlated Attributes

FGF-GAN: A Lightweight Generative Adversarial Network for Pansharpening via Fast Guided Filter

LAIF: AI, Deep Learning for Germany Suetterlin Letter Recognition and Generation

Towards Unsupervised Deep Image Enhancement with Generative Adversarial Network

A Differentially Private Multi-Output Deep Generative Networks Approach For Activity Diary Synthesis

Appearance-Invariant 6-DoF Visual Localization using Generative Adversarial Networks

IFGAN: Missing Value Imputation using Feature-specific Generative Adversarial Networks

Dual-encoder Bidirectional Generative Adversarial Networks for Anomaly Detection

Differentially Private Synthetic Medical Data Generation using Convolutional GANs

Double Generative Adversarial Networks for Conditional Independence Testing

Variational Transport: A Convergent Particle-BasedAlgorithm for Distributional Optimization

Understanding Health Misinformation Transmission: An Interpretable Deep Learning Approach to Manage Infodemics

Unsupervised Domain Adaptation with Temporal-Consistent Self-Training for 3D Hand-Object Joint Reconstruction

AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients

PSGAN: A Generative Adversarial Network for Remote Sensing Image Pan-Sharpening

Taking Control of Intra-class Variation in Conditional GANs Under Weak Supervision

Spatial Frequency Bias in Convolutional Generative Adversarial Networks

MangaGAN: Unpaired Photo-to-Manga Translation Based on The Methodology of Manga Drawing

Machine-learned Regularization and Polygonization of Building Segmentation Masks

SimuGAN: Unsupervised forward modeling and optimal design of a LIDAR Camera

GAN Compression: Efficient Architectures for Interactive Conditional GANs

Multi-modal AsynDGAN: Learn From Distributed Medical Image Data without Sharing Private Information

Geometric Surface Image Prediction for Image Recognition Enhancement

CardioGAN: Attentive Generative Adversarial Network with Dual Discriminators for Synthesis of ECG from PPG

Generating Realistic Training Images Based on Tonality-Alignment Generative Adversarial Networks for Hand Pose Estimation

Spectral Unmixing With Multinomial Mixture Kernel and Wasserstein Generative Adversarial Loss

Enhanced 3DMM Attribute Control via Synthetic Dataset Creation Pipeline

A Generative Approach for Detection-driven Underwater Image Enhancement

Super-resolution Guided Pore Detection for Fingerprint Recognition

This Face Does Not Exist ... But It Might Be Yours! Identity Leakage in Generative Models

Differentially Private Synthetic Mixed-Type Data Generation For Unsupervised Learning

Vulnerability Analysis of Face Morphing Attacks from Landmarks and Generative Adversarial Networks

Semi-supervised learning with an open augmenting unknown class for cost-effective training and reliable classifications

VAE-Info-cGAN: Generating Synthetic Images by Combining Pixel-level and Feature-level Geospatial Conditional Inputs

SuperFront: From Low-resolution to High-resolution Frontal Face Synthesis

PFA-GAN: Progressive Face Aging with Generative Adversarial Network

DGGAN: Depth-image Guided Generative Adversarial Networks for Disentangling RGB and Depth Images in 3D Hand Pose Estimation

Semantic Segmentation of Medium-Resolution Satellite Imagery using Conditional Generative Adversarial Networks

On Detecting Data Pollution Attacks On Recommender Systems Using Sequential GANs

Synthesizing Coupled 3D Face Modalities by Trunk-Branch Generative Adversarial Networks

GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution

Multiclass non-Adversarial Image Synthesis, with Application to Classification from Very Small Sample

CycleGAN without checkerboard artifacts for counter-forensics of fake-image detection

Imputation of Missing Data with Class Imbalance using Conditional Generative Adversarial Networks

Generative Adversarial Networks for Image and Video Synthesis: Algorithms and Applications

CIAGAN: Conditional Identity Anonymization Generative Adversarial Networks

Adversarial training for predictive tasks: theoretical analysis and limitations in the deterministic case

Efficient Generation of Structured Objects with Constrained Adversarial Networks

Multi-task GANs for Semantic Segmentation and Depth Completion with Cycle Consistency

Training Generative Adversarial Networks by Solving Ordinary Differential Equations

Manipulating Medical Image Translation with Manifold Disentanglement

Image Embedded Segmentation: Uniting Supervised and Unsupervised Objectives for Segmenting Histopathological Images

Cycle-consistent Generative Adversarial Networks for Neural Style Transfer using data from Chang'E-4

SCGAN: Saliency Map-guided Colorization with Generative Adversarial Network

Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks

Robust Unsupervised Small Area Change Detection from SAR Imagery Using Deep Learning

SalSum: Saliency-based Video Summarization using Generative Adversarial Networks

GAN based ball screw drive picture database enlargement for failure classification

Application of Deep Learning-based Interpolation Methods to Nearshore Bathymetry

Style Intervention: How to Achieve Spatial Disentanglement with Style-based Generators?

Mode Penalty Generative Adversarial Network with adapted Auto-encoder

Population synthesis for urban resident modeling using deep generative models

A GAN-based Approach for Mitigating Inference Attacks in Smart Home Environment

End-to-End Chinese Landscape Painting Creation Using Generative Adversarial Networks

Differentially Private Synthetic Data: Applied Evaluations and Enhancements

Line Art Correlation Matching Feature Transfer Network for Automatic Animation Colorization

Learning to Rank with Missing Data via Generative Adversarial Networks

Real-time Locational Marginal Price Forecasting Using Generative Adversarial Network

MFIF-GAN: A New Generative Adversarial Network for Multi-Focus Image Fusion

Image Clustering using an Augmented Generative Adversarial Network and Information Maximization

Generative Adversarial Networks in Human Emotion Synthesis:A Review

BGGAN: Bokeh-Glass Generative Adversarial Network for Rendering Realistic Bokeh

Accelerated WGAN update strategy with loss change rate balancing

A Novel Semi-Supervised Data-Driven Method for Chiller Fault Diagnosis with Unlabeled Data

An Unsupervised Approach towards Varying Human Skin Tone Using Generative Adversarial Networks

Exploring Generative Adversarial Networks for Image-to-Image Translation in STEM Simulation

Real-time Tropical Cyclone Intensity Estimation by Handling Temporally Heterogeneous Satellite Data

Integration of AI and mechanistic modeling in generative adversarial networks for stochastic inverse problems

Adversarial Feature Hallucination Networks for Few-Shot Learning

xAI-GAN: Enhancing Generative Adversarial Networks via Explainable AI Systems

GIMP-ML: Python Plugins for using Computer Vision Models in GIMP

Restrained Generative Adversarial Network against Overfitting in Numeric Data Augmentation

A Distributed Training Algorithm of Generative Adversarial Networks with Quantized Gradients

Discriminative feature generation for classification of imbalanced data

S2cGAN: Semi-Supervised Training of Conditional GANs with Fewer Labels

Train simultaneously, generalize better: Stability of gradient-based minimax learners

Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad Samples

Cross-Resolution Adversarial Dual Network for Person Re-Identification and Beyond

Novel View Synthesis from only a 6-DoF Camera Pose by Two-stage Networks

Robustness-aware 2-bit quantization with real-time performance for neural network

Encoder-Decoder Generative Adversarial Nets for Suffix Generation and Remaining Time Prediction of Business Process Models

DE-GAN: A Conditional Generative Adversarial Network for Document Enhancement

Semantic Segmentation for Partially Occluded Apple Trees Based on Deep Learning

Exposing GAN-generated Faces Using Inconsistent Corneal Specular Highlights

Augmented Cyclic Consistency Regularization for Unpaired Image-to-Image Translation

MADGAN: unsupervised Medical Anomaly Detection GAN using multiple adjacent brain MRI slice reconstruction

ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems

Generative Adversarial Networks (GANs): Challenges, Solutions, and Future Directions

Speech2Video Synthesis with 3D Skeleton Regularization and Expressive Body Poses

A cost-effective method for improving and re-purposing large, pre-trained GANs by fine-tuning their class-embeddings

MatchGAN: A Self-Supervised Semi-Supervised Conditional Generative Adversarial Network

Training GANs with predictive projection centripetal acceleration

On the Evaluation of Generative Adversarial Networks By Discriminative Models

Using Conditional Generative Adversarial Networks to Reduce the Effects of Latency in Robotic Telesurgery

DML-GANR: Deep Metric Learning With Generative Adversarial Network Regularization for High Spatial Resolution Remote Sensing Image Retrieval

Providing Actionable Feedback in Hiring Marketplaces using Generative Adversarial Networks

Multi-level Feature Learning on Embedding Layer of Convolutional Autoencoders and Deep Inverse Feature Learning for Image Clustering

Sample weighting as an explanation for mode collapse in generative adversarial networks

Image Counterfactual Sensitivity Analysis for Detecting Unintended Bias

MagGAN: High-Resolution Face Attribute Editing with Mask-Guided Generative Adversarial Network

Evaluating a Generative Adversarial Framework for Information Retrieval

3D Dense Geometry-Guided Facial Expression Synthesis by Adversarial Learning

Bilateral Asymmetry Guided Counterfactual Generating Network for Mammogram Classification

iSeeBetter: Spatio-temporal video super-resolution using recurrent generative back-projection networks

imdpGAN: Generating Private and Specific Data with Generative Adversarial Networks

Flexible Example-based Image Enhancement with Task Adaptive Global Feature Self-Guided Network

PhishGAN: Data Augmentation and Identification of Homoglpyh Attacks

GANs with Variational Entropy Regularizers: Applications in Mitigating the Mode-Collapse Issue

SLGAN: Style- and Latent-guided Generative Adversarial Network for Desirable Makeup Transfer and Removal

Topology-Aware Generative Adversarial Network for Joint Prediction of Multiple Brain Graphs from a Single Brain Graph

A Generative Adversarial Approach with Residual Learning for Dust and Scratches Artifacts Removal

Informative Sample Mining Network for Multi-Domain Image-to-Image Translation

Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images

To Regularize or Not To Regularize? The Bias Variance Trade-off in Regularized AEs

Graph representation forecasting of patient's medical conditions: towards a digital twin

Vax-a-Net: Training-time Defence Against Adversarial Patch Attacks

Robust Cross-View Gait Recognition with Evidence: A Discriminant Gait GAN (DiGGAN) Approach

Crossing You in Style: Cross-modal Style Transfer from Music to Visual Arts

Consistency Regularization with Generative Adversarial Networks for Semi-Supervised Learning

Improving Inversion and Generation Diversity in StyleGAN using a Gaussianized Latent Space

Symmetric Skip Connection Wasserstein GAN for High-Resolution Facial Image Inpainting

Progressive Perception-Oriented Network for Single Image Super-Resolution

Accurate and Intuitive Contextual Explanations using Linear Model Trees

Conditional Coupled Generative Adversarial Networks for Zero-Shot Domain Adaptation

MU-GAN: Facial Attribute Editing based on Multi-attention Mechanism

Multilinear Latent Conditioning for Generating Unseen Attribute Combinations

3D Facial Geometry Recovery from a Depth View with Attention Guided Generative Adversarial Network

Optimal Transport driven CycleGAN for Unsupervised Learning in Inverse Problems

Generalizing Energy-based Generative ConvNets from Particle Evolution Perspective

Single Image Haze Removal using a Generative Adversarial Network

A Variational Inequality Perspective on Generative Adversarial Networks

PCA-SRGAN: Incremental Orthogonal Projection Discrimination for Face Super-resolution

Crossing-Domain Generative Adversarial Networks for Unsupervised Multi-Domain Image-to-Image Translation

Cross-Spectral Periocular Recognition with Conditional Adversarial Networks

GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework

Joint Face Completion and Super-resolution using Multi-scale Feature Relation Learning

CnGAN: Generative Adversarial Networks for Cross-network user preference generation for non-overlapped users

Symbiotic Adversarial Learning for Attribute-based Person Search

Inclusive GAN: Improving Data and Minority Coverage in Generative Models

Symbolic Semantic Segmentation and Interpretation of COVID-19 Lung Infections in Chest CT volumes based on Emergent Languages

Conditional Wasserstein GAN-based Oversampling of Tabular Data for Imbalanced Learning

Autoencoders and Generative Adversarial Networks for Imbalanced Sequence Classification

Bayesian Cycle-Consistent Generative Adversarial Networks via Marginalizing Latent Sampling

Synthesizing Property & Casualty Ratemaking Datasets using Generative Adversarial Networks

Recurrent Deconvolutional Generative Adversarial Networks with Application to Text Guided Video Generation

Modeling Caricature Expressions by 3D Blendshape and Dynamic Texture

Mitigating Dataset Imbalance via Joint Generation and Classification

Improving the Performance of Fine-Grain Image Classifiers via Generative Data Augmentation

InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs

Oversampling Adversarial Network for Class-Imbalanced Fault Diagnosis

A feature-supervised generative adversarial network for environmental monitoring during hazy days

A Generic and Model-Agnostic Exemplar Synthetization Framework for Explainable AI

Multimodal Image-to-Image Translation via a Single Generative Adversarial Network

Blending Generative Adversarial Image Synthesis with Rendering for Computer Graphics

Unsupervised Disentanglement GAN for Domain Adaptive Person Re-Identification

Generalization Properties of Optimal Transport GANs with Latent Distribution Learning

Translate the Facial Regions You Like Using Region-Wise Normalization

A Deep Learning Framework for Generation and Analysis of Driving Scenario Trajectories

Improving Generative Adversarial Networks with Local Coordinate Coding

3DMaterialGAN: Learning 3D Shape Representation from Latent Space for Materials Science Applications

WGANVO: Monocular Visual Odometry based on Generative Adversarial Networks

C-MI-GAN : Estimation of Conditional Mutual Information using MinMax formulation

Unsupervised Learning of Solutions to Differential Equations with Generative Adversarial Networks

Training Deep Energy-Based Models with f-Divergence Minimization

Statistical Guarantees of Generative Adversarial Networks for Distribution Estimation

RGB-IR Cross-modality Person ReID based on Teacher-Student GAN Model

Lessons Learned from the Training of GANs on Artificial Datasets

Invertible generative models for inverse problems: mitigating representation error and dataset bias

CPGAN: Full-Spectrum Content-Parsing Generative Adversarial Networks for Text-to-Image Synthesis

PA-GAN: Progressive Attention Generative Adversarial Network for Facial Attribute Editing

Exponential Convergence of Gradient Methods in Concave Network Zero-sum Games

Words as Art Materials: Generating Paintings with Sequential GANs

The UU-Net: Reversible Face De-Identification for Visual Surveillance Video Footage

Multimodal Shape Completion via Conditional Generative Adversarial Networks

Understanding and Stabilizing GANs' Training Dynamics with Control Theory

Can GAN Generated Morphs Threaten Face Recognition Systems Equally as Landmark Based Morphs? -- Vulnerability and Detection

AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks

RDP-GAN: A Rényi-Differential Privacy based Generative Adversarial Network

Age-Oriented Face Synthesis with Conditional Discriminator Pool and Adversarial Triplet Loss

A Semi-Supervised Generative Adversarial Network for Prediction of Genetic Disease Outcomes

GANprintR: Improved Fakes and Evaluation of the State of the Art in Face Manipulation Detection

Estimation with Uncertainty via Conditional Generative Adversarial Networks

Reducing Noise in GAN Training with Variance Reduced Extragradient

Ensembles of Generative Adversarial Networks for Disconnected Data

Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities

Recurrent Relational Memory Network for Unsupervised Image Captioning

PoseGAN: A Pose-to-Image Translation Framework for Camera Localization

Measuring Performance of Generative Adversarial Networks on Devanagari Script

Semantically Tied Paired Cycle Consistency for Any-Shot Sketch-based Image Retrieval

Domain Embedded Multi-model Generative Adversarial Networks for Image-based Face Inpainting

DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection

MMCGAN: Generative Adversarial Network with Explicit Manifold Prior

GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models

ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping

BatVision with GCC-PHAT Features for Better Sound to Vision Predictions

Classify and Generate Reciprocally: Simultaneous Positive-Unlabelled Learning and Conditional Generation with Extra Data

MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks

Rethinking Sampling in 3D Point Cloud Generative Adversarial Networks

Improving Movement Predictions of Traffic Actors in Bird's-Eye View Models using GANs and Differentiable Trajectory Rasterization

TG-GAN: Continuous-time Temporal Graph Generation with Deep Generative Models

FakeLocator: Robust Localization of GAN-Based Face Manipulations

A Survey on Generative Adversarial Networks: Variants, Applications, and Training

FA-GANs: Facial Attractiveness Enhancement with Generative Adversarial Networks on Frontal Faces

Generation of Differentially Private Heterogeneous Electronic Health Records

Multiple Generative Adversarial Networks Analysis for Predicting Photographers' Retouching

From Real to Synthetic and Back: Synthesizing Training Data for Multi-Person Scene Understanding

Train Sparsely, Generate Densely: Memory-efficient Unsupervised Training of High-resolution Temporal GAN

StressGAN: A Generative Deep Learning Model for 2D Stress Distribution Prediction

Sparsely Grouped Multi-task Generative Adversarial Networks for Facial Attribute Manipulation

CGGAN: A Context Guided Generative Adversarial Network For Single Image Dehazing

Regularized Cycle Consistent Generative Adversarial Network for Anomaly Detection

Generative Adversarial Networks (GANs): An Overview of Theoretical Model, Evaluation Metrics, and Recent Developments

City-GAN: Learning architectural styles using a custom Conditional GAN architecture

SEAN: Image Synthesis with Semantic Region-Adaptive Normalization

AnimGAN: A Spatiotemporally-Conditioned Generative Adversarial Network for Character Animation

MBA-RainGAN: Multi-branch Attention Generative Adversarial Network for Mixture of Rain Removal from Single Images

MaskAAE: Latent space optimization for Adversarial Auto-Encoders

Lane Detection in Low-light Conditions Using an Efficient Data Enhancement : Light Conditions Style Transfer

Disentangled Inference for GANs with Latently Invertible Autoencoder

Token Manipulation Generative Adversarial Network for Text Generation

Fine-Grained Expression Manipulation via Structured Latent Space

Recent Developments Combining Ensemble Smoother and Deep Generative Networks for Facies History Matching

Multi-Modality Generative Adversarial Networks with Tumor Consistency Loss for Brain MR Image Synthesis

An Efficient Integration of Disentangled Attended Expression and Identity FeaturesFor Facial Expression Transfer andSynthesis

MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking

Unifying Neural Learning and Symbolic Reasoning for Spinal Medical Report Generation

EM-GAN: Fast Stress Analysis for Multi-Segment Interconnect Using Generative Adversarial Networks

Disrupting Deepfakes: Adversarial Attacks Against Conditional Image Translation Networks and Facial Manipulation Systems

A Closer Look at the Optimization Landscapes of Generative Adversarial Networks

PF-cpGAN: Profile to Frontal Coupled GAN for Face Recognition in the Wild

Prominent Attribute Modification using Attribute Dependent Generative Adversarial Network

Stabilizing Training of Generative Adversarial Nets via Langevin Stein Variational Gradient Descent

Is Supervised Learning With Adversarial Features Provably Better Than Sole Supervision?

TriGAN: Image-to-Image Translation for Multi-Source Domain Adaptation

The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks

YuruGAN: Yuru-Chara Mascot Generator Using Generative Adversarial Networks With Clustering Small Dataset

Generative Adversarial Networks for Video-to-Video Domain Adaptation

D-SRGAN: DEM Super-Resolution with Generative Adversarial Networks

Adversarial Variational Optimization of Non-Differentiable Simulators

Composite Travel Generative Adversarial Networks for Tabular and Sequential Population Synthesis

Semi-supervised Image Attribute Editing using Generative Adversarial Networks

Imbalanced Data Learning by Minority Class Augmentation using Capsule Adversarial Networks

Bridging the gap between AI and Healthcare sides: towards developing clinically relevant AI-powered diagnosis systems

Theoretical Insights into the Use of Structural Similarity Index In Generative Models and Inferential Autoencoders

The equivalence between Stein variational gradient descent and black-box variational inference

Predictive Business Process Monitoring via Generative Adversarial Nets: The Case of Next Event Prediction

Learning Generative Models of Tissue Organization with Supervised GANs

AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"

FusedProp: Towards Efficient Training of Generative Adversarial Networks

Physics-Based Generative Adversarial Models for Image Restoration and Beyond

Plausible Counterfactuals: Auditing Deep Learning Classifiers with Realistic Adversarial Examples

Towards Real-Time Advancement of Underwater Visual Quality with GAN

Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance

Generating Electronic Health Records with Multiple Data Types and Constraints

On Catastrophic Forgetting and Mode Collapse in Generative Adversarial Networks

Palm-GAN: Generating Realistic Palmprint Images Using Total-Variation Regularized GAN

Predicting Real-Time Locational Marginal Prices: A GAN-Based Video Prediction Approach

Teacher-Student Compression with Generative Adversarial Networks

PiiGAN: Generative Adversarial Networks for Pluralistic Image Inpainting

AMIL: Adversarial Multi Instance Learning for Human Pose Estimation

House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation

Vec2Face: Unveil Human Faces from their Blackbox Features in Face Recognition

History-based Anomaly Detector: an Adversarial Approach to Anomaly Detection

From W-Net to CDGAN: Bi-temporal Change Detection via Deep Learning Techniques

SynCGAN: Using learnable class specific priors to generate synthetic data for improving classifier performance on cytological images

Image-based model parameter optimization using Model-Assisted Generative Adversarial Networks

Motion Corrected Multishot MRI Reconstruction Using Generative Networks with Sensitivity Encoding

Super Resolution Using Segmentation-Prior Self-Attention Generative Adversarial Network

MRI Super-Resolution with GAN and 3D Multi-Level DenseNet: Smaller, Faster, and Better

Triple Memory Networks: a Brain-Inspired Method for Continual Learning

The GAN that Warped: Semantic Attribute Editing with Unpaired Data

Robust Conditional GAN from Uncertainty-Aware Pairwise Comparisons

CorGAN: Correlation-Capturing Convolutional Generative Adversarial Networks for Generating Synthetic Healthcare Records

Discriminator Feature-based Inference by Recycling the Discriminator of GANs

Generating Higher-Fidelity Synthetic Datasets with Privacy Guarantees

Topology Distance: A Topology-Based Approach For Evaluating Generative Adversarial Networks

A Mean-Field Theory for Kernel Alignment with Random Features in Generative and Discriminative Models

Subsampling Generative Adversarial Networks: Density Ratio Estimation in Feature Space with Softplus Loss

NAttack! Adversarial Attacks to bypass a GAN based classifier trained to detect Network intrusion

SD-GAN: Structural and Denoising GAN reveals facial parts under occlusion

Full-Scale Continuous Synthetic Sonar Data Generation with Markov Conditional Generative Adversarial Networks

DomainGAN: Generating Adversarial Examples to Attack Domain Generation Algorithm Classifiers

GANILLA: Generative Adversarial Networks for Image to Illustration Translation

Anomaly Detection in Particulate Matter Sensor using Hypothesis Pruning Generative Adversarial Network

SetGAN: Improving the stability and diversity of generative models through a permutation invariant architecture

GAC-GAN: A General Method for Appearance-Controllable Human Video Motion Transfer

Memory Augmented Generative Adversarial Networks for Anomaly Detection

Object-Adaptive LSTM Network for Real-time Visual Tracking with Adversarial Data Augmentation

Using generative adversarial networks to synthesize artificial financial datasets

Joint Deep Learning of Facial Expression Synthesis and Recognition

Unbalanced GANs: Pre-training the Generator of Generative Adversarial Network using Variational Autoencoder

Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation

Sparse-GAN: Sparsity-constrained Generative Adversarial Network for Anomaly Detection in Retinal OCT Image

Yes, we GAN: Applying Adversarial Techniques for Autonomous Driving

DP-CGAN: Differentially Private Synthetic Data and Label Generation

Generating Natural Adversarial Hyperspectral examples with a modified Wasserstein GAN

On the Role of Receptive Field in Unsupervised Sim-to-Real Image Translation

Information Compensation for Deep Conditional Generative Networks

Universal Data Anomaly Detection via Inverse Generative Adversary Network

Interpreting Galaxy Deblender GAN from the Discriminator's Perspective

Learning to Augment Expressions for Few-shot Fine-grained Facial Expression Recognition

A Method for Estimating Reflectance map and Material using Deep Learning with Synthetic Dataset

Physics Informed Deep Learning for Transport in Porous Media. Buckley Leverett Problem

Identifying Table Structure in Documents using Conditional Generative Adversarial Networks

Multi-source Domain Adaptation for Visual Sentiment Classification

microbatchGAN: Stimulating Diversity with Multi-Adversarial Discrimination

Generative Pseudo-label Refinement for Unsupervised Domain Adaptation

Towards Realistic Face Photo-Sketch Synthesis via Composition-Aided GANs

Bayesian Inversion Of Generative Models For Geologic Storage Of Carbon Dioxide

Bi-Semantic Reconstructing Generative Network for Zero-shot Learning

Oversampling Log Messages Using a Sequence Generative Adversarial Network for Anomaly Detection and Classification

FFusionCGAN: An end-to-end fusion method for few-focus images using conditional GAN in cytopathological digital slides

Harnessing GANs for Zero-shot Learning of New Classes in Visual Speech Recognition

TomoGAN: Low-Dose Synchrotron X-Ray Tomography with Generative Adversarial Networks

PMC-GANs: Generating Multi-Scale High-Quality Pedestrian with Multimodal Cascaded GANs

Translating multispectral imagery to nighttime imagery via conditional generative adversarial networks

A single target tracking algorithm based on Generative Adversarial Networks

PI-GAN: Learning Pose Independent representations for multiple profile face synthesis

Barycenters of Natural Images -- Constrained Wasserstein Barycenters for Image Morphing

Joint Face Super-Resolution and Deblurring Using a Generative Adversarial Network

Conditional Independence Testing using Generative Adversarial Networks

Facial Synthesis from Visual Attributes via Sketch using Multi-Scale Generators

Predicting the Future: A Jointly Learnt Model for Action Anticipation

Asymmetric Generative Adversarial Networks for Image-to-Image Translation

Region and Object based Panoptic Image Synthesis through Conditional GANs

Interpretable Deep Neural Networks for Facial Expression and Dimensional Emotion Recognition in-the-wild

Bias Remediation in Driver Drowsiness Detection systems using Generative Adversarial Networks

Environment reconstruction on depth images using Generative Adversarial Networks

Truly Generalizable Radiograph Segmentation with Conditional Domain Adaptation

Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models

Learning from Label Proportions with Generative Adversarial Networks

Face Completion with Semantic Knowledge and Collaborative Adversarial Learning

CONAN: Complementary Pattern Augmentation for Rare Disease Detection

AuthorGAN: Improving GAN Reproducibility using a Modular GAN Framework

Using Physics-Informed Super-Resolution Generative Adversarial Networks for Subgrid Modeling in Turbulent Reactive Flows

Text2FaceGAN: Face Generation from Fine Grained Textual Descriptions

Invert and Defend: Model-based Approximate Inversion of Generative Adversarial Networks for Secure Inference

Synthesizing Visual Illusions Using Generative Adversarial Networks

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach

Towards Ghost-free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GAN

Medical Image Super-Resolution Using a Generative Adversarial Network

Unsupervised Learning of Anomaly Detection from Contaminated Image Data using Simultaneous Encoder Training

Photo-Realistic Monocular Gaze Redirection Using Generative Adversarial Networks

SimVAE: Simulator-Assisted Training forInterpretable Generative Models

AdvSPADE: Realistic Unrestricted Attacks for Semantic Segmentation

MMGAN: Generative Adversarial Networks for Multi-Modal Distributions

LiDAR ICPS-net: Indoor Camera Positioning based-on Generative Adversarial Network for RGB to Point-Cloud Translation

Generative adversarial networks (GAN) based efficient sampling of chemical space for inverse design of inorganic materials

PoshakNet: Framework for matching dresses from real-life photos using GAN and Siamese Network

Learning Feature-to-Feature Translator by Alternating Back-Propagation for Generative Zero-Shot Learning

Biconditional Generative Adversarial Networks for Multiview Learning with Missing Views

BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling

Kernel-Guided Training of Implicit Generative Models with Stability Guarantees

FCSR-GAN: Joint Face Completion and Super-resolution via Multi-task Learning

Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting

A Method for Identifying Origin of Digital Images Using a Convolution Neural Network

Learning Disentangled Representation for Robust Person Re-identification

Investigating Under and Overfitting in Wasserstein Generative Adversarial Networks

A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models

Exploiting GAN Internal Capacity for High-Quality Reconstruction of Natural Images

Implicit Posterior Variational Inference for Deep Gaussian Processes

Injective State-Image Mapping facilitates Visual Adversarial Imitation Learning

Look globally, age locally: Face aging with an attention mechanism

GAN-based Projector for Faster Recovery with Convergence Guarantees in Linear Inverse Problems

Facial Expression Restoration Based on Improved Graph Convolutional Networks

Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network

Exploring Explicit Domain Supervision for Latent Space Disentanglement in Unpaired Image-to-Image Translation

A Cost Effective Solution for Road Crack Inspection using Cameras and Deep Neural Networks

A Survey and Taxonomy of Adversarial Neural Networks for Text-to-Image Synthesis

Improved Deep Spectral Convolution Network For Hyperspectral Unmixing With Multinomial Mixture Kernel and Endmember Uncertainty

LinesToFacePhoto: Face Photo Generation from Lines with Conditional Self-Attention Generative Adversarial Network

Correlation Maximized Structural Similarity Loss for Semantic Segmentation

Adversarial Regression. Generative Adversarial Networks for Non-Linear Regression: Theory and Assessment

Semi-supervised Learning using Adversarial Training with Good and Bad Samples

Restoration of marker occluded hematoxylin and eosin stained whole slide histology images using generative adversarial networks

Facial Expression Recognition Using Human to Animated-Character Expression Translation

Complement Face Forensic Detection and Localization with FacialLandmarks

Illegible Text to Readable Text: An Image-to-Image Transformation using Conditional Sliced Wasserstein Adversarial Networks

Comparison of Generative Adversarial Networks Architectures Which Reduce Mode Collapse

Unconstrained Road Marking Recognition with Generative Adversarial Networks

Unsupervised Projection Networks for Generative Adversarial Networks

Stein Bridging: Enabling Mutual Reinforcement between Explicit and Implicit Generative Models

Illumination Invariant Foreground Object Segmentation using ForeGANs

Generating Relevant Counter-Examples from a Positive Unlabeled Dataset for Image Classification

Adversarial Colorization Of Icons Based On Structure And Color Conditions

How is Gaze Influenced by Image Transformations? Dataset and Model

Detecting GAN generated Fake Images using Co-occurrence Matrices

On the estimation of the Wasserstein distance in generative models

Ward2ICU: A Vital Signs Dataset of Inpatients from the General Ward

HoloGAN: Unsupervised learning of 3D representations from natural images

ColorMapGAN: Unsupervised Domain Adaptation for Semantic Segmentation Using Color Mapping Generative Adversarial Networks

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection

Generating Geological Facies Models with Fidelity to Diversity and Statistics of Training Images using Improved Generative Adversarial Networks

Predicting Landscapes from Environmental Conditions Using Generative Networks

Memory Replay GANs: learning to generate images from new categories without forgetting

LoGANv2: Conditional Style-Based Logo Generation with Generative Adversarial Networks

Fine-grained Action Segmentation using the Semi-Supervised Action GAN

Deeply Matting-based Dual Generative Adversarial Network for Image and Document Label Supervision

Identity-Aware Deep Face Hallucination via Adversarial Face Verification

Prediction of rare feature combinations in population synthesis: Application of deep generative modelling

k-Same-Siamese-GAN: k-Same Algorithm with Generative Adversarial Network for Facial Image De-identification with Hyperparameter Tuning and Mixed Precision Training

Generating Realistic Sequences of Customer-level Transactions for Retail Datasets

GAN-Tree: An Incrementally Learned Hierarchical Generative Framework for Multi-Modal Data Distributions

Dilated Temporal Relational Adversarial Network for Generic Video Summarization

How Old Are You? Face Age Translation with Identity Preservation Using GANs

DeepPrivacy: A Generative Adversarial Network for Face Anonymization

Face De-occlusion using 3D Morphable Model and Generative Adversarial Network

IterGANs: Iterative GANs to Learn and Control 3D Object Transformation

Generalizing semi-supervised generative adversarial networks to regression using feature contrasting

High-Resolution Mammogram Synthesis using Progressive Generative Adversarial Networks

Self-Ensembling with GAN-based Data Augmentation for Domain Adaptation in Semantic Segmentation

Attention-Guided Generative Adversarial Networks for Unsupervised Image-to-Image Translation

Super-Resolved Image Perceptual Quality Improvement via Multi-Feature Discriminators

SliderGAN: Synthesizing Expressive Face Images by Sliding 3D Blendshape Parameters

RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-Resolution

SBSGAN: Suppression of Inter-Domain Background Shift for Person Re-Identification

Learning More with Less: Conditional PGGAN-based Data Augmentation for Brain Metastases Detection Using Highly-Rough Annotation on MR Images

A Realistic Face-to-Face Conversation System based on Deep Neural Networks

Towards Photo-Realistic Visible Watermark Removal with Conditional Generative Adversarial Networks

Generative Adversarial Networks for Extreme Learned Image Compression

Applying Adversarial Auto-encoder for Estimating Human Walking Gait Abnormality Index

Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints

Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification

See Clearer at Night: Towards Robust Nighttime Semantic Segmentation through Day-Night Image Conversion

Structured Coupled Generative Adversarial Networks for Unsupervised Monocular Depth Estimation

HorNet: A Hierarchical Offshoot Recurrent Network for Improving Person Re-ID via Image Captioning

Super-resolution of Omnidirectional Images Using Adversarial Learning

PCGAN-CHAR: Progressively Trained Classifier Generative Adversarial Networks for Classification of Noisy Handwritten Bangla Characters

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition

DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better

Unpaired image denoising using a generative adversarial network in X-ray CT

Attribute-Guided Coupled GAN for Cross-Resolution Face Recognition

ARGAN: Attentive Recurrent Generative Adversarial Network for Shadow Detection and Removal

Scalable Unbalanced Optimal Transport using Generative Adversarial Networks

On the Veracity of Cyber Intrusion Alerts Synthesized by Generative Adversarial Networks

Low-Dose CT via Deep CNN with Skip Connection and Network in Network

Content and Colour Distillation for Learning Image Translations with the Spatial Profile Loss

Gesture-to-Gesture Translation in the Wild via Category-Independent Conditional Maps

Generative Adversarial Networks (GANs): What it can generate and What it cannot?

Attribute-Guided Deep Polarimetric Thermal-to-visible Face Recognition

DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesis

Y-Autoencoders: disentangling latent representations via sequential-encoding

A Fine-Grained Facial Expression Database for End-to-End Multi-Pose Facial Expression Recognition

Spatial sensitivity analysis for urban land use prediction with physics-constrained conditional generative adversarial networks

Adversarial Feature Learning of Online Monitoring Data for Operational Risk Assessment in Distribution Networks

Cross-view image synthesis using geometry-guided conditional GANs

Design and Evaluation of Product Aesthetics: A Human-Machine Hybrid Approach

Data augmentation with Symbolic-to-Real Image Translation GANs for Traffic Sign Recognition

Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks

Deep Neural Network Augmentation: Generating Faces for Affect Analysis

Parametric generation of conditional geological realizations using generative neural networks

Unsupervised Adversarial Attacks on Deep Feature-based Retrieval with GAN

Dual Adversarial Semantics-Consistent Network for Generalized Zero-Shot Learning

Unsupervised Domain Alignment to Mitigate Low Level Dataset Biases

M3D-GAN: Multi-Modal Multi-Domain Translation with Universal Attention

k-GANs: Ensemble of Generative Models with Semi-Discrete Optimal Transport

Unified Attentional Generative Adversarial Network for Brain Tumor Segmentation From Multimodal Unpaired Images

Improving Detection of Credit Card Fraudulent Transactions using Generative Adversarial Networks

Incremental Concept Learning via Online Generative Memory Recall

Mask Embedding in conditional GAN for Guided Synthesis of High Resolution Images

Disentangled Makeup Transfer with Generative Adversarial Network

Towards a Better Understanding and Regularization of GAN Training Dynamics

One Network for Multi-Domains: Domain Adaptive Hashing with Intersectant Generative Adversarial Network

Example-Guided Style Consistent Image Synthesis from Semantic Labeling

Follow the Attention: Combining Partial Pose and Object Motion for Fine-Grained Action Detection

Generating User-friendly Explanations for Loan Denials using GANs

GANalyze: Toward Visual Definitions of Cognitive Image Properties

An Adversarial Super-Resolution Remedy for Radar Design Trade-offs

Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks

Low-light Image Enhancement Algorithm Based on Retinex and Generative Adversarial Network

Improving Prediction Accuracy in Building Performance Models Using Generative Adversarial Networks (GANs)

DeepFlow: History Matching in the Space of Deep Generative Models

Inferring 3D Shapes from Image Collections using Adversarial Networks

Synthesizing 3D Shapes from Silhouette Image Collections using Multi-projection Generative Adversarial Networks

Metropolis-Hastings view on variational inference and adversarial training

How to make a pizza: Learning a compositional layer-based GAN model

Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs

PAC-GAN: An Effective Pose Augmentation Scheme for Unsupervised Cross-View Person Re-identification

Y-GAN: A Generative Adversarial Network for Depthmap Estimation from Multi-camera Stereo Images

GazeCorrection:Self-Guided Eye Manipulation in the wild using Self-Supervised Generative Adversarial Networks

Generative Adversarial Networks for Operational Scenario Planning of Renewable Energy Farms: A Study on Wind and Photovoltaic

Image De-raining Using a Conditional Generative Adversarial Network

GANchors: Realistic Image Perturbation Distributions for Anchors Using Generative Models

Graph-based Discriminators: Sample Complexity and Expressiveness

GlyphGAN: Style-Consistent Font Generation Based on Generative Adversarial Networks

G2R Bound: A Generalization Bound for Supervised Learning from GAN-Synthetic Data

HexaGAN: Generative Adversarial Nets for Real World Classification

FCC-GAN: A Fully Connected and Convolutional Net Architecture for GANs

Cross-Resolution Face Recognition via Prior-Aided Face Hallucination and Residual Knowledge Distillation

CrystalGAN: Learning to Discover Crystallographic Structures with Generative Adversarial Networks

Generative Adversarial Networks for Mitigating Biases in Machine Learning Systems

A Direct Approach to Robust Deep Learning Using Adversarial Networks

Attributes Guided Feature Learning for Vehicle Re-identification

Domain Adaptation for Vehicle Detection from Bird's Eye View LiDAR Point Cloud Data

Toward Learning a Unified Many-to-Many Mapping for Diverse Image Translation

Deep Generative Design: Integration of Topology Optimization and Generative Models

Global Convergence to the Equilibrium of GANs using Variational Inequalities

DC-AL GAN: Pseudoprogression and True Tumor Progression of Glioblastoma Multiform Image Classification Based on DCGAN and AlexNet

Transferring Multiscale Map Styles Using Generative Adversarial Networks

Estimation of Tissue Oxygen Saturation from RGB images and Sparse Hyperspectral Signals based on Conditional Generative Adversarial Network

Deep Learning based Pedestrian Detection at Distance in Smart Cities

FH-GAN: Face Hallucination and Recognition using Generative Adversarial Network

ReshapeGAN: Object Reshaping by Providing A Single Reference Image

3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions

3D Semantic Scene Completion from a Single Depth Image using Adversarial Training

Game Theoretic Optimization via Gradient-based Nikaido-Isoda Function

Towards Automated Melanoma Detection with Deep Learning: Data Purification and Augmentation

CoT: Cooperative Training for Generative Modeling of Discrete Data

Flat Metric Minimization with Applications in Generative Modeling

Unsupervised Domain Adaptation using Generative Adversarial Networks for Semantic Segmentation of Aerial Images

Automatic Video Colorization using 3D Conditional Generative Adversarial Networks

Adversarial Variational Embedding for Robust Semi-supervised Learning

Out-of-Distribution Detection for Generalized Zero-Shot Action Recognition

Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis

Conditional WGANs with Adaptive Gradient Balancing for Sparse MRI Reconstruction

Quality Evaluation of GANs Using Cross Local Intrinsic Dimensionality

Informative sample generation using class aware generative adversarial networks for classification of chest Xrays

Adversarial Networks and Autoencoders: The Primal-Dual Relationship and Generalization Bounds

End-to-End Adversarial Learning for Intrusion Detection in Computer Networks

Semi-Supervised Multitask Learning on Multispectral Satellite Images Using Wasserstein Generative Adversarial Networks (GANs) for Predicting Poverty

GeoGAN: A Conditional GAN with Reconstruction and Style Loss to Generate Standard Layer of Maps from Satellite Images

Social Ways: Learning Multi-Modal Distributions of Pedestrian Trajectories with GANs

User-Controllable Multi-Texture Synthesis with Generative Adversarial Networks

Generative adversarial interpolative autoencoding: adversarial training on latent space interpolations encourage convex latent distributions

STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing

Everyone is a Cartoonist: Selfie Cartoonization with Attentive Adversarial Networks

Conditional GANs for Multi-Illuminant Color Constancy: Revolution or Yet Another Approach?

Three dimensional blind image deconvolution for fluorescence microscopy using generative adversarial networks

An Introduction to Person Re-identification with Generative Adversarial Networks

Cycle-SUM: Cycle-consistent Adversarial LSTM Networks for Unsupervised Video Summarization

Downhole Track Detection via Multiscale Conditional Generative Adversarial Nets

IAN: Combining Generative Adversarial Networks for Imaginative Face Generation

Polarimetric Thermal to Visible Face Verification via Self-Attention Guided Synthesis

A deep learning framework for quality assessment and restoration in video endoscopy

SR-GAN: Semantic Rectifying Generative Adversarial Network for Zero-shot Learning

Attribute-aware Face Aging with Wavelet-based Generative Adversarial Networks

Predicting Novel Views Using Generative Adversarial Query Network

Generating Diffusion MRI scalar maps from T1 weighted images using generative adversarial networks

Parametrization of stochastic inputs using generative adversarial networks with application in geology

Parametrization and generation of geological models with generative adversarial networks

An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection

Show, Attend and Translate: Unpaired Multi-Domain Image-to-Image Translation with Visual Attention

Latent Filter Scaling for Multimodal Unsupervised Image-to-Image Translation

GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction

Generalizing Fingerprint Spoof Detector: Learning a One-Class Classifier

Gated-GAN: Adversarial Gated Networks for Multi-Collection Style Transfer

Unpaired Thermal to Visible Spectrum Transfer using Adversarial Training

DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-Image Synthesis

Towards Efficient and Unbiased Implementation of Lipschitz Continuity in GANs

End-to-End Time-Lapse Video Synthesis from a Single Outdoor Image

Person Re-identification with Bias-controlled Adversarial Training

Infinite Brain MR Images: PGGAN-based Data Augmentation for Tumor Detection

Snore-GANs: Improving Automatic Snore Sound Classification with Synthesized Data

Auto-Embedding Generative Adversarial Networks for High Resolution Image Synthesis

Compositional GAN: Learning Image-Conditional Binary Composition

Hierarchical Attention Generative Adversarial Networks for Cross-domain Sentiment Classification

PI-REC: Progressive Image Reconstruction Network With Edge and Color Domain

Mode matching in GANs through latent space learning and inversion

Stratified Labeling for Surface Consistent Parallax Correction and Occlusion Completion

FD-GAN: Face-demorphing generative adversarial network for restoring accomplice's facial image

Cross Domain Knowledge Transfer for Unsupervised Vehicle Re-identification

Bilinear Representation for Language-based Image Editing Using Conditional Generative Adversarial Networks

Generating Adversarial Examples With Conditional Generative Adversarial Net

Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network

Generating Diverse and Accurate Visual Captions by Comparative Adversarial Learning

DSM Building Shape Refinement from Combined Remote Sensing Images based on Wnet-cGANs

A Three-Player GAN: Generating Hard Samples To Improve Classification Networks

DepthwiseGANs: Fast Training Generative Adversarial Networks for Realistic Image Synthesis

O-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks

GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks

SEGAN: Structure-Enhanced Generative Adversarial Network for Compressed Sensing MRI Reconstruction

Matching Thermal to Visible Face Images Using a Semantic-Guided Generative Adversarial Network

Single Image Haze Removal Using Conditional Wasserstein Generative Adversarial Networks

Adversarial Generation of Handwritten Text Images Conditioned on Sequences

Lung CT Imaging Sign Classification through Deep Learning on Small Data

Two-phase Hair Image Synthesis by Self-Enhancing Generative Model

Comparison of Patch-Based Conditional Generative Adversarial Neural Net Models with Emphasis on Model Robustness for Use in Head and Neck Cases for MR-Only planning

Frame Interpolation with Multi-Scale Deep Loss Functions and Generative Adversarial Networks

Void Filling of Digital Elevation Models with Deep Generative Models

Realistic Ultrasonic Environment Simulation Using Conditional Generative Adversarial Networks

BoostGAN for Occlusive Profile Face Frontalization and Recognition

Large Scale GAN Training for High Fidelity Natural Image Synthesis

MisGAN: Learning from Incomplete Data with Generative Adversarial Networks

Adversarial Learning of Structure-Aware Fully Convolutional Networks for Landmark Localization

Interaction Matters: A Note on Non-asymptotic Local Convergence of Generative Adversarial Networks

Computational Histological Staining and Destaining of Prostate Core Biopsy RGB Images with Generative Adversarial Neural Networks

Label-Removed Generative Adversarial Networks Incorporating with K-Means

Using Conditional Generative Adversarial Networks to Generate Ground-Level Views From Overhead Imagery

SC-FEGAN: Face Editing Generative Adversarial Network with User's Sketch and Color

Learning with Bad Training Data via Iterative Trimmed Loss Minimization

Data augmentation for low resource sentiment analysis using generative adversarial networks

Generative Adversarial Networks Synthesize Realistic OCT Images of the Retina

Progressive Generative Adversarial Networks for Medical Image Super resolution

Learning Generative Models of Structured Signals from Their Superposition Using GANs with Application to Denoising and Demixing

Progressively Growing Generative Adversarial Networks for High Resolution Semantic Segmentation of Satellite Images

GAN- vs. JPEG2000 Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation

Improving learnability of neural networks: adding supplementary axes to disentangle data representation

Improving Generalization and Stability of Generative Adversarial Networks

MD-GAN: Multi-Discriminator Generative Adversarial Networks for Distributed Datasets

Deep Convolutional Generative Adversarial Networks Based Flame Detection in Video

A Layer-Based Sequential Framework for Scene Generation with GANs

Resolution enhancement in scanning electron microscopy using deep learning

Generative Adversarial Networks for geometric surfaces prediction in injection molding

ClusterGAN : Latent Space Clustering in Generative Adversarial Networks

Generative Adversarial Networks for Black-Box API Attacks with Limited Training Data

On Finding Local Nash Equilibria (and Only Local Nash Equilibria) in Zero-Sum Games

Multi-objective training of Generative Adversarial Networks with multiple discriminators

CT synthesis from MR images for orthopedic applications in the lower arm using a conditional generative adversarial network

Generative Adversarial Network with Multi-Branch Discriminator for Cross-Species Image-to-Image Translation

Generating and Aligning from Data Geometries with Generative Adversarial Networks

Learning to navigate image manifolds induced by generative adversarial networks for unsupervised video generation

Segmentation Guided Image-to-Image Translation with Adversarial Networks

LayoutGAN: Generating Graphic Layouts with Wireframe Discriminators

Learning Spatial Pyramid Attentive Pooling in Image Synthesis and Image-to-Image Translation

Memory Augmented Deep Generative models for Forecasting the Next Shot Location in Tennis

Dual Generator Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

Data Augmentation with Manifold Exploring Geometric Transformations for Increased Performance and Robustness

A Novel Topology Optimization Approach using Conditional Deep Learning

Introducing a Generative Adversarial Network Model for Lagrangian Trajectory Simulation

Efficient Super Resolution For Large-Scale Images Using Attentional GAN

LGAN: Lung Segmentation in CT Scans Using Generative Adversarial Network

Disconnected Manifold Learning for Generative Adversarial Networks

A novel topology design approach using an integrated deep learning network architecture

Training-image based geostatistical inversion using a spatial generative adversarial neural network

A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference

Blind Motion Deblurring with Cycle Generative Adversarial Networks

Better Guider Predicts Future Better: Difference Guided Generative Adversarial Networks

Polarimetric Thermal to Visible Face Verification via Attribute Preserved Synthesis

Adversarial Machine Learning And Speech Emotion Recognition: Utilizing Generative Adversarial Networks For Robustness

Brain MRI super-resolution using 3D generative adversarial networks

Evaluating Generative Adversarial Networks on Explicitly Parameterized Distributions

Latent Variable Modeling for Generative Concept Representations and Deep Generative Models

Deep Convolutional Generative Adversarial Network Based Food Recognition Using Partially Labeled Data

Iris-GAN: Learning to Generate Realistic Iris Images Using Convolutional GAN

Finger-GAN: Generating Realistic Fingerprint Images Using Connectivity Imposed GAN

Texture Deformation Based Generative Adversarial Networks for Face Editing

Multi-component Image Translation for Deep Domain Generalization

DeepFakes: a New Threat to Face Recognition? Assessment and Detection

Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution

Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images

GD-GAN: Generative Adversarial Networks for Trajectory Prediction and Group Detection in Crowds

Generative adversarial networks for generation and classification of physical rehabilitation movement episodes

GAN-QP: A Novel GAN Framework without Gradient Vanishing and Lipschitz Constraint

Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks

Unsupervised Degradation Learning for Single Image Super-Resolution

Generative Adversarial Networks for Recovering Missing Spectral Information

Synthesis of High-Quality Visible Faces from Polarimetric Thermal Faces using Generative Adversarial Networks

FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification

Anomaly Generation using Generative Adversarial Networks in Host Based Intrusion Detection

GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning

Towards generative adversarial networks as a new paradigm for radiology education

FaceFeat-GAN: a Two-Stage Approach for Identity-Preserving Face Synthesis

Semantic Image Inpainting Through Improved Wasserstein Generative Adversarial Networks

Knowledge Distillation with Feature Maps for Image Classification

Semi-supervised Rare Disease Detection Using Generative Adversarial Network

Constructing Unrestricted Adversarial Examples with Generative Models

SiftingGAN: Generating and Sifting Labeled Samples to Improve the Remote Sensing Image Scene Classification Baseline in vitro

Domain-Invariant Adversarial Learning for Unsupervised Domain Adaption

Iterative Projection and Matching: Finding Structure-preserving Representatives and Its Application to Computer Vision

Simultaneously Color-Depth Super-Resolution with Conditional Generative Adversarial Network

Generative Adversarial Network Training is a Continual Learning Problem

Perceptual Conditional Generative Adversarial Networks for End-to-End Image Colourization

Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping

Automating Motion Correction in Multishot MRI Using Generative Adversarial Networks

SSGAN: Secure Steganography Based on Generative Adversarial Networks

Self Paced Adversarial Training for Multimodal Few-shot Learning

IEGAN: Multi-purpose Perceptual Quality Image Enhancement Using Generative Adversarial Network

Multi-Task Generative Adversarial Network for Handling Imbalanced Clinical Data

Unsupervised Single Image Deraining with Self-supervised Constraints

ProstateGAN: Mitigating Data Bias via Prostate Diffusion Imaging Synthesis with Generative Adversarial Networks

CariGAN: Caricature Generation through Weakly Paired Adversarial Learning

MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense

Event-based High Dynamic Range Image and Very High Frame Rate Video Generation using Conditional Generative Adversarial Networks

Pyramid Embedded Generative Adversarial Network for Automated Font Generation

Injecting and removing malignant features in mammography with CycleGAN: Investigation of an automated adversarial attack using neural networks

Training Faster by Separating Modes of Variation in Batch-normalized Models

GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training

How Generative Adversarial Networks and Their Variants Work: An Overview

Adversarial Learning of Label Dependency: A Novel Framework for Multi-class Classification

Adversarial Learning-Based On-Line Anomaly Monitoring for Assured Autonomy

Splenomegaly Segmentation on Multi-modal MRI using Deep Convolutional Networks

Neural Stain Normalization and Unsupervised Classification of Cell Nuclei in Histopathological Breast Cancer Images

Imagining an Engineer: On GAN-Based Data Augmentation Perpetuating Biases

Triple consistency loss for pairing distributions in GAN-based face synthesis

BinGAN: Learning Compact Binary Descriptors with a Regularized GAN

Style Separation and Synthesis via Generative Adversarial Networks

Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations

Thermal Infrared Colorization via Conditional Generative Adversarial Network

Learning Bone Suppression from Dual Energy Chest X-rays using Adversarial Networks

Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network

PacGAN: The power of two samples in generative adversarial networks

Building Footprint Generation Using Improved Generative Adversarial Networks

GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

Generative adversarial networks and adversarial methods in biomedical image analysis

Breast Tumor Segmentation and Shape Classification in Mammograms using Generative Adversarial and Convolutional Neural Network

Finding Mixed Nash Equilibria of Generative Adversarial Networks

LoGAN: Generating Logos with a Generative Adversarial Neural Network Conditioned on color

Deep Adversarial Training for Multi-Organ Nuclei Segmentation in Histopathology Images

Generative Adversarial Network based Autoencoder: Application to fault detection problem for closed loop dynamical systems

DeepMasterPrints: Generating MasterPrints for Dictionary Attacks via Latent Variable Evolution

Unsupervised Domain Adaptation for Learning Eye Gaze from a Million Synthetic Images: An Adversarial Approach

Deep learning-based super-resolution in coherent imaging systems

Point Cloud Colorization Based on Densely Annotated 3D Shape Dataset

MDGAN: Boosting Anomaly Detection Using \\Multi-Discriminator Generative Adversarial Networks

Training Generative Adversarial Networks with Binary Neurons by End-to-end Backpropagation

Unpaired High-Resolution and Scalable Style Transfer Using Generative Adversarial Networks

Generalized Latent Variable Recovery for Generative Adversarial Networks

Convolutional Generative Adversarial Networks with Binary Neurons for Polyphonic Music Generation

Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile

Modular Vehicle Control for Transferring Semantic Information Between Weather Conditions Using GANs

Multi-pseudo Regularized Label for Generated Data in Person Re-Identification

Pseudo-Random Number Generation using Generative Adversarial Networks

Featurized Bidirectional GAN: Adversarial Defense via Adversarially Learned Semantic Inference

Autonomously and Simultaneously Refining Deep Neural Network Parameters by a Bi-Generative Adversarial Network Aided Genetic Algorithm

Parametric Synthesis of Text on Stylized Backgrounds using PGGANs

Deep learning for determining a near-optimal topological design without any iteration

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

On the Effectiveness of Least Squares Generative Adversarial Networks

Generative adversarial network-based image super-resolution using perceptual content losses

SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints

Image Super-Resolution via Deterministic-Stochastic Synthesis and Local Statistical Rectification

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

Adversarial Feature Sampling Learning for Efficient Visual Tracking

OffsetNet: Deep Learning for Localization in the Lung using Rendered Images

A study on the use of Boundary Equilibrium GAN for Approximate Frontalization of Unconstrained Faces to aid in Surveillance

Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks

The relativistic discriminator: a key element missing from standard GAN

Coupled IGMM-GANs for deep multimodal anomaly detection in human mobility data

BubGAN: Bubble Generative Adversarial Networks for Synthesizing Realistic Bubbly Flow Images

Full-body High-resolution Anime Generation with Progressive Structure-conditional Generative Adversarial Networks

Reconstruction of Simulation-Based Physical Field by Reconstruction Neural Network Method

Robust Iris Segmentation Based on Fully Convolutional Networks and Generative Adversarial Networks

PathGAN: Visual Scanpath Prediction with Generative Adversarial Networks

Unsupervised Image Super-Resolution using Cycle-in-Cycle Generative Adversarial Networks

Regularizing Deep Hashing Networks Using GAN Generated Fake Images

Learning Data Augmentation for Brain Tumor Segmentation with Coarse-to-Fine Generative Adversarial Networks

Gaussian Mixture Generative Adversarial Networks for Diverse Datasets, and the Unsupervised Clustering of Images

GANimation: Anatomically-aware Facial Animation from a Single Image

Conditional Infilling GANs for Data Augmentation in Mammogram Classification

DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN

Improved ArtGAN for Conditional Synthesis of Natural Image and Artwork

Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

Real-time Deep Pose Estimation with Geodesic Loss for Image-to-Template Rigid Registration

An empirical study on evaluation metrics of generative adversarial networks

Text-to-Image-to-Text Translation using Cycle Consistent Adversarial Networks

ScarGAN: Chained Generative Adversarial Networks to Simulate Pathological Tissue on Cardiovascular MR Scans

Generative Invertible Networks (GIN): Pathophysiology-Interpretable Feature Mapping and Virtual Patient Generation

Unsupervised learning for cross-domain medical image synthesis using deformation invariant cycle consistency networks

Overcoming Missing and Incomplete Modalities with Generative Adversarial Networks for Building Footprint Segmentation

Coloring with Words: Guiding Image Colorization Through Text-based Palette Generation

Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation

Continuous-Time Flows for Efficient Inference and Density Estimation

Unsupervisedly Training GANs for Segmenting Digital Pathology with Automatically Generated Annotations

Anomaly Detection via Minimum Likelihood Generative Adversarial Networks

ID Preserving Generative Adversarial Network for Partial Latent Fingerprint Reconstruction

Improving Automatic Skin Lesion Segmentation using Adversarial Learning based Data Augmentation

To learn image super-resolution, use a GAN to learn how to do image degradation first

Emulating malware authors for proactive protection using GANs over a distributed image visualization of dynamic file behavior

Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks

AlphaGAN: Generative adversarial networks for natural image matting

Multi-temporal Sentinel-1 and -2 Data Fusion for Optical Image Simulation

Peeking Behind Objects: Layered Depth Prediction from a Single Image

Cross-Modality Synthesis from CT to PET using FCN and GAN Networks for Improved Automated Lesion Detection

SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination

Editable Generative Adversarial Networks: Generating and Editing Faces Simultaneously

An Improved Evaluation Framework for Generative Adversarial Networks

Generative Adversarial Networks for MR-CT Deformable Image Registration

Query-Conditioned Three-Player Adversarial Network for Video Summarization

Airline Passenger Name Record Generation using Generative Adversarial Networks

Automated Treatment Planning in Radiation Therapy using Generative Adversarial Networks

Deep Learning for Imbalance Data Classification using Class Expert Generative Adversarial Network

Recurrent Semi-supervised Classification and Constrained Adversarial Generation with Motion Capture Data

Distillation Techniques for Pseudo-rehearsal Based Incremental Learning

Discovering Interesting Plots in Production Yield Data Analytics

Fully Convolutional Networks and Generative Adversarial Networks Applied to Sclera Segmentation

Generative Adversarial Networks for Unsupervised Object Co-localization

Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing

Generating Realistic Geology Conditioned on Physical Measurements with Generative Adversarial Networks

EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection

MIXGAN: Learning Concepts from Different Domains for Mixture Generation

Generating Multi-Categorical Samples with Generative Adversarial Networks

Resembled Generative Adversarial Networks: Two Domains with Similar Attributes

Adversarial Perturbations Against Real-Time Video Classification Systems

SalGAN: Visual Saliency Prediction with Generative Adversarial Networks

Convergence Problems with Generative Adversarial Networks (GANs)

Generate the corresponding Image from Text Description using Modified GAN-CLS Algorithm

CR-GAN: Learning Complete Representations for Multi-view Generation

StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks

Parametric Adversarial Divergences are Good Task Losses for Generative Modeling

IR2VI: Enhanced Night Environmental Perception by Unsupervised Thermal Image Translation

Person Transfer GAN to Bridge Domain Gap for Person Re-Identification

Selecting the Best in GANs Family: a Post Selection Inference Framework

Cross-dataset Person Re-Identification Using Similarity Preserved Generative Adversarial Networks

Generative Adversarial Networks for Image-to-Image Translation on Multi-Contrast MR Images - A Comparison of CycleGAN and UNIT

Semi-supervised Seizure Prediction with Generative Adversarial Networks

Versatile Auxiliary Classifier with Generative Adversarial Network (VAC+GAN), Multi Class Scenarios

Semantically Selective Augmentation for Deep Compact Person Re-Identification

Gradient Layer: Enhancing the Convergence of Adversarial Training for Generative Models

CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation

Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks

Conditional Generative Adversarial and Convolutional Networks for X-ray Breast Mass Segmentation and Shape Classification

Geometry Score: A Method For Comparing Generative Adversarial Networks

Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected Network

Learning Myelin Content in Multiple Sclerosis from Multimodal MRI through Adversarial Training

Generating Image Sequence from Description with LSTM Conditional GAN

JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets

RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks

A Classification-Based Study of Covariate Shift in GAN Distributions

Adversarial Scene Editing: Automatic Object Removal from Weak Supervision

An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks

Capturing Variabilities from Computed Tomography Images with Generative Adversarial Networks

Webpage Saliency Prediction with Two-stage Generative Adversarial Networks

tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow

Synergistic Reconstruction and Synthesis via Generative Adversarial Networks for Accelerated Multi-Contrast MRI

Keep it Unreal: Bridging the Realism Gap for 2.5D Recognition with Geometry Priors Only

Adversarially Learned One-Class Classifier for Novelty Detection

Single-View Food Portion Estimation: Learning Image-to-Energy Mappings Using Generative Adversarial Networks

On the Convergence and Robustness of Training GANs with Regularized Optimal Transport

Adversarial Training for Disease Prediction from Electronic Health Records with Missing Data

Retinal Vasculature Segmentation Using Local Saliency Maps and Generative Adversarial Networks For Image Super Resolution

A Generative Adversarial Approach for Zero-Shot Learning from Noisy Texts

Generative Adversarial Forests for Better Conditioned Adversarial Learning

Augmented Skeleton Space Transfer for Depth-based Hand Pose Estimation

Exploiting Images for Video Recognition with Hierarchical Generative Adversarial Networks

Retinal Vessel Segmentation Based on Conditional Deep Convolutional Generative Adversarial Networks

Unsupervised Deep Representations for Learning Audience Facial Behaviors

Improving GAN Training via Binarized Representation Entropy (BRE) Regularization

N2RPP: An Adversarial Network to Rebuild Plantar Pressure for ACLD Patients

Pseudo-Recursal: Solving the Catastrophic Forgetting Problem in Deep Neural Networks

Attentive Generative Adversarial Network for Raindrop Removal from a Single Image

Adversarial Feature Augmentation for Unsupervised Domain Adaptation

Perceptually Optimized Generative Adversarial Network for Single Image Dehazing

CANDY: Conditional Adversarial Networks based Fully End-to-End System for Single Image Haze Removal

Learning Human Pose Models from Synthesized Data for Robust RGB-D Action Recognition

Quantitatively Evaluating GANs With Divergences Proposed for Training

GP-GAN: Gender Preserving GAN for Synthesizing Faces from Landmarks

Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss

Path Planning in Support of Smart Mobility Applications using Generative Adversarial Networks

Occluded object reconstruction for first responders with augmented reality glasses using conditional generative adversarial networks

Estimation of Tissue Oxygen Saturation from RGB Images based on Pixel-level Image Translation

RSGAN: Face Swapping and Editing using Face and Hair Representation in Latent Spaces

Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond

SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis

Generate To Adapt: Aligning Domains using Generative Adversarial Networks

Blood Vessel Geometry Synthesis using Generative Adversarial Networks

Generative Adversarial Training for MRA Image Synthesis Using Multi-Contrast MRI

Correcting differences in multi-site neuroimaging data using Generative Adversarial Networks

Unsupervised and semi-supervised learning with Categorical Generative Adversarial Networks assisted by Wasserstein distance for dermoscopy image Classification

Facial Aging and Rejuvenation by Conditional Multi-Adversarial Autoencoder with Ordinal Regression

Updating the generator in PPGN-h with gradients flowing through the encoder

SyncGAN: Synchronize the Latent Space of Cross-modal Generative Adversarial Networks

Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networks

Deep learning-based virtual histology staining using auto-fluorescence of label-free tissue

Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

Image Inpainting using Block-wise Procedural Training with Annealed Adversarial Counterpart

Comparing Generative Adversarial Network Techniques for Image Creation and Modification

Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations

Speech-Driven Facial Reenactment Using Conditional Generative Adversarial Networks

Patch-Based Image Inpainting with Generative Adversarial Networks

Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities

Line Artist: A Multiple Style Sketch to Painting Synthesis Scheme

A Multi-perspective Approach To Anomaly Detection For Self-aware Embodied Agents

Improved Part Segmentation Performance by Optimising Realism of Synthetic Images using Cycle Generative Adversarial Networks

Compressed Sensing MRI Reconstruction using a Generative Adversarial Network with a Cyclic Loss

Correction by Projection: Denoising Images with Generative Adversarial Networks

3D Reconstruction of Incomplete Archaeological Objects Using a Generative Adversarial Network

Task Specific Visual Saliency Prediction with Memory Augmented Conditional Generative Adversarial Networks

Tracking by Prediction: A Deep Generative Model for Mutli-Person localisation and Tracking

Inferencing Based on Unsupervised Learning of Disentangled Representations

ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing

Egocentric Basketball Motion Planning from a Single First-Person Image

GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification

Generating High Quality Visible Images from SAR Images Using CNNs

L1-Norm Batch Normalization for Efficient Training of Deep Neural Networks

Incremental Adversarial Domain Adaptation for Continually Changing Environments

Solving Linear Inverse Problems Using GAN Priors: An Algorithm with Provable Guarantees

Semantically Decomposing the Latent Spaces of Generative Adversarial Networks

A Study into the similarity in generator and discriminator in GAN architecture

Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step

DA-GAN: Instance-level Image Translation by Deep Attention Generative Adversarial Networks (with Supplementary Materials)

Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator

How Well Can Generative Adversarial Networks Learn Densities: A Nonparametric View

Inverting The Generator Of A Generative Adversarial Network (II)

Conditioning of three-dimensional generative adversarial networks for pore and reservoir-scale models

Satellite Image Forgery Detection and Localization Using GAN and One-Class Classifier

Joint Demosaicing and Denoising with Perceptual Optimization on a Generative Adversarial Network

An Optimized Architecture for Unpaired Image-to-Image Translation

Generalization of Deep Neural Networks for Chest Pathology Classification in X-Rays Using Generative Adversarial Networks

Generative Adversarial Networks and Probabilistic Graph Models for Hyperspectral Image Classification

Stochastic Deconvolutional Neural Network Ensemble Training on Generative Pseudo-Adversarial Networks

Bitewing Radiography Semantic Segmentation Base on Conditional Generative Adversarial Nets

Spectral Image Visualization Using Generative Adversarial Networks

Training Generative Adversarial Networks via Primal-Dual Subgradient Methods: A Lagrangian Perspective on GAN

Task-Aware Compressed Sensing with Generative Adversarial Networks

Image Synthesis in Multi-Contrast MRI with Conditional Generative Adversarial Networks

Selective Sampling and Mixture Models in Generative Adversarial Networks

Incremental Classifier Learning with Generative Adversarial Networks

No Modes left behind: Capturing the data distribution effectively using GANs

Exploiting the potential of unlabeled endoscopic video data with self-supervised learning

Interactive Generative Adversarial Networks for Facial Expression Generation in Dyadic Interactions

Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields

Classification of sparsely labeled spatio-temporal data through semi-supervised adversarial learning

Optimal transport maps for distribution preserving operations on latent spaces of Generative Models

High Resolution Face Completion with Multiple Controllable Attributes via Fully End-to-End Progressive Generative Adversarial Networks

DiscrimNet: Semi-Supervised Action Recognition from Videos using Generative Adversarial Networks

Enhancing Underwater Imagery using Generative Adversarial Networks

Generating Multi-label Discrete Patient Records using Generative Adversarial Networks

How to Fool Radiologists with Generative Adversarial Networks? A Visual Turing Test for Lung Cancer Diagnosis

Modeling urbanization patterns with generative adversarial networks

Simulating Patho-realistic Ultrasound Images using Deep Generative Networks with Adversarial Learning

Synthetic Data Augmentation using GAN for Improved Liver Lesion Classification

Crossing Generative Adversarial Networks for Cross-View Person Re-identification

Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models

Face Synthesis from Visual Attributes via Sketch using Conditional VAEs and GANs

Differential Generative Adversarial Networks: Synthesizing Non-linear Facial Variations with Limited Number of Training Data

Use of Generative Adversarial Network for Cross-Domain Change Detection

Adversarial Synthesis Learning Enables Segmentation Without Target Modality Ground Truth

SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution

Data Augmentation in Emotion Classification Using Generative Adversarial Networks

Learning Disentangling and Fusing Networks for Face Completion Under Structured Occlusions

Logo Synthesis and Manipulation with Clustered Generative Adversarial Networks

CMCGAN: A Uniform Framework for Cross-Modal Visual-Audio Mutual Generation

TV-GAN: Generative Adversarial Network Based Thermal to Visible Face Recognition

Semi-Supervised Learning with IPM-based GANs: an Empirical Study

Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal

SGAN: An Alternative Training of Generative Adversarial Networks

Towards Recovery of Conditional Vectors from Conditional Generative Adversarial Networks

Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference

Learning to Fuse Music Genres with Generative Adversarial Dual Learning

On the Effects of Batch and Weight Normalization in Generative Adversarial Networks

Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks

Personalized and Occupational-aware Age Progression by Generative Adversarial Networks

FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors

Super-Resolution for Overhead Imagery Using DenseNets and Adversarial Learning

MMD GAN: Towards Deeper Understanding of Moment Matching Network

Semantically Consistent Image Completion with Fine-grained Details

In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks

Deformable Deep Convolutional Generative Adversarial Network in Microwave Based Hand Gesture Recognition System

Improving Consistency and Correctness of Sequence Inpainting using Semantically Guided Generative Adversarial Network

Shape Inpainting using 3D Generative Adversarial Network and Recurrent Convolutional Networks

Tensor-Generative Adversarial Network with Two-dimensional Sparse Coding: Application to Real-time Indoor Localization

VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning

Hierarchical Implicit Models and Likelihood-Free Variational Inference

VIGAN: Missing View Imputation with Generative Adversarial Networks

Improved Adversarial Systems for 3D Object Generation and Reconstruction

WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images

Text2Action: Generative Adversarial Synthesis from Language to Action

Variational Approaches for Auto-Encoding Generative Adversarial Networks

Sharpness-aware Low dose CT denoising using conditional generative adversarial network

Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training

Filmy Cloud Removal on Satellite Imagery with Multispectral Conditional Generative Adversarial Nets

A Study of Cross-domain Generative Models applied to Cartoon Series

Generative Adversarial Networks with Inverse Transformation Unit

Summable Reparameterizations of Wasserstein Critics in the One-Dimensional Setting

To Go or Not To Go? A Near Unsupervised Learning Approach For Robot Navigation

The Conditional Analogy GAN: Swapping Fashion Articles on People Images

ExprGAN: Facial Expression Editing with Controllable Expression Intensity

Label Denoising Adversarial Network (LDAN) for Inverse Lighting of Face Images

Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records

Intraoperative Organ Motion Models with an Ensemble of Conditional Generative Adversarial Networks

3D Object Reconstruction from a Single Depth View with Adversarial Learning

Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

Towards the Automatic Anime Characters Creation with Generative Adversarial Networks

Conditional Adversarial Network for Semantic Segmentation of Brain Tumor

Generative Adversarial Network-based Synthesis of Visible Faces from Polarimetric Thermal Faces

Image Quality Assessment Techniques Show Improved Training and Evaluation of Autoencoder Generative Adversarial Networks

StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks

Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis

Generalization and Equilibrium in Generative Adversarial Nets (GANs)

Unsupervised Visual Attribute Transfer with Reconfigurable Generative Adversarial Networks

Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks (GANs)

Virtual PET Images from CT Data Using Deep Convolutional Networks: Initial Results

Learning from Simulated and Unsupervised Images through Adversarial Training

Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks

Generative Adversarial Network based on Resnet for Conditional Image Restoration

Generative Adversarial Models for People Attribute Recognition in Surveillance

Learning Loss Functions for Semi-supervised Learning via Discriminative Adversarial Networks

AlignGAN: Learning to Align Cross-Domain Images with Conditional Generative Adversarial Networks

High-Quality Face Image SR Using Conditional Generative Adversarial Networks

Unsupervised Diverse Colorization via Generative Adversarial Networks

Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks

Generate Identity-Preserving Faces by Generative Adversarial Networks

Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis

Style Transfer for Anime Sketches with Enhanced Residual U-net and Auxiliary Classifier GAN

DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data

Deep Generative Adversarial Networks for Compressed Sensing Automates MRI

The Cramer Distance as a Solution to Biased Wasserstein Gradients

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

Approximation and Convergence Properties of Generative Adversarial Learning

Learning to Succeed while Teaching to Fail: Privacy in Closed Machine Learning Systems

Learning to Discover Cross-Domain Relations with Generative Adversarial Networks

Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently

A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGA

Gang of GANs: Generative Adversarial Networks with Maximum Margin Ranking

Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters

Semi-Latent GAN: Learning to generate and modify facial images from attributes

Semi and Weakly Supervised Semantic Segmentation Using Generative Adversarial Network

Temporal Non-Volume Preserving Approach to Facial Age-Progression and Age-Invariant Face Recognition

Generative Adversarial Residual Pairwise Networks for One Shot Learning

Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery

Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN

Towards Principled Methods for Training Generative Adversarial Networks

Unsupervised Image-to-Image Translation with Generative Adversarial Networks

Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling

Medical Image Synthesis with Context-Aware Generative Adversarial Networks

SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networks

Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks

GANS for Sequences of Discrete Elements with the Gumbel-softmax Distribution

Generative Adversarial Nets from a Density Ratio Estimation Perspective

Generative Adversarial Networks as Variational Training of Energy Based Models

Deep Directed Generative Models with Energy-Based Probability Estimation

Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks

Non-stationary Gaussian process discriminant analysis with variable selection for high-dimensional functional data

An Explainable-AI approach for Diagnosis of COVID-19 using MALDI-ToF Mass Spectrometry

Deep graph matching meets mixed-integer linear programming: Relax at your own risk ?

Multi-Semantic Image Recognition Model and Evaluating Index for explaining the deep learning models

Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron

Meta-learning based Alternating Minimization Algorithm for Non-convex Optimization

Deep Learning-Based Detection of the Acute Respiratory Distress Syndrome: What Are the Models Learning?

EDDA: Explanation-driven Data Augmentation to Improve Explanation Faithfulness

Explaining Local, Global, And Higher-Order Interactions In Deep Learning

Local Intrinsic Dimensionality Signals Adversarial Perturbations

Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold

How do Quadratic Regularizers Prevent Catastrophic Forgetting: The Role of Interpolation

Beyond BatchNorm: Towards a General Understanding of Normalization in Deep Learning

Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles

Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning

FakeWake: Understanding and Mitigating Fake Wake-up Words of Voice Assistants

The shape and simplicity biases of adversarially robust ImageNet-trained CNNs

A Meta-Learning Approach for Training Explainable Graph Neural Networks

Evaluating explainable artificial intelligence methods for multi-label deep learning classification tasks in remote sensing

Inferring feature importance with uncertainties in high-dimensional data

Unsupervised 3D Pose Estimation for Hierarchical Dance Video Recognition

Memory Regulation and Alignment toward Generalizer RGB-Infrared Person

Visual resemblance and communicative context constrain the emergence of graphical conventions

Rotation Averaging in a Split Second: A Primal-Dual Method and a Closed-Form for Cycle Graphs

Detection Accuracy for Evaluating Compositional Explanations of Units

Towards Out-of-Distribution Detection with Divergence Guarantee in Deep Generative Models

Learning the Regularization in DCE-MR Image Reconstruction for Functional Imaging of Kidneys

A trainable monogenic ConvNet layer robust in front of large contrast changes in image classification

COVID-Net Clinical ICU: Enhanced Prediction of ICU Admission for COVID-19 Patients via Explainability and Trust Quantification

The pitfalls of using open data to develop deep learning solutions for COVID-19 detection in chest X-rays

Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters

Towards Better Model Understanding with Path-Sufficient Explanations

Explaining Deep Learning Representations by Tracing the Training Process

DisCERN:Discovering Counterfactual Explanations using Relevance Features from Neighbourhoods

Explain Me the Painting: Multi-Topic Knowledgeable Art Description Generation

Global and Local Interpretation of black-box Machine Learning models to determine prognostic factors from early COVID-19 data

Neural Networks for Latent Budget Analysis of Compositional Data

Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks

Unsupervised Causal Binary Concepts Discovery with VAE for Black-box Model Explanation

FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging

Combining resampling and reweighting for faithful stochastic optimization

ECQ$^{\text{x}}$: Explainability-Driven Quantization for Low-Bit and Sparse DNNs

Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training

Self-explaining variational posterior distributions for Gaussian Process models

Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud

Interactive slice visualization for exploring machine learning models

EsmamDS: A more diverse exceptional survival model mining approach

Estimation of Bivariate Structural Causal Models by Variational Gaussian Process Regression Under Likelihoods Parametrised by Normalising Flows

A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning

CPFN: Cascaded Primitive Fitting Networks for High-Resolution Point Clouds

Square Root Marginalization for Sliding-Window Bundle Adjustment

Data Quality Toolkit: Automatic assessment of data quality and remediation for machine learning datasets

Synthetic Benchmarks for Scientific Research in Explainable Machine Learning

How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data

White Box Methods for Explanations of Convolutional Neural Networks in Image Classification Tasks

GAM: Explainable Visual Similarity and Classification via Gradient Activation Maps

Wasserstein GANs with Gradient Penalty Compute Congested Transport

The Role of Explainability in Assuring Safety of Machine Learning in Healthcare

Explaining in Style: Training a GAN to explain a classifier in StyleSpace

Quantifying and Localizing Private Information Leakage from Neural Network Gradients

Approximation Methods for Partially Observed Markov Decision Processes (POMDPs)

PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining CNNs

Chi-square Loss for Softmax: an Echo of Neural Network Structure

Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity

Convex Geometry and Duality of Over-parameterized Neural Networks

Noticing Motion Patterns: Temporal CNN with a Novel Convolution Operator for Human Trajectory Prediction

Understanding Character Recognition using Visual Explanations Derived from the Human Visual System and Deep Networks

Wasserstein-based fairness interpretability framework for machine learning models

Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients

DomiKnowS: A Library for Integration of Symbolic Domain Knowledge in Deep Learning

This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation

Inducing Semantic Grouping of Latent Concepts for Explanations: An Ante-Hoc Approach

Adaptive Explainable Continual Learning Framework for Regression Problems with Focus on Power Forecasts

ProtoMIL: Multiple Instance Learning with Prototypical Parts for Fine-Grained Interpretability

Label-Imbalanced and Group-Sensitive Classification under Overparameterization

Explainable Machine Learning using Real, Synthetic and Augmented Fire Tests to Predict Fire Resistance and Spalling of RC Columns

Development and evaluation of an Explainable Prediction Model for Chronic Kidney Disease Patients based on Ensemble Trees

Improvement of a Prediction Model for Heart Failure Survival through Explainable Artificial Intelligence

SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition

MGSampler: An Explainable Sampling Strategy for Video Action Recognition

WiseR: An end-to-end structure learning and deployment framework for causal graphical models

Machine Learning for Security in Vehicular Networks: A Comprehensive Survey

CARE: Coherent Actionable Recourse based on Sound Counterfactual Explanations

Optimising Knee Injury Detection with Spatial Attention and Validating Localisation Ability

Existence, uniqueness, and convergence rates for gradient flows in the training of artificial neural networks with ReLU activation

Surrogate Model-Based Explainability Methods for Point Cloud NNs

A Human-in-the-Loop Approach based on Explainability to Improve NTL Detection

Explainable Person Re-Identification with Attribute-guided Metric Distillation

General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models

Synthesizing Pareto-Optimal Interpretations for Black-Box Models

Understanding the factors driving the opioid epidemic using machine learning

Detecting and interpreting faults in vulnerable power grids with machine learning

Knowledge-Based Construction of Confusion Matrices for Multi-Label Classification Algorithms using Semantic Similarity Measures

Locally Interpretable Model Agnostic Explanations using Gaussian Processes

Interpreting Attributions and Interactions of Adversarial Attacks

Reducing the Communication Cost of Federated Learning through Multistage Optimization

FOX-NAS: Fast, On-device and Explainable Neural Architecture Search

First-order and second-order variants of the gradient descent in a unified framework

FreaAI: Automated extraction of data slices to test machine learning models

Spectral Roll-off Points Variations: Exploring Useful Information in Feature Maps by Its Variations

Modeling Accurate Human Activity Recognition for Embedded Devices Using Multi-level Distillation

Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition

CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks

A Baseline for Shapley Values in MLPs: from Missingness to Neutrality

Automated Olfactory Bulb Segmentation on High Resolutional T2-Weighted MRI

Johnson-Lindenstrauss Lemma, Linear and Nonlinear Random Projections, Random Fourier Features, and Random Kitchen Sinks: Tutorial and Survey

Improved Feature Importance Computations for Tree Models: Shapley vs. Banzhaf

Deep Gravity: enhancing mobility flows generation with deep neural networks and geographic information

Understanding the computational demands underlying visual reasoning

GANterfactual - Counterfactual Explanations for Medical Non-Experts using Generative Adversarial Learning

Locally Interpretable One-Class Anomaly Detection for Credit Card Fraud Detection

Pan-Cancer Integrative Histology-Genomic Analysis via Interpretable Multimodal Deep Learning

PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations

Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability

Explainable Deep Few-shot Anomaly Detection with Deviation Networks

Explain and Improve: LRP-Inference Fine-Tuning for Image Captioning Models

Towards explainable artificial intelligence (XAI) for early anticipation of traffic accidents

Rationally Inattentive Utility Maximization for Interpretable Deep Image Classification

OpenSync: An opensource platform for synchronizing multiple measures in neuroscience experiments

Towards robust vision by multi-task learning on monkey visual cortex

Robust Explainability: A Tutorial on Gradient-Based Attribution Methods for Deep Neural Networks

Semantically Controllable Scene Generation with Guidance of Explicit Knowledge

Experiments on Properties of Hidden Structures of Sparse Neural Networks

On the Role of Optimization in Double Descent: A Least Squares Study

Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI

Dissecting FLOPs along input dimensions for GreenAI cost estimations

GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks

Interpretable Machine Learning Models for Predicting and Explaining Vehicle Fuel Consumption Anomalies

Towards Explaining Adversarial Examples Phenomenon in Artificial Neural Networks

Demand Forecasting of Individual Probability Density Functions with Machine Learning

Unsupervised Detection of Adversarial Examples with Model Explanations

Inter and Intra-Annual Spatio-Temporal Variability of Habitat Suitability for Asian Elephants in India: A Random Forest Model-based Analysis

Measuring and Explaining the Inter-Cluster Reliability of Multidimensional Projections

Differentiable Annealed Importance Sampling and the Perils of Gradient Noise

GLIME: A new graphical methodology for interpretable model-agnostic explanations

Uncertainty Estimation and Out-of-Distribution Detection for Counterfactual Explanations: Pitfalls and Solutions

Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Technical Challenges and Solutions

Predicting Driver Takeover Time in Conditionally Automated Driving

Edge of chaos as a guiding principle for modern neural network training

Believe The HiPe: Hierarchical Perturbation for Fast, Robust and Model-Agnostic Explanations

Towards the Unification and Robustness of Perturbation and Gradient Based Explanations

Understanding Failures in Out-of-Distribution Detection with Deep Generative Models

Information-Theoretic Visual Explanation for Black-Box Classifiers

Almost Tight Approximation Algorithms for Explainable Clustering

JKOnet: Proximal Optimal Transport Modeling of Population Dynamics

Mapping Learning Algorithms on Data, a useful step for optimizing performances and their comparison

Inverse Contextual Bandits: Learning How Behavior Evolves over Time

Explainability-based Backdoor Attacks Against Graph Neural Networks

DIVINE: Diverse Influential Training Points for Data Visualization and Model Refinement

How many degrees of freedom do we need to train deep networks: a loss landscape perspective

Interpretable Mammographic Image Classification using Cased-Based Reasoning and Deep Learning

Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond

Remote Blood Oxygen Estimation From Videos Using Neural Networks

SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs

One Map Does Not Fit All: Evaluating Saliency Map Explanation on Multi-Modal Medical Images

Improving Efficiency and Accuracy of Causal Discovery Using a Hierarchical Wrapper

Self-service Data Classification Using Interactive Visualization and Interpretable Machine Learning

Reliable Post hoc Explanations: Modeling Uncertainty in Explainability

WheaCha: A Method for Explaining the Predictions of Code Summarization Models

Cells are Actors: Social Network Analysis with Classical ML for SOTA Histology Image Classification

A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data

Learning Cascaded Detection Tasks with Weakly-Supervised Domain Adaptation

How to choose an Explainability Method? Towards a Methodical Implementation of XAI in Practice

PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging

TGHop: An Explainable, Efficient and Lightweight Method for Texture Generation

Encoding Domain Information with Sparse Priors for Inferring Explainable Latent Variables

Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering

Order in the Court: Explainable AI Methods Prone to Disagreement

Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning

When and How to Fool Explainable Models (and Humans) with Adversarial Examples

Provable Convergence of Nesterov Accelerated Method for Over-Parameterized Neural Networks

An Explainable AI System for the Diagnosis of High Dimensional Biomedical Data

The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks

GraphXCOVID: Explainable Deep Graph Diffusion Pseudo-Labelling for Identifying COVID-19 on Chest X-rays

Class Introspection: A Novel Technique for Detecting Unlabeled Subclasses by Leveraging Classifier Explainability Methods

Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks

Unknown Presentation Attack Detection against Rational Attackers

A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network

How good is your explanation? Algorithmic stability measures to assess the qualityof explanations for deep neural networks

Normalizing Flow based Hidden Markov Models for Classification of Speech Phones with Explainability

A general approach for Explanations in terms of Middle Level Features

Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity

Unified Framework for Spectral Dimensionality Reduction, Maximum Variance Unfolding, and Kernel Learning By Semidefinite Programming: Tutorial and Survey

Parallel Medical Imaging for Intelligent Medical Image Analysis: Concepts, Methods, and Applications

Explaining the Performance of Multi-label Classification Methods with Data Set Properties

A Graph-based approach to derive the geodesic distance on Statistical manifolds: Application to Multimedia Information Retrieval

TimeSHAP: Explaining Recurrent Models through Sequence Perturbations

Pastprop-RNN: improved predictions of the future by correcting the past

Feature Attributions and Counterfactual Explanations Can Be Manipulated

Reliable Graph Neural Network Explanations Through Adversarial Training

Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy

Towards Fully Interpretable Deep Neural Networks: Are We There Yet?

The effectiveness of feature attribution methods and its correlation with automatic evaluation scores

Gradient-Based Interpretability Methods and Binarized Neural Networks

Bayesian Deep Learning Hyperparameter Search for Robust Function Mapping to Polynomials with Noise

This Looks Like That... Does it? Shortcomings of Latent Space Prototype Interpretability in Deep Networks

Should You Go Deeper? Optimizing Convolutional Neural Network Architectures without Training by Receptive Field Analysis

groupShapley: Efficient prediction explanation with Shapley values for feature groups

Learned Interpretable Residual Extragradient ISTA for Sparse Coding

Latent-CF: A Simple Baseline for Reverse Counterfactual Explanations

Neural network interpretability for forecasting of aggregated renewable generation

Recent Deep Semi-supervised Learning Approaches and Related Works

A Mathematical Foundation for Robust Machine Learning based on Bias-Variance Trade-off

Policy Gradient Bayesian Robust Optimization for Imitation Learning

CAMERAS: Enhanced Resolution And Sanity preserving Class Activation Mapping for image saliency

Prediction of the facial growth direction with Machine Learning methods

Sparse Training via Boosting Pruning Plasticity with Neuroregeneration

A Probabilistic Representation of DNNs: Bridging Mutual Information and Generalization

NoiseGrad: enhancing explanations by introducing stochasticity to model weights

On the Connections between Counterfactual Explanations and Adversarial Examples

LoRMIkA: Local rule-based model interpretability with k-optimal associations

Guided Integrated Gradients: An Adaptive Path Method for Removing Noise

Accuracy, Interpretability, and Differential Privacy via Explainable Boosting

Towards Explainable Student Group Collaboration Assessment Models Using Temporal Representations of Individual Student Roles

Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity

Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors

Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion

Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusion

Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds, and Benign Overfitting

Insights into Data through Model Behaviour: An Explainability-driven Strategy for Data Auditing for Responsible Computer Vision Applications

A Survey on Semi-Supervised Learning for Delayed Partially Labelled Data Streams

EEG-GNN: Graph Neural Networks for Classification of Electroencephalogram (EEG) Signals

An Imprecise SHAP as a Tool for Explaining the Class Probability Distributions under Limited Training Data

Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning

Dissecting Hessian: Understanding Common Structure of Hessian in Neural Networks

Toward Affective XAI: Facial Affect Analysis for Understanding Explainable Human-AI Interactions

Learning to Disentangle GAN Fingerprint for Fake Image Attribution

Explainers in the Wild: Making Surrogate Explainers Robust to Distortions through Perception

Best of both worlds: local and global explanations with human-understandable concepts

Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data

SEEN: Sharpening Explanations for Graph Neural Networks using Explanations from Neighborhoods

Developing a Fidelity Evaluation Approach for Interpretable Machine Learning

Reproducing Kernel Hilbert Space, Mercer's Theorem, Eigenfunctions, Nyström Method, and Use of Kernels in Machine Learning: Tutorial and Survey

A Novel Interaction-based Methodology Towards Explainable AI with Better Understanding of Pneumonia Chest X-ray Images

Simon Says: Evaluating and Mitigating Bias in Pruned Neural Networks with Knowledge Distillation

Counterfactual Explanations for Machine Learning: Challenges Revisited

Going Beyond Classification Accuracy Metrics in Model Compression

Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions

An Interaction-based Convolutional Neural Network (ICNN) Towards Better Understanding of COVID-19 X-ray Images

What can linearized neural networks actually say about generalization?

Understanding Failures of Deep Networks via Robust Feature Extraction

Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect

Towards Understanding Generalization via Decomposing Excess Risk Dynamics

A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network

Progressive-Scale Boundary Blackbox Attack via Projective Gradient Estimation

Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice

On the overlooked issue of defining explanation objectives for local-surrogate explainers

Local Post-Hoc Explanations for Predictive Process Monitoring in Manufacturing

Towards Explainable Abnormal Infant Movements Identification: A Body-part Based Prediction and Visualisation Framework

Investigating sanity checks for saliency maps with image and text classification

On the Evolution of Neuron Communities in a Deep Learning Architecture

Explainable AI for medical imaging: Explaining pneumothorax diagnoses with Bayesian Teaching

Stability and Generalization of Bilevel Programming in Hyperparameter Optimization

Highly accurate digital traffic recording as a basis for future mobility research: Methods and concepts of the research project HDV-Mess

Amortized Generation of Sequential Counterfactual Explanations for Black-box Models

Accurate and robust Shapley Values for explaining predictions and focusing on local important variables

Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context

How to Evaluate Uncertainty Estimates in Machine Learning for Regression?

Parameter-free Statistically Consistent Interpolation: Dimension-independent Convergence Rates for Hilbert kernel regression

HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections

Visual communication of object concepts at different levels of abstraction

ViViT: Curvature access through the generalized Gauss-Newton's low-rank structure

On the emergence of simplex symmetry in the final and penultimate layers of neural network classifiers

A Holistic Approach to Interpretability in Financial Lending: Models, Visualizations, and Summary-Explanations

Laplacian-Based Dimensionality Reduction Including Spectral Clustering, Laplacian Eigenmap, Locality Preserving Projection, Graph Embedding, and Diffusion Map: Tutorial and Survey

GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured Interactions

KO-PDE: Kernel Optimized Discovery of Partial Differential Equations with Varying Coefficients

Explaining Data-Driven Decisions made by AI Systems: The Counterfactual Approach

On Explainability of Graph Neural Networks via Subgraph Explorations

DISSECT: Disentangled Simultaneous Explanations via Concept Traversals

Demographic Fairness in Biometric Systems: What do the Experts say?

An exact counterfactual-example-based approach to tree-ensemble models interpretability

On the geometry of generalization and memorization in deep neural networks

Generative Model-Based Loss to the Rescue: A Method to Overcome Annotation Errors for Depth-Based Hand Pose Estimation

Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End

Undefined class-label detection vs out-of-distribution detection

Understanding Instance-based Interpretability of Variational Auto-Encoders

Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning

Using Convolutional Neural Networks for Relative Pose Estimation of a Non-Cooperative Spacecraft with Thermal Infrared Imagery

Do not explain without context: addressing the blind spot of model explanations

The Sobolev Regularization Effect of Stochastic Gradient Descent

Explainable Multi-class Classification of the CAMH COVID-19 Mental Health Data

Do Gradient-based Explanations Tell Anything About Adversarial Robustness to Android Malware?

Towards Interpretable Attention Networks for Cervical Cancer Analysis

"Why Would I Trust Your Numbers?" On the Explainability of Expected Values in Soccer

Intellige: A User-Facing Model Explainer for Narrative Explanations

Loss landscapes and optimization in over-parameterized non-linear systems and neural networks

Unsupervised Part Segmentation through Disentangling Appearance and Shape

The Nonlinearity Coefficient - A Practical Guide to Neural Architecture Design

Towards Explainable Multi-Party Learning: A Contrastive Knowledge Sharing Framework

NExT-QA:Next Phase of Question-Answering to Explaining Temporal Actions

Texture synthesis via projection onto multiscale, multilayer statistics

Towards Automatic Recognition of Pure & Mixed Stones using Intraoperative Endoscopic Digital Images

Explainable Enterprise Credit Rating via Deep Feature Crossing Network

Yes We Care! -- Certification for Machine Learning Methods through the Care Label Framework

Visual representation of negation: Real world data analysis on comic image design

TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks

The MAMe Dataset: On the relevance of High Resolution and Variable Shape image properties

Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection

DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality

Graphs, Convolutions, and Neural Networks: From Graph Filters to Graph Neural Networks

Mutual Information for Explainable Deep Learning of Multiscale Systems

Fast Bayesian Uncertainty Estimation and Reduction of Batch Normalized Single Image Super-Resolution Network

Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation

Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization

Theoretical Foundations of t-SNE for Visualizing High-Dimensional Clustered Data

Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective

Controlling an Inverted Pendulum with Policy Gradient Methods-A Tutorial

How to Explain Neural Networks: A perspective of data space division

Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare

Expressive Explanations of DNNs by Combining Concept Analysis with ILP

ExSinGAN: Learning an Explainable Generative Model from a Single Image

Show Why the Answer is Correct! Towards Explainable AI using Compositional Temporal Attention

Quantifying Explainers of Graph Neural Networks in Computational Pathology

Privacy-Preserving Constrained Domain Generalization for Medical Image Classification

Agree to Disagree: When Deep Learning Models With Identical Architectures Produce Distinct Explanations

On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks

Dynamical Isometry: The Missing Ingredient for Neural Network Pruning

What's wrong with this video? Comparing Explainers for Deepfake Detection

Reachable Sets of Classifiers and Regression Models: (Non-)Robustness Analysis and Robust Training

KDExplainer: A Task-oriented Attention Model for Explaining Knowledge Distillation

SauvolaNet: Learning Adaptive Sauvola Network for Degraded Document Binarization

Comparing interpretability and explainability for feature selection

Discovery of Nonlinear Dynamical Systems using a Runge-Kutta Inspired Dictionary-based Sparse Regression Approach

Machine Assistance for Credit Card Approval? Random Wheel can Recommend and Explain

Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyond

DIG: A Turnkey Library for Diving into Graph Deep Learning Research

Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization

Coupling Intent and Action for Pedestrian Crossing Behavior Prediction

Interpretable Social Anchors for Human Trajectory Forecasting in Crowds

A Geometric Analysis of Neural Collapse with Unconstrained Features

Scaling Symbolic Methods using Gradients for Neural Model Explanation

Attack-agnostic Adversarial Detection on Medical Data Using Explainable Machine Learning

Impact of Spatial Frequency Based Constraints on Adversarial Robustness

Why Are Convolutional Nets More Sample-Efficient than Fully-Connected Nets?

Where and When: Space-Time Attention for Audio-Visual Explanations

Comparison of Machine Learning Methods for Predicting Winter Wheat Yield in Germany

Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting

Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization

Surgical Gesture Recognition Based on Bidirectional Multi-Layer Independently RNN with Explainable Spatial Feature Extraction

Failing Conceptually: Concept-Based Explanations of Dataset Shift

A Survey on Deep Learning-based Architectures for Semantic Segmentation on 2D images

A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts

Convergence Analysis and System Design for Federated Learning over Wireless Networks

Understanding the Failure Modes of Out-of-Distribution Generalization

A First Look: Towards Explainable TextVQA Models via Visual and Textual Explanations

Fourier Neural Networks as Function Approximators and Differential Equation Solvers

Finding High-Value Training Data Subset through Differentiable Convex Programming

Weakly Supervised Multi-task Learning for Concept-based Explainability

Predicting Depressive Symptom Severity through Individuals' Nearby Bluetooth Devices Count Data Collected by Mobile Phones: A Preliminary Longitudinal Study

Explainable AI For COVID-19 CT Classifiers: An Initial Comparison Study

Interpretable feature subset selection: A Shapley value based approach

EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case

The Geometry of Over-parameterized Regression and Adversarial Perturbations

Increasing the efficiency of randomized trial estimates via linear adjustment for a prognostic score

DA-DGCEx: Ensuring Validity of Deep Guided Counterfactual Explanations With Distribution-Aware Autoencoder Loss

Patch Shortcuts: Interpretable Proxy Models Efficiently Find Black-Box Vulnerabilities

SSLM: Self-Supervised Learning for Medical Diagnosis from MR Video

Understanding and Accelerating EM Algorithm's Convergence by Fair Competition Principle and Rate-Verisimilitude Function

Interpretation of multi-label classification models using shapley values

Revisiting The Evaluation of Class Activation Mapping for Explainability: A Novel Metric and Experimental Analysis

Hierarchical entropy and domain interaction to understand the structure in an image

Mapping the Internet: Modelling Entity Interactions in Complex Heterogeneous Networks

Random Reshuffling with Variance Reduction: New Analysis and Better Rates

SAS: A Simple, Accurate and Scalable Node Classification Algorithm

Fast Global Convergence for Low-rank Matrix Recovery via Riemannian Gradient Descent with Random Initialization

Spectral Bias and Task-Model Alignment Explain Generalization in Kernel Regression and Infinitely Wide Neural Networks

Towards Human-Understandable Visual Explanations:Imperceptible High-frequency Cues Can Better Be Removed

Coarse- and fine-scale geometric information content of Multiclass Classification and implied Data-driven Intelligence

Considerations Across Three Cultures: Parametric Regressions, Interpretable Algorithms, and Complex Algorithms

The Impact of Activation Sparsity on Overfitting in Convolutional Neural Networks

Understanding Prediction Discrepancies in Machine Learning Classifiers

Individual Explanations in Machine Learning Models: A Survey for Practitioners

Classical and quantum regression analysis for the optoelectronic performance of NTCDA/p-Si UV photodiode

Context-self contrastive pretraining for crop type semantic segmentation

Evaluations and Methods for Explanation through Robustness Analysis

DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations

Triplot: model agnostic measures and visualisations for variable importance in predictive models that take into account the hierarchical correlation structure

BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

A Novel Approach for Semiconductor Etching Process with Inductive Biases

No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks

Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting

Rule Extraction in Unsupervised Anomaly Detection for Model Explainability: Application to OneClass SVM

MultiMix: Sparingly Supervised, Extreme Multitask Learning From Medical Images

Analyzing Finite Neural Networks: Can We Trust Neural Tangent Kernel Theory?

Spatiotemporal Data Mining: A Survey on Challenges and Open Problems

Joint Learning of Neural Transfer and Architecture Adaptation for Image Recognition

Neural Response Interpretation through the Lens of Critical Pathways

This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition

Explaining Classifiers using Adversarial Perturbations on the Perceptual Ball

AdjointBackMap: Reconstructing Effective Decision Hypersurfaces from CNN Layers Using Adjoint Operators

Revisiting Deep Local Descriptor for Improved Few-Shot Classification

Linking average- and worst-case perturbation robustness via class selectivity and dimensionality

Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate

ZeroGrad : Mitigating and Explaining Catastrophic Overfitting in FGSM Adversarial Training

Building Reliable Explanations of Unreliable Neural Networks: Locally Smoothing Perspective of Model Interpretation

Understanding the role of importance weighting for deep learning

Visual Explanations from Spiking Neural Networks using Interspike Intervals

Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation

PureGaze: Purifying Gaze Feature for Generalizable Gaze Estimation

Out-of-Distribution Detection of Melanoma using Normalizing Flows

The Selectivity and Competition of the Mind's Eye in Visual Perception

The Success of AdaBoost and Its Application in Portfolio Management

Explainability: Relevance based Dynamic Deep Learning Algorithm for Fault Detection and Diagnosis in Chemical Processes

Interpreting Deep Learning Models with Marginal Attribution by Conditioning on Quantiles

Delving into Variance Transmission and Normalization: Shift of Average Gradient Makes the Network Collapse

Weighted Neural Tangent Kernel: A Generalized and Improved Network-Induced Kernel

Cascade Weight Shedding in Deep Neural Networks: Benefits and Pitfalls for Network Pruning

Towards Scalable and Unified Example-based Explanation and Outlier Detection

Explainable Adversarial Attacks in Deep Neural Networks Using Activation Profiles

Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations

Classifications based on response times for detecting early-stage Alzheimer's disease

Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images

Interpretability of a Deep Learning Model in the Application of Cardiac MRI Segmentation with an ACDC Challenge Dataset

Explaining Credit Risk Scoring through Feature Contribution Alignment with Expert Risk Analysts

A new interpretable unsupervised anomaly detection method based on residual explanation

TensorFlow Lite Micro: Embedded Machine Learning on TinyML Systems

Backward Feature Correction: How Deep Learning Performs Deep Learning

Discovery of Physics and Characterization of Microstructure from Data with Bayesian Hidden Physics Models

BDD4BNN: A BDD-based Quantitative Analysis Framework for Binarized Neural Networks

Explainable AI by BAPC -- Before and After correction Parameter Comparison

Learning by Self-Explanation, with Application to Neural Architecture Search

Robustness to Pruning Predicts Generalization in Deep Neural Networks

SISE-PC: Semi-supervised Image Subsampling for Explainable Pathology

Explaining dimensionality reduction results using Shapley values

A Comparative Approach to Explainable Artificial Intelligence Methods in Application to High-Dimensional Electronic Health Records: Examining the Usability of XAI

Hierarchical Self Attention Based Autoencoder for Open-Set Human Activity Recognition

Explaining the data or explaining a model? Shapley values that uncover non-linear dependencies

Towards Understanding Hierarchical Learning: Benefits of Neural Representations

Is Simple Uniform Sampling Efficient for Center-Based Clustering With Outliers: When and Why?

Explainable Machine Learning for Public Policy: Use Cases, Gaps, and Research Directions

Hard-label Manifolds: Unexpected Advantages of Query Efficiency for Finding On-manifold Adversarial Examples

Revisiting Knowledge Distillation via Label Smoothing Regularization

Greedy Search Algorithms for Unsupervised Variable Selection: A Comparative Study

ICAM-reg: Interpretable Classification and Regression with Feature Attribution for Mapping Neurological Phenotypes in Individual Scans

Learning Multi-layer Graphs and a Common Representation for Clustering

Luring of transferable adversarial perturbations in the black-box paradigm

Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates

On the effectiveness of adversarial training against common corruptions

Predicting Driver Fatigue in Automated Driving with Explainability

Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations

Deep Learning Based Decision Support for Medicine -- A Case Study on Skin Cancer Diagnosis

A Comprehensive Study on Face Recognition Biases Beyond Demographics

Interpretable Artificial Intelligence through the Lens of Feature Interaction

Robustness of classifiers to universal perturbations: a geometric perspective

A survey of algorithmic recourse: definitions, formulations, solutions, and prospects

Understanding Robustness in Teacher-Student Setting: A New Perspective

The Mathematics Behind Spectral Clustering And The Equivalence To PCA

Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks

Shapley Flow: A Graph-based Approach to Interpreting Model Predictions

If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques

Efficient Algorithms for Stochastic Repeated Second-price Auctions

Spurious Local Minima Are Common for Deep Neural Networks with Piecewise Linear Activations

Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications

On Interpretability and Similarity in Concept-Based Machine Learning

Arguments for the Unsuitability of Convolutional Neural Networks for Non--Local Tasks

Investigating Estimated Kolmogorov Complexity as a Means of Regularization for Link Prediction

Home and destination attachment: study of cultural integration on Twitter

Why do classifier accuracies show linear trends under distribution shift?

Wider Vision: Enriching Convolutional Neural Networks via Alignment to External Knowledge Bases

Shapley values for feature selection: The good, the bad, and the axioms

Nonparametric Regression on Low-Dimensional Manifolds using Deep ReLU Networks : Function Approximation and Statistical Recovery

Symbolic regression for scientific discovery: an application to wind speed forecasting

Defending SVMs against Poisoning Attacks: the Hardness and DBSCAN Approach

Discovering Dynamic Salient Regions with Spatio-Temporal Graph Neural Networks

Meta-learning on Spectral Images of Electroencephalogram of Schizophenics

Ada-SISE: Adaptive Semantic Input Sampling for Efficient Explanation of Convolutional Neural Networks

Attribution Mask: Filtering Out Irrelevant Features By Recursively Focusing Attention on Inputs of DNNs

Universal Adversarial Perturbations Through the Lens of Deep Steganography: Towards A Fourier Perspective

Physics-Informed Graphical Neural Network for Parameter & State Estimations in Power Systems

Novel Techniques to Assess Predictive Systems and Reduce Their Alarm Burden

Saliency is a Possible Red Herring When Diagnosing Poor Generalization

Deep multi-stations weather forecasting: explainable recurrent convolutional neural networks

Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI

A Quantitative Perspective on Values of Domain Knowledge for Machine Learning

Estimation and Applications of Quantiles in Deep Binary Classification

Towards Designing Computer Vision-based Explainable-AI Solution: A Use Case of Livestock Mart Industry

Achieving Explainability for Plant Disease Classification with Disentangled Variational Autoencoders

Dimension Free Generalization Bounds for Non Linear Metric Learning

Adai: Separating the Effects of Adaptive Learning Rate and Momentum Inertia

Design of Dynamic Experiments for Black-Box Model Discrimination

Convolutional Neural Network Interpretability with General Pattern Theory

Effects of Number of Filters of Convolutional Layers on Speech Recognition Model Accuracy

Key Technology Considerations in Developing and Deploying Machine Learning Models in Clinical Radiology Practice

Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals

SPACE: Structured Compression and Sharing of Representational Space for Continual Learning

Directive Explanations for Actionable Explainability in Machine Learning Applications

A Survey on Understanding, Visualizations, and Explanation of Deep Neural Networks

Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks

Linear Frequency Principle Model to Understand the Absence of Overfitting in Neural Networks

Stimuli-Sensitive Hawkes Processes for Personalized Student Procrastination Modeling

Graph Neural Networks: Architectures, Stability and Transferability

Learning Hierarchical Integration of Foveal and Peripheral Vision for Vergence Control by Active Efficient Coding

Quantifying Explainability of Saliency Methods in Deep Neural Networks

Jane Jacobs in the Sky: Predicting Urban Vitality with Open Satellite Data

On the Origin of Implicit Regularization in Stochastic Gradient Descent

A general approach to compute the relevance of middle-level input features

Better sampling in explanation methods can prevent dieselgate-like deception

GLocalX -- From Local to Global Explanations of Black Box AI Models

Probabilistic Robustness Analysis for DNNs based on PAC Learning

Show or Suppress? Managing Input Uncertainty in Machine Learning Model Explanations

Improved Training of Sparse Coding Variational Autoencoder via Weight Normalization

i-Algebra: Towards Interactive Interpretability of Deep Neural Networks

Gravity Optimizer: a Kinematic Approach on Optimization in Deep Learning

Rethinking Semantic Segmentation Evaluation for Explainability and Model Selection

Stable Recovery of Entangled Weights: Towards Robust Identification of Deep Neural Networks from Minimal Samples

Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation

Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits

Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction

Learning from pandemics: using extraordinary events can improve disease now-casting models

Explainable Online Validation of Machine Learning Models for Practical Applications

MARGIN: Uncovering Deep Neural Networks using Graph Signal Analysis

Interpretable and Trustworthy Deepfake Detection via Dynamic Prototypes

Explainability of vision-based autonomous driving systems: Review and challenges

Explainable Deep Behavioral Sequence Clustering for Transaction Fraud Detection

Pneumonia Detection on Chest X-ray using Radiomic Features and Contrastive Learning

System Design for a Data-driven and Explainable Customer Sentiment Monitor

Modeling Household Online Shopping Demand in the U.S.: A Machine Learning Approach and Comparative Investigation between 2009 and 2017

Does Learning Require Memorization? A Short Tale about a Long Tail

Mean-field Behaviour of Neural Tangent Kernel for Deep Neural Networks

Unsupervised Model Adaptation for Continual Semantic Segmentation

Predicting Illness for a Sustainable Dairy Agriculture: Predicting and Explaining the Onset of Mastitis in Dairy Cows

ISETAuto: Detecting vehicles with depth and radiance information

Demystifying Deep Neural Networks Through Interpretation: A Survey

A Canonical Architecture For Predictive Analytics on Longitudinal Patient Records

Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning

Cyclic Boosting -- an explainable supervised machine learning algorithm

Matrix Normal PCA for Interpretable Dimension Reduction and Graphical Noise Modeling

Understanding the Ability of Deep Neural Networks to Count Connected Components in Images

Conditional Local Filters with Explainers for Spatio-Temporal Forecasting

Beyond Low-frequency Information in Graph Convolutional Networks

Factor Analysis, Probabilistic Principal Component Analysis, Variational Inference, and Variational Autoencoder: Tutorial and Survey

Combining Graph Neural Networks and Spatio-temporal Disease Models to Predict COVID-19 Cases in Germany

Explanations of Machine Learning predictions: a mandatory step for its application to Operational Processes

SkiNet: A Deep Learning Solution for Skin Lesion Diagnosis with Uncertainty Estimation and Explainability

dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python

Explaining Convolutional Neural Networks through Attribution-Based Input Sampling and Block-Wise Feature Aggregation

Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study

Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems

RG-Flow: A hierarchical and explainable flow model based on renormalization group and sparse prior

A Survey on the Visual Perceptions of Gaussian Noise Filtering on Photography

Spacecraft Collision Risk Assessment with Probabilistic Programming

Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging

Universal Approximation Power of Deep Residual Neural Networks via Nonlinear Control Theory

Instrument variable detection with graph learning : an application to high dimensional GIS-census data for house pricing

Predicting Generalization in Deep Learning via Metric Learning -- PGDL Shared task

Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example

Implicit bias of deep linear networks in the large learning rate phase

Adversarial Training Reduces Information and Improves Transferability

Explainable Recommendation Systems by Generalized Additive Models with Manifest and Latent Interactions

E2E-FS: An End-to-End Feature Selection Method for Neural Networks

Combining Similarity and Adversarial Learning to Generate Visual Explanation: Application to Medical Image Classification

Dependency Decomposition and a Reject Option for Explainable Models

Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing

Restyling Images with the Bangladeshi Paintings Using Neural Style Transfer: A Comprehensive Experiment, Evaluation, and Human Perspective

Improving healthcare access management by predicting patient no-show behaviour

Debiased-CAM for bias-agnostic faithful visual explanations of deep convolutional networks

Explanation-Guided Training for Cross-Domain Few-Shot Classification

Deep Unsupervised Image Anomaly Detection: An Information Theoretic Framework

Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective

A General Computational Framework to Measure the Expressiveness of Complex Networks Using a Tighter Upper Bound of Linear Regions

Why Adversarial Interaction Creates Non-Homogeneous Patterns: A Pseudo-Reaction-Diffusion Model for Turing Instability

Structured Attention Graphs for Understanding Deep Image Classifications

An explainable deep vision system for animal classification and detection in trail-camera images with automatic post-deployment retraining

Explainable Artificial Intelligence: How Subsets of the Training Data Affect a Prediction

Efficient and Scalable Structure Learning for Bayesian Networks: Algorithms and Applications

Does the dataset meet your expectations? Explaining sample representation in image data

FuseVis: Interpreting neural networks for image fusion using per-pixel saliency visualization

Benefit of deep learning with non-convex noisy gradient descent: Provable excess risk bound and superiority to kernel methods

Challenging common interpretability assumptions in feature attribution explanations

Visualization of Supervised and Self-Supervised Neural Networks via Attribution Guided Factorization

Interpretability and Explainability: A Machine Learning Zoo Mini-tour

The Resistance to Label Noise in K-NN and DNN Depends on its Concentration

Using Cross-Loss Influence Functions to Explain Deep Network Representations

Insights into Ordinal Embedding Algorithms: A Systematic Evaluation

Generative Classifiers as a Basis for Trustworthy Image Classification

The Self-Simplifying Machine: Exploiting the Structure of Piecewise Linear Neural Networks to Create Interpretable Models

Regularization and False Alarms Quantification: Two Sides of the Explainability Coin

Explaining Machine Learning Models using Entropic Variable Projection

Learning Universal Shape Dictionary for Realtime Instance Segmentation

Rethinking Positive Aggregation and Propagation of Gradients in Gradient-based Saliency Methods

Interpreting and Improving Adversarial Robustness of Deep Neural Networks with Neuron Sensitivity

Learning Explainable Interventions to Mitigate HIV Transmission in Sex Workers Across Five States in India

A Selective Survey on Versatile Knowledge Distillation Paradigm for Neural Network Models

ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery

Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach

Road Scene Graph: A Semantic Graph-Based Scene Representation Dataset for Intelligent Vehicles

Learning Curves for Deep Neural Networks: A Gaussian Field Theory Perspective

Prediction of neonatal mortality in Sub-Saharan African countries using data-level linkage of multiple surveys

Match Them Up: Visually Explainable Few-shot Image Classification

xFraud: Explainable Fraud Transaction Detection on Heterogeneous Graphs

Gini in a Bottleneck: Sparse Molecular Representations for Graph Convolutional Neural Networks

Low-Resolution Face Recognition In Resource-Constrained Environments

Accurate and Lightweight Image Super-Resolution with Model-Guided Deep Unfolding Network

CancerNet-SCa: Tailored Deep Neural Network Designs for Detection of Skin Cancer from Dermoscopy Images

Explaining by Removing: A Unified Framework for Model Explanation

Pruning neural networks without any data by iteratively conserving synaptic flow

Data Representing Ground-Truth Explanations to Evaluate XAI Methods

Abstracting Deep Neural Networks into Concept Graphs for Concept Level Interpretability

Domain Adaptation based Technique for Image Emotion Recognition using Pre-trained Facial Expression Recognition Models

The Neural Tangent Link Between CNN Denoisers and Non-Local Filters

Natural Disaster Classification using Aerial Photography Explainable for Typhoon Damaged Feature

Multi-label classification: do Hamming loss and subset accuracy really conflict with each other?

Optimal Local Explainer Aggregation for Interpretable Prediction

A metric for sets of trajectories that is practical and mathematically consistent

Sub-Optimal Local Minima Exist for Neural Networks with Almost All Non-Linear Activations

SS-CAM: Smoothed Score-CAM for Sharper Visual Feature Localization

De-randomized PAC-Bayes Margin Bounds: Applications to Non-convex and Non-smooth Predictors

Explainable Knowledge Tracing Models for Big Data: Is Ensembling an Answer?

Towards Visually Explaining Video Understanding Networks with Perturbation

Feature Removal Is a Unifying Principle for Model Explanation Methods

Explainable AI meets Healthcare: A Study on Heart Disease Dataset

Understanding Double Descent Requires a Fine-Grained Bias-Variance Decomposition

Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay

Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks

MACE: Model Agnostic Concept Extractor for Explaining Image Classification Networks

Diverse Image Captioning with Context-Object Split Latent Spaces

Compressed Sensing via Measurement-Conditional Generative Models

AADS: Augmented Autonomous Driving Simulation using Data-driven Algorithms

Enforcing Interpretability and its Statistical Impacts: Trade-offs between Accuracy and Interpretability

Unbiased and Efficient Log-Likelihood Estimation with Inverse Binomial Sampling

A Probabilistic Representation of Deep Learning for Improving The Information Theoretic Interpretability

Q-FIT: The Quantifiable Feature Importance Technique for Explainable Machine Learning

Examining the causal structures of deep neural networks using information theory

GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model's Prediction

Relative Flatness and Generalization in the Interpolation Regime

Convergence Acceleration via Chebyshev Step: Plausible Interpretation of Deep-Unfolded Gradient Descent

Convergence and Stability of Graph Convolutional Networks on Large Random Graphs

Towards explainable classifiers using the counterfactual approach -- global explanations for discovering bias in data

Explaining Predictions by Approximating the Local Decision Boundary

DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling

FasterRCNN Monitoring of Road Damages: Competition and Deployment

High resolution weakly supervised localization architectures for medical images

Precise Statistical Analysis of Classification Accuracies for Adversarial Training

Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond

Diversity-Based Generalization for Unsupervised Text Classification under Domain Shift

Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher

Stronger, Faster and More Explainable: A Graph Convolutional Baseline for Skeleton-based Action Recognition

DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks

Implicit Regularization in Deep Learning May Not Be Explainable by Norms

Squashing activation functions in benchmark tests: towards eXplainable Artificial Intelligence using continuous-valued logic

ATHENA: A Framework based on Diverse Weak Defenses for Building Adversarial Defense

Overfitting or Underfitting? Understand Robustness Drop in Adversarial Training

Altruist: Argumentative Explanations through Local Interpretations of Predictive Models

Hold me tight! Influence of discriminative features on deep network boundaries

Human-interpretable model explainability on high-dimensional data

MFPP: Morphological Fragmental Perturbation Pyramid for Black-Box Model Explanations

PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks

Towards Theoretically Understanding Why SGD Generalizes Better Than ADAM in Deep Learning

Simplifying the explanation of deep neural networks with sufficient and necessary feature-sets: case of text classification

Handling Imbalanced Data: A Case Study for Binary Class Problems

A Unified Approach to Interpreting and Boosting Adversarial Transferability

Algorithmic Recourse: from Counterfactual Explanations to Interventions

Interpretations are useful: penalizing explanations to align neural networks with prior knowledge

Improve Adversarial Robustness via Weight Penalization on Classification Layer

Creation and Validation of a Chest X-Ray Dataset with Eye-tracking and Report Dictation for AI Development

Explaining How Deep Neural Networks Forget by Deep Visualization

Deep learning models for predictive maintenance: a survey, comparison, challenges and prospect

Explaining image classifiers by removing input features using generative models

Recovering Causal Structures from Low-Order Conditional Independencies

Self-supervised Exposure Trajectory Recovery for Dynamic Blur Estimation

Visualizing Color-wise Saliency of Black-Box Image Classification Models

Quantifying Statistical Significance of Neural Network Representation-Driven Hypotheses by Selective Inference

Attention Guided Semantic Relationship Parsing for Visual Question Answering

Learning and Interpreting Multi-Multi-Instance Learning Networks

Stuttering Speech Disfluency Prediction using Explainable Attribution Vectors of Facial Muscle Movements

Domain aware medical image classifier interpretation by counterfactual impact analysis

Understanding the Role of Adversarial Regularization in Supervised Learning

Accurate and Robust Feature Importance Estimation under Distribution Shifts

Improving Interpretability for Computer-aided Diagnosis tools on Whole Slide Imaging with Multiple Instance Learning and Gradient-based Explanations

Where is the Model Looking At?--Concentrate and Explain the Network Attention

Offline versus Online Triplet Mining based on Extreme Distances of Histopathology Patches

Distillation of Weighted Automata from Recurrent Neural Networks using a Spectral Approach

An Explainable Model for EEG Seizure Detection based on Connectivity Features

A light-weight method to foster the (Grad)CAM interpretability and explainability of classification networks

What Do You See? Evaluation of Explainable Artificial Intelligence (XAI) Interpretability through Neural Backdoors

Explainable, Stable, and Scalable Graph Convolutional Networks for Learning Graph Representation

Stochastic Neighbor Embedding with Gaussian and Student-t Distributions: Tutorial and Survey

Uncertainty-aware Attention Graph Neural Network for Defending Adversarial Attacks

Joint and Progressive Subspace Analysis (JPSA) with Spatial-Spectral Manifold Alignment for Semi-Supervised Hyperspectral Dimensionality Reduction

SecDD: Efficient and Secure Method for Remotely Training Neural Networks

Introspective Learning by Distilling Knowledge from Online Self-explanation

Multidimensional Scaling, Sammon Mapping, and Isomap: Tutorial and Survey

Rethinking Softmax with Cross-Entropy: Neural Network Classifier as Mutual Information Estimator

Analysis of Generalizability of Deep Neural Networks Based on the Complexity of Decision Boundary

Better Model Selection with a new Definition of Feature Importance

Explainable Matrix -- Visualization for Global and Local Interpretability of Random Forest Classification Ensembles

A Qualitative Study of the Dynamic Behavior of Adaptive Gradient Algorithms

Accelerating COVID-19 Differential Diagnosis with Explainable Ultrasound Image Analysis

MeLIME: Meaningful Local Explanation for Machine Learning Models

Play MNIST For Me! User Studies on the Effects of Post-Hoc, Example-Based Explanations & Error Rates on Debugging a Deep Learning, Black-Box Classifier

On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning

A Leisurely Look at Versions and Variants of the Cross Validation Estimator

Region Comparison Network for Interpretable Few-shot Image Classification

FOCAL: A Forgery Localization Framework based on Video Coding Self-Consistency

On the Global Convergence Rates of Softmax Policy Gradient Methods

Error estimate for a universal function approximator of ReLU network with a local connection

ALEX: Active Learning based Enhancement of a Model's Explainability

Scene-Graph Augmented Data-Driven Risk Assessment of Autonomous Vehicle Decisions

Short-term Traffic Prediction with Deep Neural Networks: A Survey

Making Neural Networks Interpretable with Attribution: Application to Implicit Signals Prediction

Why do These Match? Explaining the Behavior of Image Similarity Models

Explainable Disease Classification via weakly-supervised segmentation

Kernel-based Graph Learning from Smooth Signals: A Functional Viewpoint

Emergent symbolic language based deep medical image classification

Visual Summary of Value-level Feature Attribution in Prediction Classes with Recurrent Neural Networks

Utilizing Explainable AI for Quantization and Pruning of Deep Neural Networks

On the Explanation of Machine Learning Predictions in Clinical Gait Analysis

DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models

Visual stream connectivity predicts assessments of image quality

Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia

The Neural Tangent Kernel in High Dimensions: Triple Descent and a Multi-Scale Theory of Generalization

Predictive and Causal Implications of using Shapley Value for Model Interpretation

On Learning Language-Invariant Representations for Universal Machine Translation

c-Eval: A Unified Metric to Evaluate Feature-based Explanations via Perturbation

Deep regularization and direct training of the inner layers of Neural Networks with Kernel Flows

MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models

Convex Density Constraints for Computing Plausible Counterfactual Explanations

Looking in the Right place for Anomalies: Explainable AI through Automatic Location Learning

A Causal Lens for Peeking into Black Box Predictive Models: Predictive Model Interpretation via Causal Attribution

Peri-Diagnostic Decision Support Through Cost-Efficient Feature Acquisition at Test-Time

A Comprehensive Review of Skeleton-based Movement Assessment Methods

Adversarial Robustness on In- and Out-Distribution Improves Explainability

OptiLIME: Optimized LIME Explanations for Diagnostic Computer Algorithms

Learning Modality Interaction for Temporal Sentence Localization and Event Captioning in Videos

Closed-Form Expressions for Global and Local Interpretation of Tsetlin Machines with Applications to Explaining High-Dimensional Data

CPAS: the UK's National Machine Learning-based Hospital Capacity Planning System for COVID-19

Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity

Fair Marriage Principle and Initialization Map for the EM Algorithm

ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis

Illumination invariant hyperspectral image unmixing based on a digital surface model

Attention-guided Quality Assessment for Automated Cryo-EM Grid Screening

Weak and Strong Gradient Directions: Explaining Memorization, Generalization, and Hardness of Examples at Scale

DeepNNK: Explaining deep models and their generalization using polytope interpolation

An interpretable semi-supervised classifier using two different strategies for amended self-labeling

Scientific Discovery by Generating Counterfactuals using Image Translation

PySS3: A Python package implementing a novel text classifier with visualization tools for Explainable AI

Explaining Image Classifiers using Statistical Fault Localization

Explainable Deep Learning for Uncovering Actionable Scientific Insights for Materials Discovery and Design

6D Camera Relocalization in Ambiguous Scenes via Continuous Multimodal Inference

GLAD: GLocalized Anomaly Detection via Human-in-the-Loop Learning

Neural Topic Models with Survival Supervision: Jointly Predicting Time-to-Event Outcomes and Learning How Clinical Features Relate

Controversial stimuli: pitting neural networks against each other as models of human recognition

Explainable Recommendation via Interpretable Feature Mapping and Evaluation of Explainability

Locality Guided Neural Networks for Explainable Artificial Intelligence

Distangling Biological Noise in Cellular Images with a focus on Explainability

Usefulness of interpretability methods to explain deep learning based plant stress phenotyping

Attack of the Tails: Yes, You Really Can Backdoor Federated Learning

Fast Training of Deep Neural Networks Robust to Adversarial Perturbations

Contextual Encoder-Decoder Network for Visual Saliency Prediction

On Second-Order Group Influence Functions for Black-Box Predictions

Solving Bayesian Network Structure Learning Problem with Integer Linear Programming

Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks

Understanding More about Human and Machine Attention in Deep Neural Networks

Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions

Concise Explanations of Neural Networks using Adversarial Training

D-NetPAD: An Explainable and Interpretable Iris Presentation Attack Detector

Analyzing the Interpretability Robustness of Self-Explaining Models

Explaining predictive models with mixed features using Shapley values and conditional inference trees

Weakly-Supervised Segmentation for Disease Localization in Chest X-Ray Images

A Hybrid Distribution Feeder Long-Term Load Forecasting Method Based on Sequence Prediction

Fairness constraints can help exact inference in structured prediction

Data-driven Regularization via Racecar Training for Generalizing Neural Networks

On the Demystification of Knowledge Distillation: A Residual Network Perspective

Explaining Explanations: Axiomatic Feature Interactions for Deep Networks

Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothness

The Explanation Game: Explaining Machine Learning Models Using Shapley Values

CognitiveCNN: Mimicking Human Cognitive Models to resolve Texture-Shape Bias

Identification of Model Uncertainty via Optimal Design of Experiments Applied to a Mechanical Press

Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey

Order and Chaos: NTK views on DNN Normalization, Checkerboard and Boundary Artifacts

X-SHAP: towards multiplicative explainability of Machine Learning

Compression based bound for non-compressed network: unified generalization error analysis of large compressible deep neural network

Weakly-correlated synapses promote dimension reduction in deep neural networks

Inducing Hierarchical Compositional Model by Sparsifying Generator Network

Embedded Encoder-Decoder in Convolutional Networks Towards Explainable AI

Does Explainable Artificial Intelligence Improve Human Decision-Making?

TX-Ray: Quantifying and Explaining Model-Knowledge Transfer in (Un-)Supervised NLP

No one-hidden-layer neural network can represent multivariable functions

Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection

Accelerating Training in Artificial Neural Networks with Dynamic Mode Decomposition

How Much Can I Trust You? -- Quantifying Uncertainties in Explaining Neural Networks

A Programmatic and Semantic Approach to Explaining and DebuggingNeural Network Based Object Detectors

Generalized SHAP: Generating multiple types of explanations in machine learning

Meta Transition Adaptation for Robust Deep Learning with Noisy Labels

On Completeness-aware Concept-Based Explanations in Deep Neural Networks

Diagnosis and Analysis of Celiac Disease and Environmental Enteropathy on Biopsy Images using Deep Learning Approaches

Scalable Partial Explainability in Neural Networks via Flexible Activation Functions

3D Point Cloud Feature Explanations Using Gradient-Based Methods

A Safety Framework for Critical Systems Utilising Deep Neural Networks

Contextual Prediction Difference Analysis for Explaining Individual Image Classifications

SIDU: Similarity Difference and Uniqueness Method for Explainable AI

Toward Optimal Probabilistic Active Learning Using a Bayesian Approach

Make Hawkes Processes Explainable by Decomposing Self-Triggering Kernels

A Personalized Affective Memory Neural Model for Improving Emotion Recognition

One-vs-Rest Network-based Deep Probability Model for Open Set Recognition

SafeML: Safety Monitoring of Machine Learning Classifiers through Statistical Difference Measure

Rationalizing Text Matching: Learning Sparse Alignments via Optimal Transport

AutoDiscern: Rating the Quality of Online Health Information with Hierarchical Encoder Attention-based Neural Networks

Understanding Graph Isomorphism Network for rs-fMRI Functional Connectivity Analysis

Fair Inputs and Fair Outputs: The Incompatibility of Fairness in Privacy and Accuracy

From unbiased MDI Feature Importance to Explainable AI for Trees

Region Proposals for Saliency Map Refinement for Weakly-supervised Disease Localisation and Classification

Gender Slopes: Counterfactual Fairness for Computer Vision Models by Attribute Manipulation

Automated Copper Alloy Grain Size Evaluation Using a Deep-learning CNN

Applying Genetic Programming to Improve Interpretability in Machine Learning Models

DDD20 End-to-End Event Camera Driving Dataset: Fusing Frames and Events with Deep Learning for Improved Steering Prediction

Sustainable Recreational Fishing Using a Novel Electrical Muscle Stimulation (EMS) Lure and Ensemble Network Algorithm to Maximize Catch and Release Survivability

Triaging moderate COVID-19 and other viral pneumonias from routine blood tests

A Biologically Inspired Feature Enhancement Framework for Zero-Shot Learning

What is the Value of Data? On Mathematical Methods for Data Quality Estimation

Capturing and Explaining Trajectory Singularities using Composite Signal Neural Networks

Alternating Maximization: Unifying Framework for 8 Sparse PCA Formulations and Efficient Parallel Codes

A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds

SurvLIME-Inf: A simplified modification of SurvLIME for explanation of machine learning survival models

Explaining AI-based Decision Support Systems using Concept Localization Maps

On Network Science and Mutual Information for Explaining Deep Neural Networks

Heterogeneous Knowledge Distillation using Information Flow Modeling

The Information Bottleneck Problem and Its Applications in Machine Learning

Generalization Error of Generalized Linear Models in High Dimensions

Perturb More, Trap More: Understanding Behaviors of Graph Neural Networks

Towards causal generative scene models via competition of experts

Bayesian Deep Learning and a Probabilistic Perspective of Generalization

COLAM: Co-Learning of Deep Neural Networks and Soft Labels via Alternating Minimization

An Extension of LIME with Improvement of Interpretability and Fidelity

Explainable Deep CNNs for MRI-Based Diagnosis of Alzheimer's Disease

Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks

AMC-Loss: Angular Margin Contrastive Loss for Improved Explainability in Image Classification

Supervised Autoencoders Learn Robust Joint Factor Models of Neural Activity

Learning Unsplit-field-based PML for the FDTD Method by Deep Differentiable Forest

Color inference from semantic labeling for person search in videos

There and Back Again: Revisiting Backpropagation Saliency Methods

Explaining Motion Relevance for Activity Recognition in Video Deep Learning Models

Advances in Bayesian Probabilistic Modeling for Industrial Applications

Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks

RelatIF: Identifying Explanatory Training Examples via Relative Influence

High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks

An Inverse-free Truncated Rayleigh-Ritz Method for Sparse Generalized Eigenvalue Problem

Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses

Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations

Explainable Object-induced Action Decision for Autonomous Vehicles

Aggregating explanation methods for stable and robust explainability

Weakly and Semi Supervised Detection in Medical Imaging via Deep Dual Branch Net

SurvLIME: A method for explaining machine learning survival models

An Information-Theoretic Approach to Personalized Explainable Machine Learning

Counterfactual Samples Synthesizing for Robust Visual Question Answering

Explainable Deep Classification Models for Domain Generalization

Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems

Addressing multiple metrics of group fairness in data-driven decision making

Cloth in the Wind: A Case Study of Physical Measurement through Simulation

MobilePose: Real-Time Pose Estimation for Unseen Objects with Weak Shape Supervision

Captioning Images with Novel Objects via Online Vocabulary Expansion

TIME: A Transparent, Interpretable, Model-Adaptive and Explainable Neural Network for Dynamic Physical Processes

Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation

Beyond exploding and vanishing gradients: analysing RNN training using attractors and smoothness

On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks

On the Power and Limitations of Random Features for Understanding Neural Networks

Image-based OoD-Detector Principles on Graph-based Input Data in Human Action Recognition

Single Unit Status in Deep Convolutional Neural Network Codes for Face Identification: Sparseness Redefined

ACE -- An Anomaly Contribution Explainer for Cyber-Security Applications

The autofeat Python Library for Automated Feature Engineering and Selection

Fundamental Issues Regarding Uncertainties in Artificial Neural Networks

Coherent Gradients: An Approach to Understanding Generalization in Gradient Descent-based Optimization

Breaking Batch Normalization for better explainability of Deep Neural Networks through Layer-wise Relevance Propagation

Stealing Black-Box Functionality Using The Deep Neural Tree Architecture

On the Role of Dataset Quality and Heterogeneity in Model Confidence

Shapley Values of Reconstruction Errors of PCA for Explaining Anomaly Detection

Mixing autoencoder with classifier: conceptual data visualization

NeuroFabric: Identifying Ideal Topologies for Training A Priori Sparse Networks

CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods

A Modified Perturbed Sampling Method for Local Interpretable Model-agnostic Explanation

The intriguing role of module criticality in the generalization of deep networks

Classifying the classifier: dissecting the weight space of neural networks

Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model-Agnostic Interpretations

A deep-learning view of chemical space designed to facilitate drug discovery

On Learning Causal Structures from Non-Experimental Data without Any Faithfulness Assumption

Explaining individual predictions when features are dependent: More accurate approximations to Shapley values

Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks

CHAIN: Concept-harmonized Hierarchical Inference Interpretation of Deep Convolutional Neural Networks

Obstruction level detection of sewer videos using convolutional neural networks

Four Principles of Explainable AI as Applied to Biometrics and Facial Forensic Algorithms

Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods

Towards Explainable Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks

On implicit regularization: Morse functions and applications to matrix factorization

Improving the Detection of Burnt Areas in Remote Sensing using Hyper-features Evolved by M3GP

One Explanation Does Not Fit All: The Promise of Interactive Explanations for Machine Learning Transparency

Efficient computation of counterfactual explanations of LVQ models

Localization of Critical Findings in Chest X-Ray without Local Annotations Using Multi-Instance Learning

Uncertainty based Class Activation Maps for Visual Question Answering

Explainable Machine Learning Control -- robust control and stability analysis

Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model

An interpretable neural network model through piecewise linear approximation

A point-wise linear model reveals reasons for 30-day readmission of heart failure patients

On the Convex Behavior of Deep Neural Networks in Relation to the Layers' Width

Consumer-Driven Explanations for Machine Learning Decisions: An Empirical Study of Robustness

Towards Interpretable and Robust Hand Detection via Pixel-wise Prediction

Predicting population neural activity in the Algonauts challenge using end-to-end trained Siamese networks and group convolutions

Explainable Machine Learning for Scientific Insights and Discoveries

Uncertainty Propagation in Deep Neural Network Using Active Subspace

Tangent-Space Gradient Optimization of Tensor Network for Machine Learning

Dissecting Catastrophic Forgetting in Continual Learning by Deep Visualization

Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets

The troublesome kernel: why deep learning for inverse problems is typically unstable

Auditing and Debugging Deep Learning Models via Decision Boundaries: Individual-level and Group-level Analysis

Neural networks are a priori biased towards Boolean functions with low entropy

A New Approach for Explainable Multiple Organ Annotation with Few Data

This Looks Like That: Deep Learning for Interpretable Image Recognition

Interpretable Visual Question Answering by Reasoning on Dependency Trees

secml: A Python Library for Secure and Explainable Machine Learning

Analysis of Video Feature Learning in Two-Stream CNNs on the Example of Zebrafish Swim Bout Classification

Uniform convergence may be unable to explain generalization in deep learning

Iterative and Adaptive Sampling with Spatial Attention for Black-Box Model Explanations

GP-ALPS: Automatic Latent Process Selection for Multi-Output Gaussian Process Models

Realization of spatial sparseness by deep ReLU nets with massive data

Interpreting Undesirable Pixels for Image Classification on Black-Box Models

How Much Can We See? A Note on Quantifying Explainability of Machine Learning Models

Interpretable Deep Neural Networks for Dimensional and Categorical Emotion Recognition in-the-wild

Unsupervised and Generic Short-Term Anticipation of Human Body Motions

CHIP: Channel-wise Disentangled Interpretation of Deep Convolutional Neural Networks

Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches

Characterization of Hemodynamic Signal by Learning Multi-View Relationships

Knowledge extraction from the learning of sequences in a long short term memory (LSTM) architecture

Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations

A Fast deflation Method for Sparse Principal Component Analysis via Subspace Projections

Increasing the adversarial robustness and explainability of capsule networks with $γ$-capsules

Extreme Learning Machine design for dealing with unrepresentative features

Attention-based Recurrent Neural Network for Urban Vehicle Trajectory Prediction

PyTorch: An Imperative Style, High-Performance Deep Learning Library

Multiscale Self Attentive Convolutions for Vision and Language Modeling

Proposed Guidelines for the Responsible Use of Explainable Machine Learning

Investigating Convolutional Neural Networks using Spatial Orderness

Time-Guided High-Order Attention Model of Longitudinal Heterogeneous Healthcare Data

Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis

Feature relevance quantification in explainable AI: A causal problem

Generalization Error Bounds of Gradient Descent for Learning Over-parameterized Deep ReLU Networks

Adversarial Attacks on Remote User Authentication Using Behavioural Mouse Dynamics

Repetitive Reprediction Deep Decipher for Semi-Supervised Learning

Explaining Models by Propagating Shapley Values of Local Components

Chasing Ghosts: Instruction Following as Bayesian State Tracking

Modeling Gestalt Visual Reasoning on the Raven's Progressive Matrices Intelligence Test Using Generative Image Inpainting Techniques

Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns

Exploiting Deep Features for Remote Sensing Image Retrieval: A Systematic Investigation

Towards a Unified Evaluation of Explanation Methods without Ground Truth

Explanation vs Attention: A Two-Player Game to Obtain Attention for VQA

Coverage Testing of Deep Learning Models using Dataset Characterization

Likelihood Assignment for Out-of-Distribution Inputs in Deep Generative Models is Sensitive to Prior Distribution Choice

SAVEHR: Self Attention Vector Representations for EHR based Personalized Chronic Disease Onset Prediction and Interpretability

Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks

Deep Generative Models Strike Back! Improving Understanding and Evaluation in Light of Unmet Expectations for OoD Data

Explaining Away Results in Accurate and Tolerant Template Matching

Explaining Convolutional Neural Networks using Softmax Gradient Layer-wise Relevance Propagation

Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse

Leveraging Model Interpretability and Stability to increase Model Robustness

Characterizing the Exact Behaviors of Temporal Difference Learning Algorithms Using Markov Jump Linear System Theory

Group Retention when Using Machine Learning in Sequential Decision Making: the Interplay between User Dynamics and Fairness

Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise

Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms

How noise affects the Hessian spectrum in overparameterized neural networks

Concept Saliency Maps to Visualize Relevant Features in Deep Generative Models

Best Practices for Convolutional Neural Networks Applied to Object Recognition in Images

Seeing the Wind: Visual Wind Speed Prediction with a Coupled Convolutional and Recurrent Neural Network

A Game Theoretic Approach to Class-wise Selective Rationalization

CXPlain: Causal Explanations for Model Interpretation under Uncertainty

Occlusions for Effective Data Augmentation in Image Classification

Over Parameterized Two-level Neural Networks Can Learn Near Optimal Feature Representations

Are Perceptually-Aligned Gradients a General Property of Robust Classifiers?

Unsupervised Robust Disentangling of Latent Characteristics for Image Synthesis

A game method for improving the interpretability of convolution neural network

Towards Further Understanding of Sparse Filtering via Information Bottleneck

Towards Quantifying Intrinsic Generalization of Deep ReLU Networks

Effect of Superpixel Aggregation on Explanations in LIME -- A Case Study with Biological Data

U-CAM: Visual Explanation using Uncertainty based Class Activation Maps

Design, Benchmarking and Explainability Analysis of a Game-Theoretic Framework towards Energy Efficiency in Smart Infrastructure

NormLime: A New Feature Importance Metric for Explaining Deep Neural Networks

FireNet: Real-time Segmentation of Fire Perimeter from Aerial Video

Roweis Discriminant Analysis: A Generalized Subspace Learning Method

Rosetta: Large scale system for text detection and recognition in images

Finding Interpretable Concept Spaces in Node Embeddings using Knowledge Bases

Discovering Molecular Functional Groups Using Graph Convolutional Neural Networks

ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations

Hypothesis Testing Interpretations and Renyi Differential Privacy

TraffickCam: Explainable Image Matching For Sex Trafficking Investigations

Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization

Interpretable Disentanglement of Neural Networks by Extracting Class-Specific Subnetwork

Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data Bias

A Novel Graphical Lasso based approach towards Segmentation Analysis in Energy Game-Theoretic Frameworks

Enriching Visual with Verbal Explanations for Relational Concepts -- Combining LIME with Aleph

Explaining a black-box using Deep Variational Information Bottleneck Approach

MonoNet: Towards Interpretable Models by Learning Monotonic Features

Towards A Unified Min-Max Framework for Adversarial Exploration and Robustness

Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos

EDUCE: Explaining model Decisions through Unsupervised Concepts Extraction

Explainable Deep Learning for Augmentation of sRNA Expression Profiles

Mildly Overparametrized Neural Nets can Memorize Training Data Efficiently

Function Preserving Projection for Scalable Exploration of High-Dimensional Data

MIC: Mining Interclass Characteristics for Improved Metric Learning

Bin-wise Temperature Scaling (BTS): Improvement in Confidence Calibration Performance through Simple Scaling Techniques

Propagated Perturbation of Adversarial Attack for well-known CNNs: Empirical Study and its Explanation

Explainable High-order Visual Question Reasoning: A New Benchmark and Knowledge-routed Network

Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead

InterpretML: A Unified Framework for Machine Learning Interpretability

Interpretable Discriminative Dimensionality Reduction and Feature Selection on the Manifold

Semantically Interpretable Activation Maps: what-where-how explanations within CNNs

Induction of Non-monotonic Logic Programs To Explain Statistical Learning Models

Learnability Can Be Independent of ZFC Axioms: Explanations and Implications

BMVC 2019: Workshop on Interpretable and Explainable Machine Vision

On the Separability of Classes with the Cross-Entropy Loss Function

Why are Saliency Maps Noisy? Cause of and Solution to Noisy Saliency Maps

Defending Against Adversarial Attacks by Suppressing the Largest Eigenvalue of Fisher Information Matrix

Consensus-based Interpretable Deep Neural Networks with Application to Mortality Prediction

When Explainability Meets Adversarial Learning: Detecting Adversarial Examples using SHAP Signatures

Explainable Deep Learning for Video Recognition Tasks: A Framework & Recommendations

Generalized Integrated Gradients: A practical method for explaining diverse ensembles

Understanding Individual Decisions of CNNs via Contrastive Backpropagation

Enhancing Explainability of Neural Networks through Architecture Constraints

Temporal Consistency Objectives Regularize the Learning of Disentangled Representations

Explainable Video Action Reasoning via Prior Knowledge and State Transitions

Machine Learning based Prediction of Hierarchical Classification of Transposable Elements

Outfit Compatibility Prediction and Diagnosis with Multi-Layered Comparison Network

Accurate and interpretable evaluation of surgical skills from kinematic data using fully convolutional neural networks

Adaptive Image-Feature Learning for Disease Classification Using Inductive Graph Networks

Discriminating Spatial and Temporal Relevance in Deep Taylor Decompositions for Explainable Activity Recognition

Requirements Engineering for Machine Learning: Perspectives from Data Scientists

Learning Credible Deep Neural Networks with Rationale Regularization

Atlas: A Dataset and Benchmark for E-commerce Clothing Product Categorization

LioNets: Local Interpretation of Neural Networks through Penultimate Layer Decoding

What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use

IEA: Inner Ensemble Average within a convolutional neural network

Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness

Linked Dynamic Graph CNN: Learning on Point Cloud via Linking Hierarchical Features

NeuroMask: Explaining Predictions of Deep Neural Networks through Mask Learning

Smooth Grad-CAM++: An Enhanced Inference Level Visualization Technique for Deep Convolutional Neural Network Models

Two-temperature logistic regression based on the Tsallis divergence

Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features

What's in the box? Explaining the black-box model through an evaluation of its interpretable features

Local Interpretation Methods to Machine Learning Using the Domain of the Feature Space

Safe Augmentation: Learning Task-Specific Transformations from Data

Not All Adversarial Examples Require a Complex Defense: Identifying Over-optimized Adversarial Examples with IQR-based Logit Thresholding

The Challenge of Imputation in Explainable Artificial Intelligence Models

Iris Recognition for Personal Identification using LAMSTAR neural network

An Empirical Study on Leveraging Scene Graphs for Visual Question Answering

The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations

Adversarial Attack Type I: Cheat Classifiers by Significant Changes

Understanding Adversarial Robustness Through Loss Landscape Geometries

Measuring the Effects of Data Parallelism on Neural Network Training

Towards Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-based Convolutional Encoders

PreCall: A Visual Interface for Threshold Optimization in ML Model Selection

Perturbation theory approach to study the latent space degeneracy of Variational Autoencoders

A review on deep learning techniques for 3D sensed data classification

All Sparse PCA Models Are Wrong, But Some Are Useful. Part I: Computation of Scores, Residuals and Explained Variance

Quantifying Transparency of Machine Learning Systems through Analysis of Contributions

Generative Counterfactual Introspection for Explainable Deep Learning

AMD Severity Prediction And Explainability Using Image Registration And Deep Embedded Clustering

A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks

HyperNOMAD: Hyperparameter optimization of deep neural networks using mesh adaptive direct search

Layer rotation: a surprisingly powerful indicator of generalization in deep networks?

Chaining Mutual Information and Tightening Generalization Bounds

Extending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers

One Size Does Not Fit All: Quantifying and Exposing the Accuracy-Latency Trade-off in Machine Learning Cloud Service APIs via Tolerance Tiers

Explaining Deep Learning Models with Constrained Adversarial Examples

DLIME: A Deterministic Local Interpretable Model-Agnostic Explanations Approach for Computer-Aided Diagnosis Systems

Ego-CNN: Distributed, Egocentric Representations of Graphs for Detecting Critical Structures

Semi-Supervised Learning for Cancer Detection of Lymph Node Metastases

Generating Counterfactual and Contrastive Explanations using SHAP

Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Values Approximation

Lift Up and Act! Classifier Performance in Resource-Constrained Applications

Automatic Relevance Determination Bayesian Neural Networks for Credit Card Default Modelling

What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment

Comparing Machine Learning Approaches for Table Recognition in Historical Register Books

Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks

Cognitive Knowledge Graph Reasoning for One-shot Relational Learning

Utilizing Edge Features in Graph Neural Networks via Variational Information Maximization

Evaluation of Dataflow through layers of Deep Neural Networks in Classification and Regression Problems

Theoretical evidence for adversarial robustness through randomization

Principled Training of Neural Networks with Direct Feedback Alignment

On the Insufficiency of the Large Margins Theory in Explaining the Performance of Ensemble Methods

Unit Impulse Response as an Explainer of Redundancy in a Deep Convolutional Neural Network

Generation of Multimodal Justification Using Visual Word Constraint Model for Explainable Computer-Aided Diagnosis

Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models

On the Current State of Research in Explaining Ensemble Performance Using Margins

Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise

Teaching AI to Explain its Decisions Using Embeddings and Multi-Task Learning

Multi-modal Probabilistic Prediction of Interactive Behavior via an Interpretable Model

Unsupervised and Supervised Principal Component Analysis: Tutorial

Regularizing Black-box Models for Improved Interpretability (HILL 2019 Version)

An attention-based multi-resolution model for prostate whole slide imageclassification and localization

Not All Features Are Equal: Feature Leveling Deep Neural Networks for Better Interpretation

Induction of Non-Monotonic Rules From Statistical Learning Models Using High-Utility Itemset Mining

Discovering Conditionally Salient Features with Statistical Guarantees

The Theory Behind Overfitting, Cross Validation, Regularization, Bagging, and Boosting: Tutorial

SGD on Neural Networks Learns Functions of Increasing Complexity

Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds

A Rate-Distortion Framework for Explaining Neural Network Decisions

PDH : Probabilistic deep hashing based on MAP estimation of Hamming distance

Demand forecasting techniques for build-to-order lean manufacturing supply chains

BDgraph: An R Package for Bayesian Structure Learning in Graphical Models

Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels

Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization

Show, Control and Tell: A Framework for Generating Controllable and Grounded Captions

Advancements in Image Classification using Convolutional Neural Network

Extracting human emotions at different places based on facial expressions and spatial clustering analysis

Learning, Planning, and Control in a Monolithic Neural Event Inference Architecture

Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping

Towards computer vision powered color-nutrient assessment of pureed food

Interpretation of Feature Space using Multi-Channel Attentional Sub-Networks

Automatic extrinsic calibration between a camera and a 3D Lidar using 3D point and plane correspondences

Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory

Concise Fuzzy System Modeling Integrating Soft Subspace Clustering and Sparse Learning

ExplaiNE: An Approach for Explaining Network Embedding-based Link Predictions

Beyond Explainability: Leveraging Interpretability for Improved Adversarial Learning

Deep learning generalizes because the parameter-function map is biased towards simple functions

Understanding Neural Networks via Feature Visualization: A survey

Deep learning approach based on dimensionality reduction for designing electromagnetic nanostructures

Learning Interpretable Disentangled Representations using Adversarial VAEs

Reducing Adversarial Example Transferability Using Gradient Regularization

CodeSLAM - Learning a Compact, Optimisable Representation for Dense Visual SLAM

Universal Lipschitz Approximation in Bounded Depth Neural Networks

Comments on "Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy?"

Joint Learning of Discriminative Low-dimensional Image Representations Based on Dictionary Learning and Two-layer Orthogonal Projections

SRM : A Style-based Recalibration Module for Convolutional Neural Networks

A unified spectra analysis workflow for the assessment of microbial contamination of ready to eat green salads: Comparative study and application of non-invasive sensors

Learning Embodied Semantics via Music and Dance Semiotic Correlations

f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning

Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records

Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet

A New Perspective on Machine Learning: How to do Perfect Supervised Learning

OCAPIS: R package for Ordinal Classification And Preprocessing In Scala

GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection

Attribution-driven Causal Analysis for Detection of Adversarial Examples

Efficient Interpretation of Deep Learning Models Using Graph Structure and Cooperative Game Theory: Application to ASD Biomarker Discovery

Interpreting recurrent neural networks behaviour via excitable network attractors

Visual Explanation by Interpretation: Improving Visual Feedback Capabilities of Deep Neural Networks

Why Learning of Large-Scale Neural Networks Behaves Like Convex Optimization

Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference

Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors

TrIK-SVM : an alternative decomposition for kernel methods in Krein spaces

Explaining the Unique Nature of Individual Gait Patterns with Deep Learning

Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks

Integrated analysis of the urban water-electricity demand nexus in the Midwestern United States

CFM-BD: a distributed rule induction algorithm for building Compact Fuzzy Models in Big Data classification problems

Lung Cancer Detection using Co-learning from Chest CT Images and Clinical Demographics

A Nonparametric Multi-view Model for Estimating Cell Type-Specific Gene Regulatory Networks

Going Deep in Medical Image Analysis: Concepts, Methods, Challenges and Future Directions

Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent

Global Explanations of Neural Networks: Mapping the Landscape of Predictions

Stagewise Training Accelerates Convergence of Testing Error Over SGD

Toward Sensor-based Sleep Monitoring with Electrodermal Activity Measures

Generalising Deep Learning MRI Reconstruction across Different Domains

A Simple Explanation for the Existence of Adversarial Examples with Small Hamming Distance

Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem

An Investigation into Neural Net Optimization via Hessian Eigenvalue Density

Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians

Active Anomaly Detection via Ensembles: Insights, Algorithms, and Interpretability

Unsupervised Learning of Neural Networks to Explain Neural Networks (extended abstract)

A Universal Logic Operator for Interpretable Deep Convolution Networks

Understanding the Importance of Single Directions via Representative Substitution

Inducing Sparse Coding and And-Or Grammar from Generator Network

Segmentation Analysis in Human Centric Cyber-Physical Systems using Graphical Lasso

Generalization in Deep Networks: The Role of Distance from Initialization

Predicting University Students' Academic Success and Major using Random Forests

Revealing interpretable object representations from human behavior

Explaining AlphaGo: Interpreting Contextual Effects in Neural Networks

Demystifying Multi-Faceted Video Summarization: Tradeoff Between Diversity,Representation, Coverage and Importance

Nearly-tight bounds on linear regions of piecewise linear neural networks

Interactive Naming for Explaining Deep Neural Networks: A Formative Study

A cortical-inspired model for orientation-dependent contrast perception: a link with Wilson-Cowan equations

Mining Interpretable AOG Representations from Convolutional Networks via Active Question Answering

Artificial Intelligence Assisted Infrastructure Assessment Using Mixed Reality Systems

Automatically Explaining Machine Learning Prediction Results: A Demonstration on Type 2 Diabetes Risk Prediction

Superresolution method for data deconvolution by superposition of point sources

Towards Robust Interpretability with Self-Explaining Neural Networks

Learning Functional Causal Models with Generative Neural Networks

Learning Global Additive Explanations for Neural Nets Using Model Distillation

Knowledge-driven generative subspaces for modeling multi-view dependencies in medical data

Towards Explainable Deep Learning for Credit Lending: A Case Study

An Interpretable Model with Globally Consistent Explanations for Credit Risk

Learning Finite State Representations of Recurrent Policy Networks

Understanding training and generalization in deep learning by Fourier analysis

In Defense of the Classification Loss for Person Re-Identification

An Adversarial Approach for Explainable AI in Intrusion Detection Systems

Effective Ways to Build and Evaluate Individual Survival Distributions

Accurate, Data-Efficient Learning from Noisy, Choice-Based Labels for Inherent Risk Scoring

HELOC Applicant Risk Performance Evaluation by Topological Hierarchical Decomposition

Explaining Latent Factor Models for Recommendation with Influence Functions

On the Persistence of Clustering Solutions and True Number of Clusters in a Dataset

AdapterNet - learning input transformation for domain adaptation

Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks

Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME

Explaining Deep Learning Models - A Bayesian Non-parametric Approach

Comparison of Discrete Choice Models and Artificial Neural Networks in Presence of Missing Variables

Detailed Region-Adaptive Normalization for Heavy Makeup Transfer

Exact Statistical Inference for the Wasserstein Distance by Selective Inference

Hybrid Dynamic Contrast and Probability Distillation for Unsupervised Person Re-Id

Temporal Clustering with External Memory Network for Disease Progression Modeling

Improved Xception with Dual Attention Mechanism and Feature Fusion for Face Forgery Detection

Attention-Guided Black-box Adversarial Attacks with Large-Scale Multiobjective Evolutionary Optimization

Near-Linear Time Algorithm with Near-Logarithmic Regret Per Switch for Mixable/Exp-Concave Losses

Machine learning methods for prediction of cancer driver genes: a survey paper

Once Quantization-Aware Training: High Performance Extremely Low-bit Architecture Search

Attention-augmented Spatio-Temporal Segmentation for Land Cover Mapping

DynG2G: An Efficient Stochastic Graph Embedding Method for Temporal Graphs

Automated Estimation of Construction Equipment Emission using Inertial Sensors and Machine Learning Models

TSM: Temporal Shift Module for Efficient and Scalable Video Understanding on Edge Device

VQA-MHUG: A Gaze Dataset to Study Multimodal Neural Attention in Visual Question Answering

Text-based Person Search in Full Images via Semantic-Driven Proposal Generation

Stabilizing Elastic Weight Consolidation method in practical ML tasks and using weight importances for neural network pruning

ReINTEL Challenge 2020: A Comparative Study of Hybrid Deep Neural Network for Reliable Intelligence Identification on Vietnamese SNSs

One-shot Key Information Extraction from Document with Deep Partial Graph Matching

Multi-Source Video Domain Adaptation with Temporal Attentive Moment Alignment

A Compositional Feature Embedding and Similarity Metric for Ultra-Fine-Grained Visual Categorization

Hard-sample Guided Hybrid Contrast Learning for Unsupervised Person Re-Identification

Multi-Modal Multi-Instance Learning for Retinal Disease Recognition

SPNet: Multi-Shell Kernel Convolution for Point Cloud Semantic Segmentation

Pairwise Emotional Relationship Recognition in Drama Videos: Dataset and Benchmark

Partially Encrypted Machine Learning using Functional Encryption

Adaptive Logit Adjustment Loss for Long-Tailed Visual Recognition

Predicting Stress in Remote Learning via Advanced Deep Learning Technologies

A Benchmark Comparison of Visual Place Recognition Techniques for Resource-Constrained Embedded Platforms

The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence

Label Cleaning Multiple Instance Learning: Refining Coarse Annotations on Single Whole-Slide Images

Early Lane Change Prediction for Automated Driving Systems Using Multi-Task Attention-based Convolutional Neural Networks

PSGCNet: A Pyramidal Scale and Global Context Guided Network for Dense Object Counting in Remote Sensing Images

Less is More: Learning from Synthetic Data with Fine-grained Attributes for Person Re-Identification

Blindness of score-based methods to isolated components and mixing proportions

Multiblock-Networks: A Neural Network Analog to Component Based Methods for Multi-Source Data

MESSFN : a Multi-level and Enhanced Spectral-Spatial Fusion Network for Pan-sharpening

Cross-Modal Food Retrieval: Learning a Joint Embedding of Food Images and Recipes with Semantic Consistency and Attention Mechanism

YinYang-Net: Complementing Face and Body Information for Wild Gender Recognition

Splitfed learning without client-side synchronization: Analyzing client-side split network portion size to overall performance

RSI-Net: Two-Stream Deep Neural Network Integrating GCN and Atrous CNN for Semantic Segmentation of High-resolution Remote Sensing Images

Efficient Urban-scale Point Clouds Segmentation with BEV Projection

Adversarial examples attack based on random warm restart mechanism and improved Nesterov momentum

Edge Prior Augmented Networks for Motion Deblurring on Naturally Blurry Images

Coordinate Descent for MCP/SCAD Penalized Least Squares Converges Linearly

P-WAE: Generalized Patch-Wasserstein Autoencoder for Anomaly Screening

Cross Modification Attention Based Deliberation Model for Image Captioning

NetTraj: A Network-based Vehicle Trajectory Prediction Model with Directional Representation and Spatiotemporal Attention Mechanisms

Bio-Inspired Audio-Visual Cues Integration for Visual Attention Prediction

An Interpretable Framework for Drug-Target Interaction with Gated Cross Attention

OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication

Generating Dataset For Large-scale 3D Facial Emotion Recognition

Learnable Multi-level Frequency Decomposition and Hierarchical Attention Mechanism for Generalized Face Presentation Attack Detection

Less is More: Pre-train a Strong Text Encoder for Dense Retrieval Using a Weak Decoder

The Pursuit of Knowledge: Discovering and Localizing Novel Categories using Dual Memory

Learning to Aggregate and Refine Noisy Labels for Visual Sentiment Analysis

Distract Your Attention: Multi-head Cross Attention Network for Facial Expression Recognition

DAPnet: A Double Self-attention Convolutional Network for Point Cloud Semantic Labeling

CalCROP21: A Georeferenced multi-spectral dataset of Satellite Imagery and Crop Labels

Luminance Attentive Networks for HDR Image and Panorama Reconstruction

Clustering acoustic emission data streams with sequentially appearing clusters using mixture models

Exploring the Long Short-Term Dependencies to Infer Shot Influence in Badminton Matches

A Pilot Study on Visually Stimulated Cognitive Tasks for EEG-Based Dementia Recognition

Progressively Guide to Attend: An Iterative Alignment Framework for Temporal Sentence Grounding

Adaptive Proposal Generation Network for Temporal Sentence Localization in Videos

Machine Learning for Online Algorithm Selection under Censored Feedback

On the Sins of Image Synthesis Loss for Self-supervised Depth Estimation

Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity

Evaluating the Progress of Deep Learning for Visual Relational Concepts

Unified Framework for Feature Extraction based on Contrastive Learning

ADNet: Leveraging Error-Bias Towards Normal Direction in Face Alignment

Spatial and Semantic Consistency Regularizations for Pedestrian Attribute Recognition

On the Impact of Spurious Correlation for Out-of-distribution Detection

Unsupervised Domain Adaptive Learning via Synthetic Data for Person Re-identification

LEA-Net: Layer-wise External Attention Network for Efficient Color Anomaly Detection

DynSTGAT: Dynamic Spatial-Temporal Graph Attention Network for Traffic Signal Control

Channelized Axial Attention for Semantic Segmentation -- Considering Channel Relation within Spatial Attention for Semantic Segmentation

More Than Just Attention: Improving Cross-Modal Attentions with Contrastive Constraints for Image-Text Matching

Space Meets Time: Local Spacetime Neural Network For Traffic Flow Forecasting

Pyramid Hybrid Pooling Quantization for Efficient Fine-Grained Image Retrieval

Semantic-guided Automatic Natural Image Matting with Trimap Generation Network and Light-weight Non-local Attention

Enhancing Unsupervised Anomaly Detection with Score-Guided Network

Deciphering Environmental Air Pollution with Large Scale City Data

FedCon: A Contrastive Framework for Federated Semi-Supervised Learning

Provably efficient RL with Rich Observations via Latent State Decoding

Modeling Massive Spatial Datasets Using a Conjugate Bayesian Linear Regression Framework

LightSAL: Lightweight Sign Agnostic Learning for Implicit Surface Representation

PIMNet: A Parallel, Iterative and Mimicking Network for Scene Text Recognition

End-to-End Information Extraction by Character-Level Embedding and Multi-Stage Attentional U-Net

Generation, augmentation, and alignment: A pseudo-source domain based method for source-free domain adaptation

GDP: Stabilized Neural Network Pruning via Gates with Differentiable Polarization

Which and Where to Focus: A Simple yet Accurate Framework for Arbitrary-Shaped Nearby Text Detection in Scene Images

Improving Adversarial Robustness via Attention and Adversarial Logit Pairing

Model Selection's Disparate Impact in Real-World Deep Learning Applications

TrouSPI-Net: Spatio-temporal attention on parallel atrous convolutions and U-GRUs for skeletal pedestrian crossing prediction

Grassmannian Graph-attentional Landmark Selection for Domain Adaptation

Sensor-Augmented Egocentric-Video Captioning with Dynamic Modal Attention

Spatiotemporal Inconsistency Learning for DeepFake Video Detection

Learning to Combine the Modalities of Language and Video for Temporal Moment Localization

Agent-Environment Network for Temporal Action Proposal Generation

Iterative Pseudo-Labeling with Deep Feature Annotation and Confidence-Based Sampling

Individual Mobility Prediction via Attentive Marked Temporal Point Processes

Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time

Encoder-decoder with Multi-level Attention for 3D Human Shape and Pose Estimation

Robust Attentive Deep Neural Network for Exposing GAN-generated Faces

Deep Person Generation: A Survey from the Perspective of Face, Pose and Cloth Synthesis

Toward Multidiversified Ensemble Clustering of High-Dimensional Data: From Subspaces to Metrics and Beyond

RiWNet: A moving object instance segmentation Network being Robust in adverse Weather conditions

PR-Net: Preference Reasoning for Personalized Video Highlight Detection

Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos

Building Interpretable Models for Business Process Prediction using Shared and Specialised Attention Mechanisms

Sampling methods for efficient training of graph convolutional networks: A survey

Impact of Attention on Adversarial Robustness of Image Classification Models

Advances in adversarial attacks and defenses in computer vision: A survey

AnANet: Modeling Association and Alignment for Cross-modal Correlation Classification

CI-Net: Contextual Information for Joint Semantic Segmentation and Depth Estimation

Joint Graph Learning and Matching for Semantic Feature Correspondence

Look Who's Talking: Interpretable Machine Learning for Assessing Italian SMEs Credit Default

Nonasymptotic one-and two-sample tests in high dimension with unknown covariance structure

Unsupervised Person Re-Identification: A Systematic Survey of Challenges and Solutions

S4-Crowd: Semi-Supervised Learning with Self-Supervised Regularisation for Crowd Counting

Attention-based Multi-Reference Learning for Image Super-Resolution

SimulLR: Simultaneous Lip Reading Transducer with Attention-Guided Adaptive Memory

SMAC-Seg: LiDAR Panoptic Segmentation via Sparse Multi-directional Attention Clustering

Seminar Learning for Click-Level Weakly Supervised Semantic Segmentation

Progressive Co-Attention Network for Fine-grained Visual Classification

Searching for Two-Stream Models in Multivariate Space for Video Recognition

Attentive Rotation Invariant Convolution for Point Cloud-based Large Scale Place Recognition

DeepMultiCap: Performance Capture of Multiple Characters Using Sparse Multiview Cameras

Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces

Multi-Horizon Forecasting for Limit Order Books: Novel Deep Learning Approaches and Hardware Acceleration using Intelligent Processing Units

TRiPOD: Human Trajectory and Pose Dynamics Forecasting in the Wild

Man versus Machine: AutoML and Human Experts' Role in Phishing Detection

LassoLayer: Nonlinear Feature Selection by Switching One-to-one Links

Provable Tensor-Train Format Tensor Completion by Riemannian Optimization

Self-supervised Multi-scale Consistency for Weakly Supervised Segmentation Learning

An Optimized Dataflow for Mitigating Attention Performance Bottlenecks

MemX: An Attention-Aware Smart Eyewear System for Personalized Moment Auto-capture

Multiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Prediction

Monocular Depth Estimation Primed by Salient Point Detection and Normalized Hessian Loss

Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping

A Comprehensive Survey on Graph Anomaly Detection with Deep Learning

Are socially-aware trajectory prediction models really socially-aware?

Spatio-Temporal Self-Attention Network for Video Saliency Prediction

The Effect of Noise Level on Causal Identification with Additive Noise Models

SIDE: Center-based Stereo 3D Detector with Structure-aware Instance Depth Estimation

ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentation

Using Neighborhood Context to Improve Information Extraction from Visual Documents Captured on Mobile Phones

D2-Net: Weakly-Supervised Action Localization via Discriminative Embeddings and Denoised Activations

Multivariate and Propagation Graph Attention Network for Spatial-Temporal Prediction with Outdoor Cellular Traffic

Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection

Identifying Illicit Drug Dealers on Instagram with Large-scale Multimodal Data Fusion

Interpreting Super-Resolution Networks with Local Attribution Maps

Towards Coherent Visual Storytelling with Ordered Image Attention

DCAP: Deep Cross Attentional Product Network for User Response Prediction

Memorize, Factorize, or be Naïve: Learning Optimal Feature Interaction Methods for CTR Prediction

BoundaryNet: An Attentive Deep Network with Fast Marching Distance Maps for Semi-automatic Layout Annotation

Integer-arithmetic-only Certified Robustness for Quantized Neural Networks

Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions

Mobility-Aware Cluster Federated Learning in Hierarchical Wireless Networks

Video-based Person Re-identification with Spatial and Temporal Memory Networks

Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification

Channel-Temporal Attention for First-Person Video Domain Adaptation

Stroke-Based Scene Text Erasing Using Synthetic Data for Training

Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain

VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection

AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis

Residual Attention: A Simple but Effective Method for Multi-Label Recognition

Semantic Reinforced Attention Learning for Visual Place Recognition

STADB: A Self-Thresholding Attention Guided ADB Network for Person Re-identification

Listening to the city, attentively: A Spatio-Temporal Attention Boosted Autoencoder for the Short-Term Flow Prediction Problem

Pitfalls in Machine Learning Research: Reexamining the Development Cycle

DeepExpress: Heterogeneous and Coupled Sequence Modeling for Express Delivery Prediction

Towards Deep and Efficient: A Deep Siamese Self-Attention Fully Efficient Convolutional Network for Change Detection in VHR Images

Active Observer Visual Problem-Solving Methods are Dynamically Hypothesized, Deployed and Tested

Deep Graph Memory Networks for Forgetting-Robust Knowledge Tracing

Variational Attention: Propagating Domain-Specific Knowledge for Multi-Domain Learning in Crowd Counting

Towards Secure and Practical Machine Learning via Secret Sharing and Random Permutation

Cross-Sentence Temporal and Semantic Relations in Video Activity Localisation

TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition

Graph-based Neural Architecture Search with Operation Embeddings

Continuous Emotion Recognition with Audio-visual Leader-follower Attentive Fusion

A Dense Siamese U-Net trained with Edge Enhanced 3D IOU Loss for Image Co-segmentation

Group-wise Inhibition based Feature Regularization for Robust Classification

Dense Interaction Learning for Video-based Person Re-identification

CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objects

QuantumFed: A Federated Learning Framework for Collaborative Quantum Training

SaccadeCam: Adaptive Visual Attention for Monocular Depth Sensing

VLG-Net: Video-Language Graph Matching Network for Video Grounding

AIREX: Neural Network-based Approach for Air Quality Inference in Unmonitored Cities

Towards Real-World Prohibited Item Detection: A Large-Scale X-ray Benchmark

Video Person Re-identification using Attribute-enhanced Features

Towards Face Encryption by Generating Adversarial Identity Masks

CrossNorm and SelfNorm for Generalization under Distribution Shifts

Incorporating Reachability Knowledge into a Multi-Spatial Graph Convolution Based Seq2Seq Model for Traffic Forecasting

Instance-Sensitive Algorithms for Pure Exploration in Multinomial Logit Bandit

Towards Understanding Theoretical Advantages of Complex-Reaction Networks

Few-Shot Fine-Grained Action Recognition via Bidirectional Attention and Contrastive Meta-Learning

A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation

Interpretable Visual Understanding with Cognitive Attention Network

Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization

ACNet: Mask-Aware Attention with Dynamic Context Enhancement for Robust Acne Detection

WideCaps: A Wide Attention based Capsule Network for Image Classification

Optimal and Efficient Algorithms for General Mixable Losses against Switching Oracles

DensePASS: Dense Panoramic Semantic Segmentation via Unsupervised Domain Adaptation with Attention-Augmented Context Exchange

Unsupervised Monocular Depth Learning with Integrated Intrinsics and Spatio-Temporal Constraints

Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark

A Generative Adversarial Framework for Optimizing Image Matting and Harmonization Simultaneously

Progressive Representative Labeling for Deep Semi-Supervised Learning

AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric Learning

NI-UDA: Graph Adversarial Domain Adaptation from Non-shared-and-Imbalanced Big Data to Small Imbalanced Applications

AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer

A Queueing-Theoretic Framework for Vehicle Dispatching in Dynamic Car-Hailing [technical report]

GRF: Learning a General Radiance Field for 3D Representation and Rendering

MetaPose: Fast 3D Pose from Multiple Views without 3D Supervision

Embedded Knowledge Distillation in Depth-Level Dynamic Neural Network

FoodLogoDet-1500: A Dataset for Large-Scale Food Logo Detection via Multi-Scale Feature Decoupling Network

TBNet:Two-Stream Boundary-aware Network for Generic Image Manipulation Localization

GPCA: A Probabilistic Framework for Gaussian Process Embedded Channel Attention

The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification

Pose is all you need: The pose only group activity recognition system (POGARS)

Spatio-Temporal Attention Mechanism and Knowledge Distillation for Lip Reading

Uniformity in Heterogeneity:Diving Deep into Count Interval Partition for Crowd Counting

Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning

Attention-based fusion of semantic boundary and non-boundary information to improve semantic segmentation

Self-supervised optimization of random material microstructures in the small-data regime

LSENet: Location and Seasonality Enhanced Network for Multi-Class Ocean Front Detection

Structured Multi-modal Feature Embedding and Alignment for Image-Sentence Retrieval

Attentive Cross-modal Connections for Deep Multimodal Wearable-based Emotion Recognition

Multi-Branch with Attention Network for Hand-Based Person Recognition

Self-Supervised Learning of Depth and Ego-Motion from Video by Alternative Training and Geometric Constraints from 3D to 2D

Weakly Supervised Foreground Learning for Weakly Supervised Localization and Detection

Non-local Graph Convolutional Network for joint Activity Recognition and Motion Prediction

Adaptive Affinity Loss and Erroneous Pseudo-Label Refinement for Weakly Supervised Semantic Segmentation

Improving Weakly-supervised Object Localization via Causal Intervention

Knowing When to Quit: Selective Cascaded Regression with Patch Attention for Real-Time Face Alignment

RAIN: Reinforced Hybrid Attention Inference Network for Motion Forecasting

PAN++: Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Shaped Text

RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth

Object-to-Scene: Learning to Transfer Object Knowledge to Indoor Scene Recognition

Learning Few-shot Open-set Classifiers using Exemplar Reconstruction

Take an Emotion Walk: Perceiving Emotions from Gaits Using Hierarchical Attention Pooling and Affective Mapping

Reducing Effects of Swath Gaps on Unsupervised Machine Learning Models for NASA MODIS Instruments

SiamAPN++: Siamese Attentional Aggregation Network for Real-Time UAV Tracking

Manipulating Identical Filter Redundancy for Efficient Pruning on Deep and Complicated CNN

Few-Shot and Continual Learning with Attentive Independent Mechanisms

Improving Robustness and Accuracy via Relative Information Encoding in 3D Human Pose Estimation

Anchor-Based Spatio-Temporal Attention 3D Convolutional Networks for Dynamic 3D Point Cloud Sequences

U-GAT: Multimodal Graph Attention Network for COVID-19 Outcome Prediction

Playing to distraction: towards a robust training of CNN classifiers through visual explanation techniques

VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation

Efficient Human Pose Estimation by Maximizing Fusion and High-Level Spatial Attention

Task-Specific Normalization for Continual Learning of Blind Image Quality Models

Effective Eigendecomposition based Graph Adaptation for Heterophilic Networks

Stronger Privacy for Federated Collaborative Filtering with Implicit Feedback

Rethinking ResNets: Improved Stacking Strategies With High Order Schemes

Content-aware Directed Propagation Network with Pixel Adaptive Kernel Attention

Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network

DV-ConvNet: Fully Convolutional Deep Learning on Point Clouds with Dynamic Voxelization and 3D Group Convolution

Cross-modal Consensus Network for Weakly Supervised Temporal Action Localization

Joint Visual Semantic Reasoning: Multi-Stage Decoder for Text Recognition

BridgeNet: A Joint Learning Network of Depth Map Super-Resolution and Monocular Depth Estimation

Super-Human Performance in Online Low-latency Recognition of Conversational Speech

Short-Term Electricity Price Forecasting based on Graph Convolution Network and Attention Mechanism

An Efficient Insect Pest Classification Using Multiple Convolutional Neural Network Based Models

Boosting Entity-aware Image Captioning with Multi-modal Knowledge Graph

Domain-Aware SE Network for Sketch-based Image Retrieval with Multiplicative Euclidean Margin Softmax

Aggregate or Not? Exploring Where to Privatize in DNN Based Federated Learning Under Different Non-IID Scenes

Semantic Attention and Scale Complementary Network for Instance Segmentation in Remote Sensing Images

Temporal-wise Attention Spiking Neural Networks for Event Streams Classification

G2DA: Geometry-Guided Dual-Alignment Learning for RGB-Infrared Person Re-Identification

Deep Learning Based Cardiac MRI Segmentation: Do We Need Experts?

ReSSL: Relational Self-Supervised Learning with Weak Augmentation

Taxonomizing local versus global structure in neural network loss landscapes

Classifying bacteria clones using attention-based deep multiple instance learning interpreted by persistence homology

Empirical Risk Minimization in the Interpolating Regime with Application to Neural Network Learning

DeepTitle -- Leveraging BERT to generate Search Engine Optimized Headlines

MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking

Mini-data-driven Deep Arbitrary Polynomial Chaos Expansion for Uncertainty Quantification

Tri-Branch Convolutional Neural Networks for Top-$k$ Focused Academic Performance Prediction

UACANet: Uncertainty Augmented Context Attention for Polyp Segmentation

Ensemble-based Uncertainty Quantification: Bayesian versus Credal Inference

DanHAR: Dual Attention Network For Multimodal Human Activity Recognition Using Wearable Sensors

Structure-Aware Long Short-Term Memory Network for 3D Cephalometric Landmark Detection

Defending against Reconstruction Attack in Vertical Federated Learning

WGCN: Graph Convolutional Networks with Weighted Structural Features

Saliency for free: Saliency prediction as a side-effect of object recognition

SOGAN: 3D-Aware Shadow and Occlusion Robust GAN for Makeup Transfer

Consistent Two-Flow Network for Tele-Registration of Point Clouds

Locality-aware Channel-wise Dropout for Occluded Face Recognition

ABCNet v2: Adaptive Bezier-Curve Network for Real-time End-to-end Text Spotting

Video Crowd Localization with Multi-focus Gaussian Neighbor Attention and a Large-Scale Benchmark

InsPose: Instance-Aware Networks for Single-Stage Multi-Person Pose Estimation

A Benchmark for Gait Recognition under Occlusion Collected by Multi-Kinect SDAS

A2-FPN for Semantic Segmentation of Fine-Resolution Remotely Sensed Images

Semi-Supervised Learning of Classifiers from a Statistical Perspective: A Brief Review

UNIK: A Unified Framework for Real-world Skeleton-based Action Recognition

Spatio-Temporal Event Segmentation and Localization for Wildlife Extended Videos

A Miniature Biological Eagle-Eye Vision System for Small Target Detection

Fair Balance: Mitigating Machine Learning Bias Against Multiple Protected Attributes With Data Balancing

Looking Twice for Partial Clues: Weakly-supervised Part-Mentored Attention Network for Vehicle Re-Identification

Review of Video Predictive Understanding: Early Action Recognition and Future Action Prediction

Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma Classification

MSCFNet: A Lightweight Network With Multi-Scale Context Fusion for Real-Time Semantic Segmentation

Passive attention in artificial neural networks predicts human visual selectivity

FetalNet: Multi-task deep learning framework for fetal ultrasound biometric measurements

Uncertainty-Guided Mixup for Semi-Supervised Domain Adaptation without Source Data

MSFNet:Multi-scale features network for monocular depth estimation

Privacy Preserving Gaze Estimation using Synthetic Images via a Randomized Encoding Based Framework

Emotion Recognition for Healthcare Surveillance Systems Using Neural Networks: A Survey

A Comprehensive Review of Deep Learning-based Single Image Super-resolution

Towards Representation Identical Privacy-Preserving Graph Neural Network via Split Learning

Region attention and graph embedding network for occlusion objective class-based micro-expression recognition

Interflow: Aggregating Multi-layer Feature Mappings with Attention Mechanism

LATTE: LSTM Self-Attention based Anomaly Detection in Embedded Automotive Platforms

Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning

Cross-modal Attention for MRI and Ultrasound Volume Registration

SE-PSNet: Silhouette-based Enhancement Feature for Panoptic Segmentation Network

Locality Relationship Constrained Multi-view Clustering Framework

Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Network

A Weakly-Supervised Depth Estimation Network Using Attention Mechanism

Using Radiomics as Prior Knowledge for Thorax Disease Classification and Localization in Chest X-rays

Efficient Real-Time Image Recognition Using Collaborative Swarm of UAVs and Convolutional Networks

ASC-Net : Adversarial-based Selective Network for Unsupervised Anomaly Segmentation

Adversarial Domain Adaptation with Self-Training for EEG-based Sleep Stage Classification

Action Unit Detection with Joint Adaptive Attention and Graph Relation

ABD-Net: Attention Based Decomposition Network for 3D Point Cloud Decomposition

Case-based similar image retrieval for weakly annotated large histopathological images of malignant lymphoma using deep metric learning

Polarized Self-Attention: Towards High-quality Pixel-wise Regression

Use of Affective Visual Information for Summarization of Human-Centric Videos

OXnet: Omni-supervised Thoracic Disease Detection from Chest X-rays

AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction

Mitigating Memorization in Sample Selection for Learning with Noisy Labels

BANet: Blur-aware Attention Networks for Dynamic Scene Deblurring

Distribution-free uncertainty quantification for classification under label shift

Enhancing Deep Neural Network Saliency Visualizations with Gradual Extrapolation

Face Hallucination via Split-Attention in Split-Attention Network

GA-NET: Global Attention Network for Point Cloud Semantic Segmentation

GCN-Based Linkage Prediction for Face Clustering on Imbalanced Datasets: An Empirical Study

Single Model for Influenza Forecasting of Multiple Countries by Multi-task Learning

Attention over learned object embeddings enables complex visual reasoning

Attention-based Adversarial Appearance Learning of Augmented Pedestrians

Memory-aware curriculum federated learning for breast cancer classification

DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations

FloorLevel-Net: Recognizing Floor-Level Lines with Height-Attention-Guided Multi-task Learning

Self-Adversarial Training incorporating Forgery Attention for Image Forgery Localization

Learning an Explicit Hyperparameter Prediction Policy Conditioned on Tasks

VolNet: Estimating Human Body Part Volumes from a Single RGB Image

Tiled Squeeze-and-Excite: Channel Attention With Local Spatial Context

Evaluation of Audio-Visual Alignments in Visually Grounded Speech Models

Part2Word: Learning Joint Embedding of Point Clouds and Text by Matching Parts to Words

SSPNet: Scale Selection Pyramid Network for Tiny Person Detection from UAV Images

Joint Object Contour Points and Semantics for Instance Segmentation

Distilling Knowledge from Ensembles of Acoustic Models for Joint CTC-Attention End-to-End Speech Recognition

Species Distribution Modeling for Machine Learning Practitioners: A Review

Minimum Wasserstein Distance Estimator under Finite Location-scale Mixtures

A Novel Disaster Image Dataset and Characteristics Analysis using Attention Model

Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data

Byzantine-Robust Learning on Heterogeneous Datasets via Resampling

PoliTO-IIT Submission to the EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition

Generic Event Boundary Detection Challenge at CVPR 2021 Technical Report: Cascaded Temporal Attention Network (CASTANET)

Dual Reweighting Domain Generalization for Face Presentation Attack Detection

Domain-Adversarial Training of Self-Attention Based Networks for Land Cover Classification using Multi-temporal Sentinel-2 Satellite Imagery

Efficient Spatio-Temporal Recurrent Neural Network for Video Deblurring

Muti-view Mouse Social Behaviour Recognition with Deep Graphical Model

Machine Learning-based Lie Detector applied to a Novel Annotated Game Dataset

GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphs

IMENet: Joint 3D Semantic Scene Completion and 2D Semantic Segmentation through Iterative Mutual Enhancement

SALYPATH: A Deep-Based Architecture for visual attention prediction

Iris Presentation Attack Detection by Attention-based and Deep Pixel-wise Binary Supervision Network

Progressive Class-based Expansion Learning For Image Classification

A Circular-Structured Representation for Visual Emotion Distribution Learning

Transfer-based adaptive tree for multimodal sentiment analysis based on user latent aspects

Spectral-Spatial Graph Reasoning Network for Hyperspectral Image Classification

Graph Pattern Loss based Diversified Attention Network for Cross-Modal Retrieval

Interpreting Depression From Question-wise Long-term Video Recording of SDS Evaluation

HAN: An Efficient Hierarchical Self-Attention Network for Skeleton-Based Gesture Recognition

Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting

All You Need is a Second Look: Towards Arbitrary-Shaped Text Detection

Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning

Deep unsupervised 3D human body reconstruction from a sparse set of landmarks

ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models

Region-Aware Network: Model Human's Top-Down Visual Perception Mechanism for Crowd Counting

Modality Attention and Sampling Enables Deep Learning with Heterogeneous Marker Combinations in Fluorescence Microscopy

Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation

NetFense: Adversarial Defenses against Privacy Attacks on Neural Networks for Graph Data

Deep Conditional Gaussian Mixture Model for Constrained Clustering

RtFPS: An Interactive Map that Visualizes and Predicts Wildfires in the US

Sequential Late Fusion Technique for Multi-modal Sentiment Analysis

Deep Learning for Suicide and Depression Identification with Unsupervised Label Correction

FP-Age: Leveraging Face Parsing Attention for Facial Age Estimation in the Wild

Channel Pruning Guided by Spatial and Channel Attention for DNNs in Intelligent Edge Computing

Cross-layer Navigation Convolutional Neural Network for Fine-grained Visual Classification

An End-to-End Khmer Optical Character Recognition using Sequence-to-Sequence with Attention

iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients

Tag, Copy or Predict: A Unified Weakly-Supervised Learning Framework for Visual Information Extraction using Sequences

A Coarse-to-Fine Instance Segmentation Network with Learning Boundary Representation

A Dynamic Spatial-temporal Attention Network for Early Anticipation of Traffic Accidents

Fusion of Embeddings Networks for Robust Combination of Text Dependent and Independent Speaker Recognition

A Vertical Federated Learning Framework for Horizontally Partitioned Labels

Multi-Granularity Network with Modal Attention for Dense Affective Understanding

AttDLNet: Attention-based DL Network for 3D LiDAR Place Recognition

Scale-Consistent Fusion: from Heterogeneous Local Sampling to Global Immersive Rendering

LiRA: Learning Visual Speech Representations from Audio through Self-supervision

Soft Attention: Does it Actually Help to Learn Social Interactions in Pedestrian Trajectory Prediction?

Data Augmentation for Graph Convolutional Network on Semi-Supervised Classification

Anomaly Detection in Video Sequences: A Benchmark and Computational Model

Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks

TabularNet: A Neural Network Architecture for Understanding Semantic Structures of Tabular Data

Graph Neural Networks Inspired by Classical Iterative Algorithms

An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction

Generating Contrastive Explanations for Inductive Logic Programming Based on a Near Miss Approach

Zero-sample surface defect detection and classification based on semantic feedback neural network

S2R-DepthNet: Learning a Generalizable Depth-specific Structural Representation

Over-Fit: Noisy-Label Detection based on the Overfitted Model Property

Group-based Bi-Directional Recurrent Wavelet Neural Networks for Video Super-Resolution

Learning to Combine Per-Example Solutions for Neural Program Synthesis

Training Deep Architectures Without End-to-End Backpropagation: A Brief Survey

Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning

Representation and Correlation Enhanced Encoder-Decoder Framework for Scene Text Recognition

LaplaceNet: A Hybrid Energy-Neural Model for Deep Semi-Supervised Classification

Multi-level Attention Fusion Network for Audio-visual Event Recognition

Structure-Regularized Attention for Deformable Object Representation

Evaluating Meta-Feature Selection for the Algorithm Recommendation Problem

Pedestrian Attribute Recognition in Video Surveillance Scenarios Based on View-attribute Attention Localization

Exploiting Record Similarity for Practical Vertical Federated Learning

TrafficStream: A Streaming Traffic Flow Forecasting Framework Based on Graph Neural Networks and Continual Learning

Implicit Feature Alignment: Learn to Convert Text Recognizer to Text Spotter

Unsupervised Hyperspectral Mixed Noise Removal Via Spatial-Spectral Constrained Deep Image Prior

A New Notion of Individually Fair Clustering: $α$-Equitable $k$-Center

An Efficient Point of Gaze Estimator for Low-Resolution Imaging Systems Using Extracted Ocular Features Based Neural Architecture

Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions

Real Time Egocentric Object Segmentation: THU-READ Labeling and Benchmarking Results

Memory-based Optimization Methods for Model-Agnostic Meta-Learning

Learning to Discover Multi-Class Attentional Regions for Multi-Label Image Recognition

Tracking by Joint Local and Global Search: A Target-aware Attention based Approach

Self-Supervised Graph Learning with Hyperbolic Embedding for Temporal Health Event Prediction

Understanding top-down attention using task-oriented ablation design

Interpreting Deep Learning based Cerebral Palsy Prediction with Channel Attention

CSRNet: Cascaded Selective Resolution Network for Real-time Semantic Segmentation

A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs

Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation

Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks

Deep Learning 3D Dose Prediction for Conventional Lung IMRT Using Consistent/Unbiased Automated Plans

Self-supervised Depth Estimation Leveraging Global Perception and Geometric Smoothness Using On-board Videos

Improve the Interpretability of Attention: A Fast, Accurate, and Interpretable High-Resolution Attention Model

Channel DropBlock: An Improved Regularization Method for Fine-Grained Visual Classification

Adversarially Regularized Graph Attention Networks for Inductive Learning on Partially Labeled Graphs

Contextual Guided Segmentation Framework for Semi-supervised Video Instance Segmentation

MOC-GAN: Mixing Objects and Captions to Generate Realistic Images

Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method

Memory Wrap: a Data-Efficient and Interpretable Extension to Image Classification Models

Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning

Bonsai-Net: One-Shot Neural Architecture Search via Differentiable Pruners

Deep Learning Methods for Vessel Trajectory Prediction based on Recurrent Neural Networks

Incomplete Graph Representation and Learning via Partial Graph Neural Networks

Hybrid attention network based on progressive embedding scale-context for crowd counting

The Earth Mover's Pinball Loss: Quantiles for Histogram-Valued Regression

A Survey on Optimal Transport for Machine Learning: Theory and Applications

Global Wheat Head Dataset 2021: more diversity to improve the benchmarking of wheat head localization methods

Lymph Node Graph Neural Networks for Cancer Metastasis Prediction

Learning to Select: A Fully Attentive Approach for Novel Object Captioning

SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize

Hybrid Ensemble optimized algorithm based on Genetic Programming for imbalanced data classification

Benchmarking CNN on 3D Anatomical Brain MRI: Architectures, Data Augmentation and Deep Ensemble Learning

Consumer Image Quality Prediction using Recurrent Neural Networks for Spatial Pooling

Hyperdimensional Computing for Efficient Distributed Classification with Randomized Neural Networks

Attention Based Semantic Segmentation on UAV Dataset for Natural Disaster Damage Assessment

Fidelity Estimation Improves Noisy-Image Classification with Pretrained Networks

Full-Resolution Encoder-Decoder Networks with Multi-Scale Feature Fusion for Human Pose Estimation

DLA-Net: Learning Dual Local Attention Features for Semantic Segmentation of Large-Scale Building Facade Point Clouds

Rotation Invariant Point Cloud Classification: Where Local Geometry Meets Global Topology

Hardness Sampling for Self-Training Based Transductive Zero-Shot Learning

VA-GCN: A Vector Attention Graph Convolution Network for learning on Point Clouds

AS-Net: Fast Photoacoustic Reconstruction with Multi-feature Fusion from Sparse Data

Enhancing Trajectory Prediction using Sparse Outputs: Application to Team Sports

Spatio-Temporal Point Processes with Attention for Traffic Congestion Event Modeling

ACE-NODE: Attentive Co-Evolving Neural Ordinary Differential Equations

Learning Inductive Attention Guidance for Partially Supervised Pancreatic Ductal Adenocarcinoma Prediction

Bio-inspired visual attention for silicon retinas based on spiking neural networks applied to pattern classification

Towards a Federated Learning Framework for Heterogeneous Devices of Internet of Things

Convergence of End-to-End Training in Deep Unsupervised Contrastive Learning

MarkerPose: Robust Real-time Planar Target Tracking for Accurate Stereo Pose Estimation

Modeling Multi-Label Action Dependencies for Temporal Action Localization

A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image Classification

SCOUT: Socially-COnsistent and UndersTandable Graph Attention Network for Trajectory Prediction of Vehicles and VRUs

Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overview

A model for traffic incident prediction using emergency braking data

Spatial-Temporal Dynamic Graph Attention Networks for Ride-hailing Demand Prediction

A Critical Look at the Consistency of Causal Estimation With Deep Latent Variable Models

Improving Facial Attribute Recognition by Group and Graph Learning

An Attention-Fused Network for Semantic Segmentation of Very-High-Resolution Remote Sensing Imagery

DR-TANet: Dynamic Receptive Temporal Attention Network for Street Scene Change Detection

Semi-supervised Anatomical Landmark Detection via Shape-regulated Self-training

Open-world Machine Learning: Applications, Challenges, and Opportunities

Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future

Robust learning from corrupted EEG with dynamic spatial filtering

Spatio-Contextual Deep Network Based Multimodal Pedestrian Detection For Autonomous Driving

Social-IWSTCNN: A Social Interaction-Weighted Spatio-Temporal Convolutional Neural Network for Pedestrian Trajectory Prediction in Urban Traffic Scenarios

Weakly Supervised Instance Attention for Multisource Fine-Grained Object Recognition with an Application to Tree Species Classification

Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits

Multi-Level Attentive Convoluntional Neural Network for Crowd Counting

SSPC-Net: Semi-supervised Semantic 3D Point Cloud Segmentation Network

Progressively Normalized Self-Attention Network for Video Polyp Segmentation

Heuristic Weakly Supervised 3D Human Pose Estimation in Novel Contexts without Any 3D Pose Ground Truth

SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition

DepressionNet: A Novel Summarization Boosted Deep Framework for Depression Detection on Social Media

ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging

Puck localization and multi-task event recognition in broadcast hockey videos

ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search

A Novel 3D-UNet Deep Learning Framework Based on High-Dimensional Bilateral Grid for Edge Consistent Single Image Depth Estimation

Attention-guided Chained Context Aggregation for Semantic Segmentation

Where Do Deep Fakes Look? Synthetic Face Detection via Gaze Tracking

A Spatio-temporal Attention-based Model for Infant Movement Assessment from Videos

Multi-Person Extreme Motion Prediction with Cross-Interaction Attention

PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask and Group-Level Consistency

GT-STORM: Taming Sample, Communication, and Memory Complexities in Decentralized Non-Convex Learning

Non-contact Pain Recognition from Video Sequences with Remote Physiological Measurements Prediction

Multi-Aspect Temporal Network Embedding: A Mixture of Hawkes Process View

Self-Point-Flow: Self-Supervised Scene Flow Estimation from Point Clouds with Optimal Transport and Random Walk

VPN++: Rethinking Video-Pose embeddings for understanding Activities of Daily Living

CNN-based Approaches For Cross-Subject Classification in Motor Imagery: From The State-of-The-Art to DynamicNet

Physics-informed attention-based neural network for solving non-linear partial differential equations

EA-Net: Edge-Aware Network for Flow-based Video Frame Interpolation

Collaborative Video Object Segmentation by Multi-Scale Foreground-Background Integration

BDANet: Multiscale Convolutional Neural Network with Cross-directional Attention for Building Damage Assessment from Satellite Images

One for All: An End-to-End Compact Solution for Hand Gesture Recognition

Evaluating the Robustness of Self-Supervised Learning in Medical Imaging

Exploring the Intrinsic Probability Distribution for Hyperspectral Anomaly Detection

Attentional Prototype Inference for Few-Shot Semantic Segmentation

Relation-aware Hierarchical Attention Framework for Video Question Answering

Supervised Video Summarization via Multiple Feature Sets with Parallel Attention

Exploiting Heterogeneous Graph Neural Networks with Latent Worker/Task Correlation Information for Label Aggregation in Crowdsourcing

Operation-wise Attention Network for Tampering Localization Fusion

Connecting What to Say With Where to Look by Modeling Human Attention Traces

Adversarial Multi-task Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations

Style-based Point Generator with Adversarial Rendering for Point Cloud Completion

From Handcrafted to Deep Features for Pedestrian Detection: A Survey

Open Set Domain Recognition via Attention-Based GCN and Semantic Matching Optimization

The DEVIL is in the Details: A Diagnostic Evaluation Benchmark for Video Inpainting

NBNet: Noise Basis Learning for Image Denoising with Subspace Projection

MGP-AttTCN: An Interpretable Machine Learning Model for the Prediction of Sepsis

Instance-aware Remote Sensing Image Captioning with Cross-hierarchy Attention

EDPN: Enhanced Deep Pyramid Network for Blurry Image Restoration

Found a Reason for me? Weakly-supervised Grounded Visual Question Answering using Capsules

Adaptive Domain-Specific Normalization for Generalizable Person Re-Identification

Modeling High-order Interactions across Multi-interests for Micro-video Recommendation

AFINet: Attentive Feature Integration Networks for Image Classification

T-EMDE: Sketching-based global similarity for cross-modal retrieval

Improving auto-encoder novelty detection using channel attention and entropy minimization

Towards Dynamic Feature Selection with Attention to Assist Banking Customers in Establishing a New Business

Attention and Prediction Guided Motion Detection for Low-Contrast Small Moving Targets

Stochastic Client Selection for Federated Learning with Volatile Clients

A^2-FPN: Attention Aggregation based Feature Pyramid Network for Instance Segmentation

Write-a-speaker: Text-based Emotional and Rhythmic Talking-head Generation

Certainty Driven Consistency Loss on Multi-Teacher Networks for Semi-Supervised Learning

Batch Coherence-Driven Network for Part-aware Person Re-Identification

Error-Robust Multi-View Clustering: Progress, Challenges and Opportunities

ConCAD: Contrastive Learning-based Cross Attention for Sleep Apnea Detection

CPT: Efficient Deep Neural Network Training via Cyclic Precision

SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization

(ASNA) An Attention-based Siamese-Difference Neural Network with Surrogate Ranking Loss function for Perceptual Image Quality Assessment

High-dimensional Functional Graphical Model Structure Learning via Neighborhood Selection Approach

Split and Connect: A Universal Tracklet Booster for Multi-Object Tracking

Sat2Vid: Street-view Panoramic Video Synthesis from a Single Satellite Image

Do Saliency Models Detect Odd-One-Out Targets? New Datasets and Evaluations

Conditional Invertible Neural Networks for Diverse Image-to-Image Translation

Feature Boosting, Suppression, and Diversification for Fine-Grained Visual Classification

OR-Net: Pointwise Relational Inference for Data Completion under Partial Observation

S3Net: A Single Stream Structure for Depth Guided Image Relighting

Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning

Multi-Target Multi-Camera Tracking of Vehicles using Metadata-Aided Re-ID and Trajectory-Based Camera Link Model

LFI-CAM: Learning Feature Importance for Better Visual Explanation

A Perceptual Distortion Reduction Framework for Adversarial Perturbation Generation

One-pass Stochastic Gradient Descent in Overparametrized Two-layer Neural Networks

Unsupervised Discriminative Embedding for Sub-Action Learning in Complex Activities

Dynamic Image Restoration and Fusion Based on Dynamic Degradation

Vehicle Re-identification Method Based on Vehicle Attribute and Mutual Exclusion Between Cameras

Novel Adaptive Binary Search Strategy-First Hybrid Pyramid- and Clustering-Based CNN Filter Pruning Method without Parameters Setting

BiCnet-TKS: Learning Efficient Spatial-Temporal Representation for Video Person Re-Identification

AttendSeg: A Tiny Attention Condenser Neural Network for Semantic Segmentation on the Edge

Crack Semantic Segmentation using the U-Net with Full Attention Strategy

Thermal Infrared Image Colorization for Nighttime Driving Scenes with Top-Down Guided Attention

Learning Multi-Attention Context Graph for Group-Based Re-Identification

Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems

Action Unit Memory Network for Weakly Supervised Temporal Action Localization

Learning Actor-centered Representations for Action Localization in Streaming Videos using Predictive Learning

HiCOMEX: Facial Action Unit Recognition Based on Hierarchy Intensity Distribution and COMEX Relation Learning

Assessing YOLACT++ for real time and robust instance segmentation of medical instruments in endoscopic procedures

A Genetic Algorithm with Tree-structured Mutation for Hyperparameter Optimisation of Graph Neural Networks

Graph Decoupling Attention Markov Networks for Semi-supervised Graph Node Classification

Group Feature Learning and Domain Adversarial Neural Network for aMCI Diagnosis System Based on EEG

Unified Spatio-Temporal Modeling for Traffic Forecasting using Graph Neural Network

MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions

Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding

Visually Imperceptible Adversarial Patch Attacks on Digital Images

Non-uniform Blur Kernel Estimation via Adaptive Basis Decomposition

PatchGuard++: Efficient Provable Attack Detection against Adversarial Patches

Contextualized Keyword Representations for Multi-modal Retinal Image Captioning

GPT2MVS: Generative Pre-trained Transformer-2 for Multi-modal Video Summarization

Delving into Data: Effectively Substitute Training for Black-box Attack

CNN-based search model underestimates attention guidance by simple visual features

Image Inpainting with Edge-guided Learnable Bidirectional Attention Maps

Parallel Scale-wise Attention Network for Effective Scene Text Recognition

Statistical learning for accurate and interpretable battery lifetime prediction

Spatial-Spectral Clustering with Anchor Graph for Hyperspectral Image

Joint Detection and Localization of Stealth False Data Injection Attacks in Smart Grids using Graph Neural Networks

Towards Accurate Text-based Image Captioning with Content Diversity Exploration

Inductive biases and Self Supervised Learning in modelling a physical heating system

H2O: A Benchmark for Visual Human-human Object Handover Analysis

Certifiably Polynomial Algorithm for Best Group Subset Selection

H-Net: Unsupervised Attention-based Stereo Depth Estimation Leveraging Epipolar Geometry

Temporal Attention-Augmented Graph Convolutional Network for Efficient Skeleton-Based Human Action Recognition

On the spatial attention in Spatio-Temporal Graph Convolutional Networks for skeleton-based human action recognition

Aerial Scene Understanding in The Wild: Multi-Scene Recognition via Prototype-based Memory Networks

Diverse Temporal Aggregation and Depthwise Spatiotemporal Factorization for Efficient Video Classification

A Hierarchical Conditional Random Field-based Attention Mechanism Approach for Gastric Histopathology Image Classification

Superpixels and Graph Convolutional Neural Networks for Efficient Detection of Nutrient Deficiency Stress from Aerial Imagery

COSMOS: Catching Out-of-Context Misinformation with Self-Supervised Learning

Link Prediction on N-ary Relational Data Based on Relatedness Evaluation

Machine vision detection to daily facial fatigue with a nonlocal 3D attention network

Multi-Attention-Based Soft Partition Network for Vehicle Re-Identification

Guided Interactive Video Object Segmentation Using Reliability-Based Attention Maps

Actor-Context-Actor Relation Network for Spatio-Temporal Action Localization

Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset

Efficient Two-Stream Network for Violence Detection Using Separable Convolutional LSTM

DeepWORD: A GCN-based Approach for Owner-Member Relationship Detection in Autonomous Driving

Out-of-distribution detection and generalization to enhance fairness in age prediction

CrossATNet - A Novel Cross-Attention Based Framework for Sketch-Based Image Retrieval

UFA-FUSE: A novel deep supervised and hybrid model for multi-focus image fusion

Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and tracking

Self-Enhanced GNN: Improving Graph Neural Networks Using Model Outputs

Beyond Joint Demosaicking and Denoising: An Image Processing Pipeline for a Pixel-bin Image Sensor

Camera Calibration and Player Localization in SoccerNet-v2 and Investigation of their Representations for Action Spotting

Automated problem setting selection in multi-target prediction with AutoMTP

Two-Step Image Dehazing with Intra-domain and Inter-domain Adaptation

Multi-fold Correlation Attention Network for Predicting Traffic Speeds with Heterogeneous Frequency

Let's See Clearly: Contaminant Artifact Removal for Moving Cameras

Multi-scale Self-calibrated Network for Image Light Source Transfer

Attentional Biased Stochastic Gradient for Imbalanced Classification

Efficient Screening of Diseased Eyes based on Fundus Autofluorescence Images using Support Vector Machine

VisualGPT: Data-efficient Adaptation of Pretrained Language Models for Image Captioning

Material Recognition for Automated Progress Monitoring using Deep Learning Methods

Semantic Layout Manipulation with High-Resolution Sparse Attention

Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators

Fusing the Old with the New: Learning Relative Camera Pose with Geometry-Guided Uncertainty

Exploiting Global and Local Attentions for Heavy Rain Removal on Single Images

Learning Implicit 3D Representations of Dressed Humans from Sparse Views

A De-raining semantic segmentation network for real-time foreground segmentation

SiamReID: Confuser Aware Siamese Tracker with Re-identification Feature

Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers

Learning Regional Attention over Multi-resolution Deep Convolutional Features for Trademark Retrieval

Attentive Max Feature Map for Acoustic Scene Classification with Joint Learning considering the Abstraction of Classes

When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution

Class Normalization for (Continual)? Generalized Zero-Shot Learning

Which Hyperparameters to Optimise? An Investigation of Evolutionary Hyperparameter Optimisation in Graph Neural Network For Molecular Property Prediction

AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling

Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes

First and Second Order Dynamics in a Hierarchical SOM system for Action Recognition

Learning Multi-modal Information for Robust Light Field Depth Estimation

Geometric Back-projection Network for Point Cloud Classification

UIEC^2-Net: CNN-based Underwater Image Enhancement Using Two Color Space

GSA-Forecaster: Forecasting Graph-Based Time-Dependent Data with Graph Sequence Attention

High-resolution Depth Maps Imaging via Attention-based Hierarchical Multi-modal Fusion

Predicting Pedestrian Crossing Intention with Feature Fusion and Spatio-Temporal Attention

PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network

Glance and Gaze: Inferring Action-aware Points for One-Stage Human-Object Interaction Detection

SCPM-Net: An Anchor-free 3D Lung Nodule Detection Network using Sphere Representation and Center Points Matching

Involution: Inverting the Inherence of Convolution for Visual Recognition

Fine-Grained Attention for Weakly Supervised Object Localization

MASTER: Multi-Aspect Non-local Network for Scene Text Recognition

Adaptive Filters and Aggregator Fusion for Efficient Graph Convolutions

SVDistNet: Self-Supervised Near-Field Distance Estimation on Surround View Fisheye Cameras

Blending Knowledge in Deep Recurrent Networks for Adverse Event Prediction at Hospital Discharge

Towards Fine-grained Visual Representations by Combining Contrastive Learning with Image Reconstruction and Attention-weighted Pooling

DG-Font: Deformable Generative Networks for Unsupervised Font Generation

DOTS: Decoupling Operation and Topology in Differentiable Architecture Search

FatNet: A Feature-attentive Network for 3D Point Cloud Processing

ConsNet: Learning Consistency Graph for Zero-Shot Human-Object Interaction Detection

Learning Residue-Aware Correlation Filters and Refining Scale Estimates with the GrabCut for Real-Time UAV Tracking

VGF-Net: Visual-Geometric Fusion Learning for Simultaneous Drone Navigation and Height Mapping

RWNE: A Scalable Random-Walk-Based Network Embedding Framework with Personalized Higher-Order Proximity Preserved

MPN: Multimodal Parallel Network for Audio-Visual Event Localization

ACM-Net: Action Context Modeling Network for Weakly-Supervised Temporal Action Localization

Localization of Autonomous Vehicles: Proof of Concept for A Computer Vision Approach

Are GAN generated images easy to detect? A critical analysis of the state-of-the-art

Fine-Grained Fashion Similarity Prediction by Attribute-Specific Embedding Learning

Hyperspectral and LiDAR data classification based on linear self-attention

Graph Sampling Based Deep Metric Learning for Generalizable Person Re-Identification

Efficient Spatialtemporal Context Modeling for Action Recognition

LayoutGMN: Neural Graph Matching for Structural Layout Similarity

Multi-Scale Context Aggregation Network with Attention-Guided for Crowd Counting

DexDeepFM: Ensemble Diversity Enhanced Extreme Deep Factorization Machine Model

Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation

Branch-and-Pruning Optimization Towards Global Optimality in Deep Learning

MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection

A Deep Attentive Convolutional Neural Network for Automatic Cortical Plate Segmentation in Fetal MRI

Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation

PWCLO-Net: Deep LiDAR Odometry in 3D Point Clouds Using Hierarchical Embedding Mask Optimization

Metapath- and Entity-aware Graph Neural Network for Recommendation

Comparison of different convolutional neural network activation functions and methods for building ensembles

SDAN: Squared Deformable Alignment Network for Learning Misaligned Optical Zoom

FESTA: Flow Estimation via Spatial-Temporal Attention for Scene Point Clouds

Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval

LaPred: Lane-Aware Prediction of Multi-Modal Future Trajectories of Dynamic Agents

Less is More: Accelerating Faster Neural Networks Straight from JPEG

Knowing What VQA Does Not: Pointing to Error-Inducing Regions to Improve Explanation Helpfulness

SST-GNN: Simplified Spatio-temporal Traffic forecasting model using Graph Neural Network

SRA-LSTM: Social Relationship Attention LSTM for Human Trajectory Prediction

CR-Fill: Generative Image Inpainting with Auxiliary Contexutal Reconstruction

SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences

Attention, please! A survey of Neural Attention Models in Deep Learning

Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learning

Temporal Memory Relation Network for Workflow Recognition from Surgical Video

Multi-modal Trajectory Prediction for Autonomous Driving with Semantic Map and Dynamic Graph Attention Network

Context Modeling in 3D Human Pose Estimation: A Unified Perspective

A Holistic Representation Guided Attention Network for Scene Text Recognition

Dynamic Attention guided Multi-Trajectory Analysis for Single Object Tracking

Deep Compression for PyTorch Model Deployment on Microcontrollers

$DA^3$: Deep Additive Attention Adaption for Memory-Efficient On-Device Multi-Domain Learning

Meta Batch-Instance Normalization for Generalizable Person Re-Identification

Cross-MPI: Cross-scale Stereo for Image Super-Resolution using Multiplane Images

IA-GCN: Interpretable Attention based Graph Convolutional Network for Disease prediction

RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data

Learning to Predict Salient Faces: A Novel Visual-Audio Saliency Model

A Dataset and Benchmark Towards Multi-Modal Face Anti-Spoofing Under Surveillance Scenarios

Attention-guided Image Compression by Deep Reconstruction of Compressive Sensed Saliency Skeleton

A Temporal Kernel Approach for Deep Learning with Continuous-time Information

Few-shot Action Recognition with Prototype-centered Attentive Learning

Temporal-Relational CrossTransformers for Few-Shot Action Recognition

ACSNet: Action-Context Separation Network for Weakly Supervised Temporal Action Localization

BAF-Detector: An Efficient CNN-Based Detector for Photovoltaic Cell Defect Detection

AR Mapping: Accurate and Efficient Mapping for Augmented Reality

Deep Ensemble Collaborative Learning by using Knowledge-transfer Graph for Fine-grained Object Classification

From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation

Improved Semantic Segmentation of Tuberculosis-consistent findings in Chest X-rays Using Augmented Training of Modality-specific U-Net Models with Weak Localizations

Geometry-Aware Unsupervised Domain Adaptation for Stereo Matching

Learning from Pixel-Level Label Noise: A New Perspective for Semi-Supervised Semantic Segmentation

Synthesize-It-Classifier: Learning a Generative Classifier through RecurrentSelf-analysis

Leaning Compact and Representative Features for Cross-Modality Person Re-Identification

Towards a Unified Approach to Single Image Deraining and Dehazing

GridDehazeNet+: An Enhanced Multi-Scale Network with Intra-Task Knowledge Transfer for Single Image Dehazing

Domain Adaptation with Auxiliary Target Domain-Oriented Classifier

SS-SFDA : Self-Supervised Source-Free Domain Adaptation for Road Segmentation in Hazardous Environments

JDSR-GAN: Constructing A Joint and Collaborative Learning Network for Masked Face Super-Resolution

Jointly Modeling Heterogeneous Student Behaviors and Interactions Among Multiple Prediction Tasks

A Hybrid Attention Mechanism for Weakly-Supervised Temporal Action Localization

Social-STAGE: Spatio-Temporal Multi-Modal Future Trajectory Forecast

Affective Processes: stochastic modelling of temporal context for emotion and facial expression recognition

Structured Co-reference Graph Attention for Video-grounded Dialogue

Object Localization Through a Single Multiple-Model Convolutional Neural Network with a Specific Training Approach

Opportunistic Federated Learning: An Exploration of Egocentric Collaboration for Pervasive Computing Applications

Learning Polar Encodings for Arbitrary-Oriented Ship Detection in SAR Images

Learning Salient Boundary Feature for Anchor-free Temporal Action Localization

Deformable Siamese Attention Networks for Visual Object Tracking

Polysemy Deciphering Network for Robust Human-Object Interaction Detection

SCAN: A Spatial Context Attentive Network for Joint Multi-Agent Intent Prediction

Integrating Novelty Detection Capabilities with MSL Mastcam Operations to Enhance Data Analysis

Are all outliers alike? On Understanding the Diversity of Outliers for Detecting OODs

Generalizing Face Forgery Detection with High-frequency Features

Co-Grounding Networks with Semantic Attention for Referring Expression Comprehension in Videos

Objective Class-based Micro-Expression Recognition through Simultaneous Action Unit Detection and Feature Aggregation

Human-like Controllable Image Captioning with Verb-specific Semantic Roles

Prediction of lung and colon cancer through analysis of histopathological images by utilizing Pre-trained CNN models with visualization of class activation and saliency maps

AET-EFN: A Versatile Design for Static and Dynamic Event-Based Vision

A Large-Scale Dataset for Benchmarking Elevator Button Segmentation and Character Recognition

A Survey of Hand Crafted and Deep Learning Methods for Image Aesthetic Assessment

Human De-occlusion: Invisible Perception and Recovery for Humans

Context-aware Biaffine Localizing Network for Temporal Sentence Grounding

Hidden Technical Debts for Fair Machine Learning in Financial Services

MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation

Reference-Aided Part-Aligned Feature Disentangling for Video Person Re-Identification

Discriminative and Semantic Feature Selection for Place Recognition towards Dynamic Environments

Deep Dense Multi-scale Network for Snow Removal Using Semantic and Geometric Priors

Classifier Crafting: Turn Your ConvNet into a Zero-Shot Learner!

ReviewViz: Assisting Developers Perform Empirical Study on Energy Consumption Related Reviews for Mobile Applications

Linear Last-iterate Convergence in Constrained Saddle-point Optimization

Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets

AXM-Net: Cross-Modal Context Sharing Attention Network for Person Re-ID

DCF-ASN: Coarse-to-fine Real-time Visual Tracking via Discriminative Correlation Filter and Attentional Siamese Network

HW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark

CLTA: Contents and Length-based Temporal Attention for Few-shot Action Recognition

A Novel Visual Fault Detection and Classification System for Semiconductor Manufacturing Using Stacked Hybrid Convolutional Neural Networks

Which to Match? Selecting Consistent GT-Proposal Assignment for Pedestrian Detection

Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAE

A Deep Learning Framework for Recognizing both Static and Dynamic Gestures

Privileged Pooling: Better Sample Efficiency Through Supervised Attention

Improved Deep Classwise Hashing With Centers Similarity Learning for Image Retrieval

NAS-TC: Neural Architecture Search on Temporal Convolutions for Complex Action Recognition

MSR-DARTS: Minimum Stable Rank of Differentiable Architecture Search

RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems

An Efficient Multitask Neural Network for Face Alignment, Head Pose Estimation and Face Tracking

Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data

Dual Attention-in-Attention Model for Joint Rain Streak and Raindrop Removal

Improving Adversarial Robustness via Channel-wise Activation Suppressing

Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation

Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domain

AttaNet: Attention-Augmented Network for Fast and Accurate Scene Parsing

ES-Net: Erasing Salient Parts to Learn More in Re-Identification

A Discriminative Vectorial Framework for Multi-modal Feature Representation

Regional Attention with Architecture-Rebuilt 3D Network for RGB-D Gesture Recognition

Simple and effective localized attribute representations for zero-shot learning

PcmNet: Position-Sensitive Context Modeling Network for Temporal Action Localization

HOT-VAE: Learning High-Order Label Correlation for Multi-Label Classification via Attention-Based Variational Autoencoders

Interpretable Attention Guided Network for Fine-grained Visual Classification

From Hand-Perspective Visual Information to Grasp Type Probabilities: Deep Learning via Ranking Labels

On Implicit Attribute Localization for Generalized Zero-Shot Learning

Learning Graph Neural Networks with Positive and Unlabeled Nodes

Unsupervised Person Re-Identification with Multi-Label Learning Guided Self-Paced Clustering

A Tractable Online Learning Algorithm for the Multinomial Logit Contextual Bandit

Use square root affinity to regress labels in semantic segmentation

ERASOR: Egocentric Ratio of Pseudo Occupancy-based Dynamic Object Removal for Static 3D Point Cloud Map Building

Perception Framework through Real-Time Semantic Segmentation and Scene Recognition on a Wearable System for the Visually Impaired

Panoptic Lintention Network: Towards Efficient Navigational Perception for the Visually Impaired

An End-to-End Foreground-Aware Network for Person Re-Identification

Visual-Semantic Graph Attention Networks for Human-Object Interaction Detection

Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation

Demonstrating Rosa: the fairness solution for any Data Analytic pipeline

Critical Evaluation of Deep Neural Networks for Wrist Fracture Detection

Enhanced 3D Human Pose Estimation from Videos by using Attention-Based Neural Network with Dilated Convolutions

Incomplete Descriptor Mining with Elastic Loss for Person Re-Identification

EDNet: Efficient Disparity Estimation with Cost Volume Combination and Attention-based Spatial Residual

Learning Granularity-Aware Convolutional Neural Network for Fine-Grained Visual Classification

Cross-View Regularization for Domain Adaptive Panoptic Segmentation

HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline

A Unified Theory of Decentralized SGD with Changing Topology and Local Updates

An Interpretable Multiple-Instance Approach for the Detection of referable Diabetic Retinopathy from Fundus Images

Deep Domain Adaptation for Ordinal Regression of Pain Intensity Estimation Using Weakly-Labelled Videos

Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World

Regularizing Attention Networks for Anomaly Detection in Visual Question Answering

Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating

STUDD: A Student-Teacher Method for Unsupervised Concept Drift Detection

Video action detection by learning graph-based spatio-temporal interactions

ADAADepth: Adapting Data Augmentation and Attention for Self-Supervised Monocular Depth Estimation

BSN++: Complementary Boundary Regressor with Scale-Balanced Relation Modeling for Temporal Action Proposal Generation

Semi-Supervised Active Learning for COVID-19 Lung Ultrasound Multi-symptom Classification

Nested-block self-attention for robust radiotherapy planning segmentation

Batch Bayesian Optimization on Permutations using Acquisition Weighted Kernels

Where to look at the movies : Analyzing visual attention to understand movie editing

A Universal Model for Cross Modality Mapping by Relational Reasoning

Bottom-Up Temporal Action Localization with Mutual Regularization

Gaze-Informed Multi-Objective Imitation Learning from Human Demonstrations

A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix

Arbitrary-Oriented Ship Detection through Center-Head Point Extraction

Noisy Student Training using Body Language Dataset Improves Facial Expression Recognition

Character-Based Handwritten Text Transcription with Attention Networks

Efficient and Accurate Multi-scale Topological Network for Single Image Dehazing

Efficient Palm-Line Segmentation with U-Net Context Fusion Module

Accelerating Recursive Partition-Based Causal Structure Learning

Stability and Generalization of the Decentralized Stochastic Gradient Descent

No-Reference Quality Assessment for 360-degree Images by Analysis of Multi-frequency Information and Local-global Naturalness

Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic Programming

Leveraging Meta-path Contexts for Classification in Heterogeneous Information Networks

Scribble-Supervised Semantic Segmentation by Uncertainty Reduction on Neural Representation and Self-Supervision on Neural Eigenspace

Trends in Vehicle Re-identification Past, Present, and Future: A Comprehensive Review

An Enhanced Adversarial Network with Combined Latent Features for Spatio-Temporal Facial Affect Estimation in the Wild

Spatio-Temporal Graph Dual-Attention Network for Multi-Agent Prediction and Tracking

AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units

Improving Visual Place Recognition Performance by Maximising Complementarity

Accurate and Clear Precipitation Nowcasting with Consecutive Attention and Rain-map Discrimination

Learning to Recognize Actions on Objects in Egocentric Video with Attention Dictionaries

EDITH :ECG biometrics aided by Deep learning for reliable Individual auTHentication

Knowledge Distillation with Adaptive Asymmetric Label Sharpening for Semi-supervised Fracture Detection in Chest X-rays

And/or trade-off in artificial neurons: impact on adversarial robustness

Two-stage Training of Graph Neural Networks for Graph Classification

Knowledge Graph Embedding using Graph Convolutional Networks with Relation-Aware Attention

Improving Automated Visual Fault Detection by Combining a Biologically Plausible Model of Visual Attention with Deep Learning

Adversarial Unsupervised Domain Adaptation Guided with Deep Clustering for Face Presentation Attack Detection

Towards DeepSentinel: An extensible corpus of labelled Sentinel-1 and -2 imagery and a general-purpose sensor-fusion semantic embedding model

Adversarial Attacks and Defenses in Physiological Computing: A Systematic Review

FedCM: A Real-time Contribution Measurement Method for Participants in Federated Learning

Multiple-view clustering for identifying subject clusters and brain sub-networks using functional connectivity matrices without vectorization

Doctor Imitator: A Graph-based Bone Age Assessment Framework Using Hand Radiographs

Sequential vessel segmentation via deep channel attention network

M2FN: Multi-step Modality Fusion for Advertisement Image Assessment

(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Network

Improving Non-Intrusive Load Disaggregation through an Attention-Based Deep Neural Network

Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay

Towards Accurate RGB-D Saliency Detection with Complementary Attention and Adaptive Integration

Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud

Understanding Higher-order Structures in Evolving Graphs: A Simplicial Complex based Kernel Estimation Approach

Template-Free Try-on Image Synthesis via Semantic-guided Optimization

Bidirectional Multi-scale Attention Networks for Semantic Segmentation of Oblique UAV Imagery

PointCutMix: Regularization Strategy for Point Cloud Classification

Temporal Cascade and Structural Modelling of EHRs for Granular Readmission Prediction

ABCNet: Attentive Bilateral Contextual Network for Efficient Semantic Segmentation of Fine-Resolution Remote Sensing Images

Answer Questions with Right Image Regions: A Visual Attention Regularization Approach

Attributes-Guided and Pure-Visual Attention Alignment for Few-Shot Recognition

Do Not Forget to Attend to Uncertainty while Mitigating Catastrophic Forgetting

Multi-Instance Learning by Utilizing Structural Relationship among Instances

Rank-Consistency Deep Hashing for Scalable Multi-Label Image Search

Deep DA for Ordinal Regression of Pain Intensity Estimation Using Weakly-Labeled Videos

Real-time Prediction for Mechanical Ventilation in COVID-19 Patients using A Multi-task Gaussian Process Multi-objective Self-attention Network

Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark

Semi-Supervised Disentanglement of Class-Related and Class-Independent Factors in VAE

Spatio-temporal Weather Forecasting and Attention Mechanism on Convolutional LSTMs

A NIR-to-VIS face recognition via part adaptive and relation attention module

ACNe: Attentive Context Normalization for Robust Permutation-Equivariant Learning

Urban Change Detection by Fully Convolutional Siamese Concatenate Network with Attention

Cascade Network with Guided Loss and Hybrid Attention for Finding Good Correspondences

Fine-Grained Visual Classification via Simultaneously Learning of Multi-regional Multi-grained Features

Gigapixel Histopathological Image Analysis using Attention-based Neural Networks

Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure

Spatiotemporal Dilated Convolution with Uncertain Matching for Video-based Crowd Estimation

GIID-Net: Generalizable Image Inpainting Detection via Neural Architecture Search and Attention

Multi-Threshold Attention U-Net (MTAU) based Model for Multimodal Brain Tumor Segmentation in MRI scans

Deep Triplet Hashing Network for Case-based Medical Image Retrieval

A finite sample analysis of the benign overfitting phenomenon for ridge function estimation

Generalising via Meta-Examples for Continual Learning in the Wild

Exchangeable deep neural networks for set-to-set matching and learning

torchdistill: A Modular, Configuration-Driven Framework for Knowledge Distillation

Collaborative Teacher-Student Learning via Multiple Knowledge Transfer

Efficient Video Summarization Framework using EEG and Eye-tracking Signals

Convolutional Neural Network-Based Age Estimation Using B-Mode Ultrasound Tongue Image

Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks

Anatomy-aware 3D Human Pose Estimation with Bone-based Pose Decomposition

Semi-synthesis: A fast way to produce effective datasets for stereo matching

The Consequences of the Framing of Machine Learning Risk Prediction Models: Evaluation of Sepsis in General Wards

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size

Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solution

SmaAt-UNet: Precipitation Nowcasting using a Small Attention-UNet Architecture

Grad-CAM guided channel-spatial attention module for fine-grained visual classification

Exploiting Web Images for Fine-Grained Visual Recognition by Eliminating Noisy Samples and Utilizing Hard Ones

Polarization-driven Semantic Segmentation via Efficient Attention-bridged Fusion

Multimodal Engagement Analysis from Facial Videos in the Classroom

Dense outlier detection and open-set recognition based on training with noisy negative images

Adaptive Neighbourhoods for the Discovery of Adversarial Examples

Human Interaction Recognition Framework based on Interacting Body Part Attention

A Two-stream Neural Network for Pose-based Hand Gesture Recognition

Knowledge Graph Embedding for Link Prediction: A Comparative Analysis

Driver Glance Classification In-the-wild: Towards Generalization Across Domains and Subjects

Image Denoising using Attention-Residual Convolutional Neural Networks

PICA: A Pixel Correlation-based Attentional Black-box Adversarial Attack

Attend and Decode: 4D fMRI Task State Decoding Using Attention Models

Separable Batch Normalization for Robust Facial Landmark Localization with Cross-protocol Network Training

Coarse Temporal Attention Network (CTA-Net) for Driver's Activity Recognition

Context-aware Attentional Pooling (CAP) for Fine-grained Visual Classification

Gradient Descent Averaging and Primal-dual Averaging for Strongly Convex Optimization

Exploring the Capacity of an Orderless Box Discretization Network for Multi-orientation Scene Text Detection

Risk & returns around FOMC press conferences: a novel perspective from computer vision

Residual Shuffle-Exchange Networks for Fast Processing of Long Sequences

Graph Convolutional Networks for Hyperspectral Image Classification

A Metaheuristic-Driven Approach to Fine-Tune Deep Boltzmann Machines

AVGCN: Trajectory Prediction using Graph Convolutional Networks Guided by Human Attention

Reliability Check via Weight Similarity in Privacy-Preserving Multi-Party Machine Learning

Lane Attention: Predicting Vehicles' Moving Trajectories by Learning Their Attention over Lanes

SPAN: Spatial Pyramid Attention Network forImage Manipulation Localization

VMLoc: Variational Fusion For Learning-Based Multimodal Camera Localization

Image deblurring based on lightweight multi-information fusion network

AMENet: Attentive Maps Encoder Network for Trajectory Prediction

ShineOn: Illuminating Design Choices for Practical Video-based Virtual Clothing Try-on

Phase Retrieval using Expectation Consistent Signal Recovery Algorithm based on Hypernetwork

Deep Attention Based Semi-Supervised 2D-Pose Estimation for Surgical Instruments

WDR FACE: The First Database for Studying Face Detection in Wide Dynamic Range

Multi-Domain Image-to-Image Translation with Adaptive Inference Graph

Learning Omni-frequency Region-adaptive Representations for Real Image Super-Resolution

An Unsupervised Learning Method with Convolutional Auto-Encoder for Vessel Trajectory Similarity Computation

Contextual Non-Local Alignment over Full-Scale Representation for Text-Based Person Search

Probabilistic Graph Attention Network with Conditional Kernels for Pixel-Wise Prediction

Exploiting Diverse Characteristics and Adversarial Ambivalence for Domain Adaptive Segmentation

Scale-Aware Network with Regional and Semantic Attentions for Crowd Counting under Cluttered Background

Identification of Latent Variables From Graphical Model Residuals

Adaptive-Attentive Geolocalization from few queries: a hybrid approach

Attention-based Convolutional Autoencoders for 3D-Variational Data Assimilation

Node2Seq: Towards Trainable Convolutions in Graph Neural Networks

Risk markers by sex and age group for in-hospital mortality in patients with STEMI or NSTEMI: an approach based on machine learning

Comparison of Classification Algorithms Towards Subject-Specific and Subject-Independent BCI

WildDeepfake: A Challenging Real-World Dataset for Deepfake Detection

Het-node2vec: second order random walk sampling for heterogeneous multigraphs embedding

Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation

Graph Partitioning and Graph Neural Network based Hierarchical Graph Matching for Graph Similarity Computation

AttnMove: History Enhanced Trajectory Recovery via Attentional Network

SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation

Attention, Please! Adversarial Defense via Attention Rectification and Preservation

Panoptic Feature Fusion Net: A Novel Instance Segmentation Paradigm for Biomedical and Biological Images

Combinatorial Pure Exploration with Full-bandit Feedback and Beyond: Solving Combinatorial Optimization under Uncertainty with Limited Observation

A Deep Retinal Image Quality Assessment Network with Salient Structure Priors

Provably Training Neural Network Classifiers under Fairness Constraints

Frame Aggregation and Multi-Modal Fusion Framework for Video-Based Person Recognition

Class-Attentive Diffusion Network for Semi-Supervised Classification

Towards Reducing Severe Defocus Spread Effects for Multi-Focus Image Fusion via an Optimization Based Strategy

Tips and Tricks for Webly-Supervised Fine-Grained Recognition: Learning from the WebFG 2020 Challenge

Sparse PCA via $l_{2,p}$-Norm Regularization for Unsupervised Feature Selection

Lip-reading with Hierarchical Pyramidal Convolution and Self-Attention

Fine-Grained 3D Shape Classification with Hierarchical Part-View Attentions

Memory-Efficient Hierarchical Neural Architecture Search for Image Restoration

Exploring Emotion Features and Fusion Strategies for Audio-Video Emotion Recognition

Coarse to Fine: Multi-label Image Classification with Global/Local Attention

A Simple Fine-tuning Is All You Need: Towards Robust Deep Learning Via Adversarial Fine-tuning

GraNet: Global Relation-aware Attentional Network for ALS Point Cloud Classification

A Regret bound for Non-stationary Multi-Armed Bandits with Fairness Constraints

Exploring Motion Boundaries in an End-to-End Network for Vision-based Parkinson's Severity Assessment

Person Re-Identification using Deep Learning Networks: A Systematic Review

Deep Ancient Roman Republican Coin Classification via Feature Fusion and Attention

EPSNet: Efficient Panoptic Segmentation Network with Cross-layer Attention Fusion

The Multimodal Driver Monitoring Database: A Naturalistic Corpus to Study Driver Attention

Estimation of Driver's Gaze Region from Head Position and Orientation using Probabilistic Confidence Regions

ConvMath: A Convolutional Sequence Network for Mathematical Expression Recognition

MARA-Net: Single Image Deraining Network with Multi-level connections and Adaptive Regional Attentions

Hierarchical Recurrent Attention Networks for Structured Online Maps

Multiple Instance Segmentation in Brachial Plexus Ultrasound Image Using BPMSegNet

Predicting Online Video Advertising Effects with Multimodal Deep Learning

Natural vs Balanced Distribution in Deep Learning on Whole Slide Images for Cancer Detection

AttentionLite: Towards Efficient Self-Attention Models for Vision

A Frequency And Phase Attention Based Deep Learning Framework For Partial Discharge Detection On Insulated Overhead Conductors

Incremental Real-Time Personalization in Human Activity Recognition Using Domain Adaptive Batch Normalization

An Overview of Facial Micro-Expression Analysis: Data, Methodology and Challenge

Improving unsupervised anomaly localization by applying multi-scale memories to autoencoders

T-GAP: Learning to Walk across Time for Temporal Knowledge Graph Completion

A Graph Attention Based Approach for Trajectory Prediction in Multi-agent Sports Games

LGENet: Local and Global Encoder Network for Semantic Segmentation of Airborne Laser Scanning Point Clouds

Weakly-Supervised Action Localization and Action Recognition using Global-Local Attention of 3D CNN

Classification by Attention: Scene Graph Classification with Prior Knowledge

I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting

Difficulty in estimating visual information from randomly sampled images

AIST: An Interpretable Attention-based Deep Learning Model for Crime Prediction

Two-Stage Copy-Move Forgery Detection with Self Deep Matching and Proposal SuperGlue

Attentional Local Contrast Networks for Infrared Small Target Detection

STL-SGD: Speeding Up Local SGD with Stagewise Communication Period

Fitting the Search Space of Weight-sharing NAS with Graph Convolutional Networks

Can AutoML outperform humans? An evaluation on popular OpenML datasets using AutoML Benchmark

Dilated-Scale-Aware Attention ConvNet For Multi-Class Object Counting

Deep Layout of Custom-size Furniture through Multiple-domain Learning

Image Inpainting Guided by Coherence Priors of Semantics and Textures

Efficient Human Pose Estimation by Learning Deeply Aggregated Representations

Semantic-Guided Representation Enhancement for Self-supervised Monocular Trained Depth Estimation

Deep Bayesian Active Learning, A Brief Survey on Recent Advances

Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming

DeepFakesON-Phys: DeepFakes Detection based on Heart Rate Estimation

Learned Video Codec with Enriched Reconstruction for CLIC P-frame Coding

An Adaptive Memory Multi-Batch L-BFGS Algorithm for Neural Network Training

One Point is All You Need: Directional Attention Point for Feature Learning

Learning Enhanced Resolution-wise features for Human Pose Estimation

Split then Refine: Stacked Attention-guided ResUNets for Blind Single Image Visible Watermark Removal

Automatic Detection of Cardiac Chambers Using an Attention-based YOLOv4 Framework from Four-chamber View of Fetal Echocardiography

Adversarial Attacks and Defenses on Graphs: A Review, A Tool and Empirical Studies

Separating Content from Style Using Adversarial Learning for Recognizing Text in the Wild

Weakly-supervised Object Localization for Few-shot Learning and Fine-grained Few-shot Learning

ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting

Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks

I-GCN: Robust Graph Convolutional Network via Influence Mechanism

Deep Learning Approach for Matrix Completion Using Manifold Learning

Untangling tradeoffs between recurrence and self-attention in neural networks

Exploring the Vulnerability of Deep Neural Networks: A Study of Parameter Corruption

Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise

Federated Learning in Unreliable and Resource-Constrained Cellular Wireless Networks

Group-Wise Semantic Mining for Weakly Supervised Semantic Segmentation

CASTing Your Model: Learning to Localize Improves Self-Supervised Representations

SPU-Net: Self-Supervised Point Cloud Upsampling by Coarse-to-Fine Reconstruction with Self-Projection Optimization

Learning Structured Declarative Rule Sets -- A Challenge for Deep Discrete Learning

Scale Aware Adaptation for Land-Cover Classification in Remote Sensing Imagery

Weakly-Supervised Cross-Domain Adaptation for Endoscopic Lesions Segmentation

Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't

Age and Gender Prediction From Face Images Using Attentional Convolutional Network

SuperCoder: Program Learning Under Noisy Conditions From Superposition of States

End-to-end Handwritten Paragraph Text Recognition Using a Vertical Attention Network

MERANet: Facial Micro-Expression Recognition using 3D Residual Attention Network

Neural Temporal Point Processes For Modelling Electronic Health Records

Ada-Segment: Automated Multi-loss Adaptation for Panoptic Segmentation

Devil's in the Details: Aligning Visual Clues for Conditional Embedding in Person Re-Identification

Backpropagating Linearly Improves Transferability of Adversarial Examples

Revisiting Street-to-Aerial View Image Geo-localization and Orientation Estimation

Robust Multi-class Feature Selection via $l_{2,0}$-Norm Regularization Minimization

CompFeat: Comprehensive Feature Aggregation for Video Instance Segmentation

Select, Label, and Mix: Learning Discriminative Invariant Feature Representations for Partial Domain Adaptation

Selective Eye-gaze Augmentation To Enhance Imitation Learning In Atari Games

Attention-Driven Dynamic Graph Convolutional Network for Multi-Label Image Recognition

Multi Scale Temporal Graph Networks For Skeleton-based Action Recognition

SelfText Beyond Polygon: Unconstrained Text Detection with Box Supervision and Dynamic Self-Training

Effective Label Propagation for Discriminative Semi-Supervised Domain Adaptation

Learning to Attend Relevant Regions in Videos from Eye Fixations

A Multi-task Contextual Atrous Residual Network for Brain Tumor Detection & Segmentation

Lookahead optimizer improves the performance of Convolutional Autoencoders for reconstruction of natural images

Meta-Generating Deep Attentive Metric for Few-shot Classification

Attentive WaveBlock: Complementarity-enhanced Mutual Networks for Unsupervised Domain Adaptation in Person Re-identification and Beyond

SensitiveLoss: Improving Accuracy and Fairness of Face Representations with Discrimination-Aware Deep Learning

Highly Accurate CNN Inference Using Approximate Activation Functions over Homomorphic Encryption

Blockchain Assisted Decentralized Federated Learning (BLADE-FL) with Lazy Clients

Partially Shared Semi-supervised Deep Matrix Factorization with Multi-view Data

Addressing Cold Start in Recommender Systems with Hierarchical Graph Neural Networks

Trajformer: Trajectory Prediction with Local Self-Attentive Contexts for Autonomous Driving

Person Perception Biases Exposed: Revisiting the First Impressions Dataset

Adaptive Compact Attention For Few-shot Video-to-video Translation

Multi-scale Adaptive Task Attention Network for Few-Shot Learning

BSNet: Bi-Similarity Network for Few-shot Fine-grained Image Classification

DeepSOCIAL: Social Distancing Monitoring and Infection Risk Assessment in COVID-19 Pandemic

Uncertainty-Aware Physically-Guided Proxy Tasks for Unseen Domain Face Anti-spoofing

Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach

Distributed Variational Bayesian Algorithms Over Sensor Networks

Graph Prototypical Networks for Few-shot Learning on Attributed Networks

Computational efficient deep neural network with difference attention maps for facial action unit detection

Net2: A Graph Attention Network Method Customized for Pre-Placement Net Length Estimation

Bidirectional Modeling and Analysis of Brain Aging with Normalizing Flows

FusiformNet: Extracting Discriminative Facial Features on Different Levels

Adherent Mist and Raindrop Removal from a Single Image Using Attentive Convolutional Network

Neural Networks for Pulmonary Disease Diagnosis using Auditory and Demographic Information

FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning

Attention Aware Cost Volume Pyramid Based Multi-view Stereo Network for 3D Reconstruction

Encoder-Decoder Based Convolutional Neural Networks with Multi-Scale-Aware Modules for Crowd Counting

Advancements of federated learning towards privacy preservation: from federated learning to split learning

UFPR-Periocular: A Periocular Dataset Collected by Mobile Devices in Unconstrained Scenarios

Conditional Uncorrelation and Efficient Non-approximate Subset Selection in Sparse Regression

Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data

Unsupervised Many-to-Many Image-to-Image Translation Across Multiple Domains

Pyramid Point: A Multi-Level Focusing Network for Revisiting Feature Layers

Multi-task Learning for Human Settlement Extent Regression and Local Climate Zone Classification

Liquid Warping GAN with Attention: A Unified Framework for Human Image Synthesis

Attentional-GCNN: Adaptive Pedestrian Trajectory Prediction towards Generic Autonomous Vehicle Use Cases

PS-DeVCEM: Pathology-sensitive deep learning model for video capsule endoscopy based on weakly labeled data

Language-guided Navigation via Cross-Modal Grounding and Alternate Adversarial Learning

ATSal: An Attention Based Architecture for Saliency Prediction in 360 Videos

DiPE: Deeper into Photometric Errors for Unsupervised Learning of Depth and Ego-motion from Monocular Videos

Efficient Consensus Model based on Proximal Gradient Method applied to Convolutional Sparse Problems

Adversarial Examples for $k$-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams

Rethinking the competition between detection and ReID in Multi-Object Tracking

Patient-independent Epileptic Seizure Prediction using Deep Learning Models

Neuro-Symbolic Representations for Video Captioning: A Case for Leveraging Inductive Biases for Vision and Language

Attentional Separation-and-Aggregation Network for Self-supervised Depth-Pose Learning in Dynamic Scenes

Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection

Predicting Rigid Body Dynamics using Dual Quaternion Recurrent Neural Networks with Quaternion Attention

Dense-Resolution Network for Point Cloud Classification and Segmentation

2D+3D Facial Expression Recognition via Discriminative Dynamic Range Enhancement and Multi-Scale Learning

Fast and Robust Cascade Model for Multiple Degradation Single Image Super-Resolution

AMPA-Net: Optimization-Inspired Attention Neural Network for Deep Compressed Sensing

iPerceive: Applying Common-Sense Reasoning to Multi-Modal Dense Video Captioning and Video Question Answering

Hybrid Attentional Memory Network for Computational drug repositioning

Domain Adaptation Gaze Estimation by Embedding with Prediction Consistency

Let's Get Dirty: GAN Based Data Augmentation for Camera Lens Soiling Detection in Autonomous Driving

SynDistNet: Self-Supervised Monocular Fisheye Camera Distance Estimation Synergized with Semantic Segmentation for Autonomous Driving

Representing Deep Neural Networks Latent Space Geometries with Graphs

Online Knowledge Distillation via Multi-branch Diversity Enhancement

Video Reconstruction by Spatio-Temporal Fusion of Blurred-Coded Image Pair

Deep Template Matching for Pedestrian Attribute Recognition with the Auxiliary Supervision of Attribute-wise Keypoints

Lightweight Single-Image Super-Resolution Network with Attentive Auxiliary Feature Learning

Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems

Scribble-Supervised Semantic Segmentation by Random Walk on Neural Representation and Self-Supervision on Neural Eigenspace

Lip-reading with Densely Connected Temporal Convolutional Networks

Multi-modal, multi-task, multi-attention (M3) deep learning detection of reticular pseudodrusen: towards automated and accessible classification of age-related macular degeneration

Noise Conscious Training of Non Local Neural Network powered by Self Attentive Spectral Normalized Markovian Patch GAN for Low Dose CT Denoising

DASNet: Dual attentive fully convolutional siamese networks for change detection of high resolution satellite images

Probability-Density-Based Deep Learning Paradigm for the Fuzzy Design of Functional Metastructures

A Quantum-Inspired Probabilistic Model for the Inverse Design of Meta-Structures

Fast & Slow Learning: Incorporating Synthetic Gradients in Neural Memory Controllers

Selective Spatio-Temporal Aggregation Based Pose Refinement System: Towards Understanding Human Activities in Real-World Videos

On Estimating the Training Cost of Conversational Recommendation Systems

Find it if You Can: End-to-End Adversarial Erasing for Weakly-Supervised Semantic Segmentation

Comparison between ARIMA and Deep Learning Models for Temperature Forecasting

MAGNeto: An Efficient Deep Learning Method for the Extractive Tags Summarization Problem

Integrating Human Gaze into Attention for Egocentric Activity Recognition

Coarse- and Fine-grained Attention Network with Background-aware Loss for Crowd Density Map Estimation

TB-Net: A Three-Stream Boundary-Aware Network for Fine-Grained Pavement Disease Segmentation

Improving Sales Forecasting Accuracy: A Tensor Factorization Approach with Demand Awareness

Runtime Performances Benchmark for Knowledge Graph Embedding Methods

End-to-end Deep Learning Methods for Automated Damage Detection in Extreme Events at Various Scales

Registration Loss Learning for Deep Probabilistic Point Set Registration

NAS-FAS: Static-Dynamic Central Difference Network Search for Face Anti-Spoofing

Cross-Media Keyphrase Prediction: A Unified Framework with Multi-Modality Multi-Head Attention and Image Wordings

Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks

Adversarial Attacks on Machine Learning Systems for High-Frequency Trading

GAIN: Graph Attention & Interaction Network for Inductive Semi-Supervised Learning over Large-scale Graphs

SuPEr-SAM: Using the Supervision Signal from a Pose Estimator to Train a Spatial Attention Module for Personal Protective Equipment Recognition

Facial UV Map Completion for Pose-invariant Face Recognition: A Novel Adversarial Approach based on Coupled Attention Residual UNets

Unsupervised Deep Persistent Monocular Visual Odometry and Depth Estimation in Extreme Environments

In the Eye of the Beholder: Gaze and Actions in First Person Video

Learning Deep Interleaved Networks with Asymmetric Co-Attention for Image Restoration

RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning

Sea-Net: Squeeze-And-Excitation Attention Net For Diabetic Retinopathy Grading

CNN Profiler on Polar Coordinate Images for Tropical Cyclone Structure Analysis

Mining Generalized Features for Detecting AI-Manipulated Fake Faces

One-vs.-One Mitigation of Intersectional Bias: A General Method to Extend Fairness-Aware Binary Classification

Progressive Multi-stage Feature Mix for Person Re-Identification

Where to Look and How to Describe: Fashion Image Retrieval with an Attentional Heterogeneous Bilinear Network

$P^2$ Net: Augmented Parallel-Pyramid Net for Attention Guided Pose Estimation

Fast and Accurate Light Field Saliency Detection through Feature Extraction

Not Half Bad: Exploring Half-Precision in Graph Convolutional Neural Networks

Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks

DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting

The Pursuit of Algorithmic Fairness: On "Correcting" Algorithmic Unfairness in a Child Welfare Reunification Success Classifier

Talk2Nav: Long-Range Vision-and-Language Navigation with Dual Attention and Spatial Memory

mEBAL: A Multimodal Database for Eye Blink Detection and Attention Level Estimation

Two-Stream Consensus Network for Weakly-Supervised Temporal Action Localization

Learning Dual Semantic Relations with Graph Attention for Image-Text Matching

Attention Deep Model with Multi-Scale Deep Supervision for Person Re-Identification

Automatically Learning Compact Quality-aware Surrogates for Optimization Problems

Effective Proximal Methods for Non-convex Non-smooth Regularized Learning

Universal Adversarial Attack on Attention and the Resulting Dataset DAmageNet

Mutual-Supervised Feature Modulation Network for Occluded Pedestrian Detection

TargetDrop: A Targeted Regularization Method for Convolutional Neural Networks

On the Global Self-attention Mechanism for Graph Convolutional Networks

ST-GRAT: A Novel Spatio-temporal Graph Attention Network for Accurately Forecasting Dynamically Changing Road Speed

Extracting Seasonal Gradual Patterns from Temporal Sequence Data Using Periodic Patterns Mining

A Generalized Zero-Shot Framework for Emotion Recognition from Body Gestures

Kalman Filtering Attention for User Behavior Modeling in CTR Prediction

Contextual Heterogeneous Graph Network for Human-Object Interaction Detection

Query Attack via Opposite-Direction Feature:Towards Robust Image Retrieval

A Graph Attention Spatio-temporal Convolutional Network for 3D Human Pose Estimation in Video

DeepApple: Deep Learning-based Apple Detection using a Suppression Mask R-CNN

Multivariate Gaussian Variational Inference by Natural Gradient Descent

AUTSL: A Large Scale Multi-modal Turkish Sign Language Dataset and Baseline Methods

Rotation Invariant Aerial Image Retrieval with Group Convolutional Metric Learning

Gaussian Constrained Attention Network for Scene Text Recognition

Unsupervised Foveal Vision Neural Networks with Top-Down Attention

View-Invariant Gait Recognition with Attentive Recurrent Learning of Partial Representations

Are Adaptive Face Recognition Systems still Necessary? Experiments on the APE Dataset

Answer-checking in Context: A Multi-modal FullyAttention Network for Visual Question Answering

DEAL: Difficulty-aware Active Learning for Semantic Segmentation

A Novel Just-Noticeable-Difference-based Saliency-Channel Attention Residual Network for Full-Reference Image Quality Predictions

Drug-Drug Interaction Prediction with Wasserstein Adversarial Autoencoder-based Knowledge Graph Embeddings

How to compare adversarial robustness of classifiers from a global perspective

Normal Forms for (Semantically) Witness-Based Learners in Inductive Inference

Towards Optimal Filter Pruning with Balanced Performance and Pruning Speed

Viewpoint-Aware Channel-Wise Attentive Network for Vehicle Re-Identification

Orientation-aware Vehicle Re-identification with Semantics-guided Part Attention Network

Convolutional Neural Network optimization via Channel Reassessment Attention module

Unsupervised Semantic Aggregation and Deformable Template Matching for Semi-Supervised Learning

Facial Pose Estimation by Deep Learning from Label Distributions

Pay Attention to the cough: Early Diagnosis of COVID-19 using Interpretable Symptoms Embeddings with Cough Sound Signal Processing

Is It Time to Redefine the Classification Task for Deep Neural Networks?

Boosted EfficientNet: Detection of Lymph Node Metastases in Breast Cancer Using Convolutional Neural Network

Adversarial Metric Attack and Defense for Person Re-identification

ADCC: An Effective and Intelligent Attention Dense Color Constancy System for Studying Images in Smart Cities

Affect Expression Behaviour Analysis in the Wild using Spatio-Channel Attention and Complementary Context Information

Interpretable Neural Computation for Real-World Compositional Visual Question Answering

Online Anomaly Detection in Surveillance Videos with Asymptotic Bounds on False Alarm Rate

Fast Objective & Duality Gap Convergence for Nonconvex-Strongly-Concave Min-Max Problems

GraphMix: Improved Training of GNNs for Semi-Supervised Learning

A Pose Proposal and Refinement Network for Better Object Pose Estimation

Attention Model Enhanced Network for Classification of Breast Cancer Image

Channel Recurrent Attention Networks for Video Pedestrian Retrieval

Microscopic fine-grained instance classification through deep attention

ECG Classification with a Convolutional Recurrent Neural Network

AE-Netv2: Optimization of Image Fusion Efficiency and Network Architecture

Learning Visual-Semantic Embeddings for Reporting Abnormal Findings on Chest X-rays

Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification

Theme-Matters: Fashion Compatibility Learning via Theme Attention

A Deep Genetic Programming based Methodology for Art Media Classification Robust to Adversarial Perturbations

Attention-Driven Body Pose Encoding for Human Activity Recognition

Learning Image Labels On-the-fly for Training Robust Classification Models

Answer-Driven Visual State Estimator for Goal-Oriented Visual Dialogue

Can You Trust Your Pose? Confidence Estimation in Visual Localization

Think before you act: A simple baseline for compositional generalization

Deformable Kernel Convolutional Network for Video Extreme Super-Resolution

The Importance of Balanced Data Sets: Analyzing a Vehicle Trajectory Prediction Model based on Neural Networks and Distributed Representations

ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks

EWS-GCN: Edge Weight-Shared Graph Convolutional Network for Transactional Banking Data

Asymmetric Contextual Modulation for Infrared Small Target Detection

MAP-Net: Multi Attending Path Neural Network for Building Footprint Extraction from Remote Sensed Imagery

Pyramidal Edge-maps and Attention based Guided Thermal Super-resolution

AttendNets: Tiny Deep Image Recognition Neural Networks for the Edge via Visual Attention Condensers

ChemoVerse: Manifold traversal of latent spaces for novel molecule discovery

End-to-end Recurrent Multi-Object Tracking and Trajectory Prediction with Relational Reasoning

Multi-scale Receptive Fields Graph Attention Network for Point Cloud Classification

Interpretable Detail-Fidelity Attention Network for Single Image Super-Resolution

Concentrated Multi-Grained Multi-Attention Network for Video Based Person Re-Identification

Heterogeneous Molecular Graph Neural Networks for Predicting Molecule Properties

LFD-ProtoNet: Prototypical Network Based on Local Fisher Discriminant Analysis for Few-shot Learning

Sequence-to-Sequence Load Disaggregation Using Multi-Scale Residual Neural Network

AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

In-sample Contrastive Learning and Consistent Attention for Weakly Supervised Object Localization

Benchmarking Tropical Cyclone Rapid Intensification with Satellite Images and Attention-based Deep Models

Krylov Subspace Method for Nonlinear Dynamical Systems with Random Noise

J$\hat{\text{A}}$A-Net: Joint Facial Action Unit Detection and Face Alignment via Adaptive Attention

Why I'm not Answering: Understanding Determinants of Classification of an Abstaining Classifier for Cancer Pathology Reports

A Simple Yet Effective Method for Video Temporal Grounding with Cross-Modality Attention

MAFF-Net: Filter False Positive for 3D Vehicle Detection with Multi-modal Adaptive Feature Fusion

Exploring global diverse attention via pairwise temporal relation for video summarization

Improving Medical Annotation Quality to Decrease Labeling Burden Using Stratified Noisy Cross-Validation

An embedded deep learning system for augmented reality in firefighting applications

The Use of AI for Thermal Emotion Recognition: A Review of Problems and Limitations in Standard Design and Data

Visual Methods for Sign Language Recognition: A Modality-Based Review

Leveraging Cross Feedback of User and Item Embeddings with Attention for Variational Autoencoder based Collaborative Filtering

Improving Person Re-identification with Iterative Impression Aggregation

A Novel Transferability Attention Neural Network Model for EEG Emotion Recognition

Dual-path CNN with Max Gated block for Text-Based Person Re-identification

Multi-Level Graph Convolutional Network with Automatic Graph Learning for Hyperspectral Image Classification

Image Captioning with Attention for Smart Local Tourism using EfficientNet

COMET: Context-Aware IoU-Guided Network for Small Object Tracking

DeepRemaster: Temporal Source-Reference Attention Networks for Comprehensive Video Enhancement

Deploying machine learning to assist digital humanitarians: making image annotation in OpenStreetMap more efficient

An early prediction of covid-19 associated hospitalization surge using deep learning approach

Diversity Helps: Unsupervised Few-shot Learning via Distribution Shift-based Data Augmentation

LDNet: End-to-End Lane Detection Approach usinga Dynamic Vision Sensor

Malicious Network Traffic Detection via Deep Learning: An Information Theoretic View

ChoreoNet: Towards Music to Dance Synthesis with Choreographic Action Unit

From Design Draft to Real Attire: Unaligned Fashion Image Translation

SGQuant: Squeezing the Last Bit on Graph Neural Networks with Specialized Quantization

Parallax Attention for Unsupervised Stereo Correspondence Learning

PointIso: Point Cloud Based Deep Learning Model for Detecting Arbitrary-Precision Peptide Features in LC-MS Map through Attention Based Segmentation

The Devil is the Classifier: Investigating Long Tail Relation Classification with Decoupling Analysis

Optimal Use of Multi-spectral Satellite Data with Convolutional Neural Networks

How to track your dragon: A Multi-Attentional Framework for real-time RGB-D 6-DOF Object Pose Tracking

Multi-scale Attention U-Net (MsAUNet): A Modified U-Net Architecture for Scene Segmentation

FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping

Attention-SLAM: A Visual Monocular SLAM Learning from Human Gaze

Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism

Hybrid Multiple Attention Network for Semantic Segmentation in Aerial Images

REXUP: I REason, I EXtract, I UPdate with Structured Compositional Reasoning for Visual Question Answering

IntroVAC: Introspective Variational Classifiers for Learning Interpretable Latent Subspaces

Attention-Guided Lightweight Network for Real-Time Segmentation of Robotic Surgical Instruments

Interpretation of smartphone-captured radiographs utilizing a deep learning-based approach

TCDesc: Learning Topology Consistent Descriptors for Image Matching

Few-shot Learning with LSSVM Base Learner and Transductive Modules

Smoothness Sensor: Adaptive Smoothness-Transition Graph Convolutions for Attributed Graph Clustering

A Progressive Sub-Network Searching Framework for Dynamic Inference

Non-contact Real time Eye Gaze Mapping System Based on Deep Convolutional Neural Network

Plant Diseases recognition on images using Convolutional Neural Networks: A Systematic Review

Online trajectory recovery from offline handwritten Japanese kanji characters

Learning Flow-based Feature Warping for Face Frontalization with Illumination Inconsistent Supervision

Temporal Attribute-Appearance Learning Network for Video-based Person Re-Identification

One-shot Text Field Labeling using Attention and Belief Propagation for Structure Information Extraction

PoWER-BERT: Accelerating BERT Inference via Progressive Word-vector Elimination

Interpreting Deep Glucose Predictive Models for Diabetic People Using RETAIN

Approximate Multiplication of Sparse Matrices with Limited Space

High-throughput relation extraction algorithm development associating knowledge articles and electronic health records

Towards Accurate Pixel-wise Object Tracking by Attention Retrieval

Sparse Network Inversion for Key Instance Detection in Multiple Instance Learning

Scaling up Differentially Private Deep Learning with Fast Per-Example Gradient Clipping

Scalar Coupling Constant Prediction Using Graph Embedding Local Attention Encoder

Particle Swarm Optimized Federated Learning For Industrial IoT and Smart City Services

Question Guided Modular Routing Networks for Visual Question Answering

Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis

Trajectory Prediction for Autonomous Driving based on Multi-Head Attention with Joint Agent-Map Representation

Deep Generative Model for Image Inpainting with Local Binary Pattern Learning and Spatial Attention

MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation

Taming Convergence for Asynchronous Stochastic Gradient Descent with Unbounded Delay in Non-Convex Learning

Multimodal Aggregation Approach for Memory Vision-Voice Indoor Navigation with Meta-Learning

A Mathematical Introduction to Generative Adversarial Nets (GAN)

ALANET: Adaptive Latent Attention Network forJoint Video Deblurring and Interpolation

Traffic-Aware Multi-Camera Tracking of Vehicles Based on ReID and Camera Link Model

Quantitative Survey of the State of the Art in Sign Language Recognition

A Free Lunch in Generating Datasets: Building a VQG and VQA System with Attention and Humans in the Loop

KBGN: Knowledge-Bridge Graph Network for Adaptive Vision-Text Reasoning in Visual Dialogue

Counting from Sky: A Large-scale Dataset for Remote Sensing Object Counting and A Benchmark Method

Attentive One-Dimensional Heatmap Regression for Facial Landmark Detection and Tracking

DMD: A Large-Scale Multi-Modal Driver Monitoring Dataset for Attention and Alertness Analysis

Fingerprint Feature Extraction by Combining Texture, Minutiae, and Frequency Spectrum Using Multi-Task CNN

Adaptively-Accumulated Knowledge Transfer for Partial Domain Adaptation

Multi-Label Sentiment Analysis on 100 Languages with Dynamic Weighting for Label Imbalance

Cross-regional oil palm tree counting and detection via multi-level attention domain adaptation network

Uncertainty-Aware Surrogate Model For Oilfield Reservoir Simulation

DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms

Discriminative Cross-Domain Feature Learning for Partial Domain Adaptation

Weakly-Supervised Action Localization with Expectation-Maximization Multi-Instance Learning

FastSal: a Computationally Efficient Network for Visual Saliency Prediction

Using Deep Networks for Scientific Discovery in Physiological Signals

A Critical Analysis of Patch Similarity Based Image Denoising Algorithms

A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-Resolution

Object-Aware Multi-Branch Relation Networks for Spatio-Temporal Video Grounding

A Efficient Multimodal Framework for Large Scale Emotion Recognition by Fusing Music and Electrodermal Activity Signals

Semantic Segmentation and Data Fusion of Microsoft Bing 3D Cities and Small UAV-based Photogrammetric Data

INSIDE: Steering Spatial Attention with Non-Imaging Information in CNNs

Self-Supervised Gait Encoding with Locality-Aware Attention for Person Re-Identification

Searching Multi-Rate and Multi-Modal Temporal Enhanced Networks for Gesture Recognition

Self-Attentive Classification-Based Anomaly Detection in Unstructured Logs

MEANTIME: Mixture of Attention Mechanisms with Multi-temporal Embeddings for Sequential Recommendation

Monocular Expressive Body Regression through Body-Driven Attention

Attention-based Fully Gated CNN-BGRU for Russian Handwritten Text

Co-Saliency Detection with Co-Attention Fully Convolutional Network

Linear Attention Mechanism: An Efficient Attention for Semantic Segmentation

Spatial--spectral FFPNet: Attention-Based Pyramid Network for Segmentation and Classification of Remote Sensing Images

Every Pixel Matters: Center-aware Feature Alignment for Domain Adaptive Object Detector

Black Re-ID: A Head-shoulder Descriptor for the Challenging Problem of Person Re-Identification

Sparse Cholesky covariance parametrization for recovering latent structure in ordered data

Query Twice: Dual Mixture Attention Meta Learning for Video Summarization

Axiom-based Grad-CAM: Towards Accurate Visualization and Explanation of CNNs

Learning Tuple Compatibility for Conditional OutfitRecommendation

AssembleNet++: Assembling Modality Representations via Attention Connections

AB3DMOT: A Baseline for 3D Multi-Object Tracking and New Evaluation Metrics

Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem

Linguistically-aware Attention for Reducing the Semantic-Gap in Vision-Language Tasks

Ensemble Node Embeddings using Tensor Decomposition: A Case-Study on DeepWalk

Investigating maximum likelihood based training of infinite mixtures for uncertainty quantification

Self-Supervised Learning for Monocular Depth Estimation from Aerial Imagery

Give Me Something to Eat: Referring Expression Comprehension with Commonsense Knowledge

DeepGIN: Deep Generative Inpainting Network for Extreme Image Inpainting

Vision-Based Fall Event Detection in Complex Background Using Attention Guided Bi-directional LSTM

Do Not Disturb Me: Person Re-identification Under the Interference of Other Pedestrians

Audio-Visual Event Localization via Recursive Fusion by Joint Co-Attention

AntiDote: Attention-based Dynamic Optimization for Neural Network Runtime Efficiency

Efficient hyperparameter optimization by way of PAC-Bayes bound minimization

GeoLayout: Geometry Driven Room Layout Estimation Based on Depth Maps of Planes

MHSA-Net: Multi-Head Self-Attention Network for Occluded Person Re-Identification

Paying more attention to snapshots of Iterative Pruning: Improving Model Compression via Ensemble Distillation

Hybrid Dynamic-static Context-aware Attention Network for Action Assessment in Long Videos

CAMAL: Context-Aware Multi-layer Attention framework for Lightweight Environment Invariant Visual Place Recognition

DFEW: A Large-Scale Database for Recognizing Dynamic Facial Expressions in the Wild

Alleviating Human-level Shift : A Robust Domain Adaptation Method for Multi-person Pose Estimation

Attention-Guided Discriminative Region Localization and Label Distribution Learning for Bone Age Assessment

Jointly Cross- and Self-Modal Graph Attention Network for Query-Based Moment Localization

Identity-Aware Attribute Recognition via Real-Time Distributed Inference in Mobile Edge Clouds

ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation

Select Good Regions for Deblurring based on Convolutional Neural Networks

Thoracic Disease Identification and Localization using Distance Learning and Region Verification

Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor Scene

Cross-Modal Hierarchical Modelling for Fine-Grained Sketch Based Image Retrieval

Locating Cephalometric X-Ray Landmarks with Foveated Pyramid Attention

SemEval-2020 Task 8: Memotion Analysis -- The Visuo-Lingual Metaphor!

DCA: Diversified Co-Attention towards Informative Live Video Commenting

Unravelling Small Sample Size Problems in the Deep Learning World

Hierarchical Bi-Directional Feature Perception Network for Person Re-Identification

Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation

Geometric Attention for Prediction of Differential Properties in 3D Point Clouds

Gender and Ethnicity Classification based on Palmprint and Palmar Hand Images from Uncontrolled Environment

Fine-grained Iterative Attention Network for TemporalLanguage Localization in Videos

TPG-DNN: A Method for User Intent Prediction Based on Total Probability Formula and GRU Loss with Multi-task Learning

Beyond Controlled Environments: 3D Camera Re-Localization in Changing Indoor Scenes

Component Divide-and-Conquer for Real-World Image Super-Resolution

Weight-Sharing Neural Architecture Search: A Battle to Shrink the Optimization Gap

Cross-Global Attention Graph Kernel Network Prediction of Drug Prescription

From Human Mesenchymal Stromal Cells to Osteosarcoma Cells Classification by Deep Learning

A Machine Learning Approach for Modelling Parking Duration in Urban Land-use

Hyperspectral Image Classification with Spatial Consistence Using Fully Convolutional Spatial Propagation Network

ExchNet: A Unified Hashing Network for Large-Scale Fine-Grained Image Retrieval

Few-shot Action Recognition with Permutation-invariant Attention

NWPU-Crowd: A Large-Scale Benchmark for Crowd Counting and Localization

Mixup-CAM: Weakly-supervised Semantic Segmentation via Uncertainty Regularization

Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss

Weakly-Supervised Semantic Segmentation via Sub-category Exploration

Blind Face Restoration via Deep Multi-scale Component Dictionaries

LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence

Light Field Super-resolution via Attention-Guided Fusion of Hybrid Lenses

Vulnerability Under Adversarial Machine Learning: Bias or Variance?

AttentionNAS: Spatiotemporal Attention Cell Search for Video Classification

Temporal Aggregate Representations for Long-Range Video Understanding

PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings

Split Computing for Complex Object Detectors: Challenges and Preliminary Results

Post-Workshop Report on Science meets Engineering in Deep Learning, NeurIPS 2019, Vancouver

When and why PINNs fail to train: A neural tangent kernel perspective

A Convolutional Neural Network for gaze preference detection: A potential tool for diagnostics of autism spectrum disorder in children

Exploit the potential of Multi-column architecture for Crowd Counting

Stochastic Normalized Gradient Descent with Momentum for Large Batch Training

3D Point Cloud Descriptors in Hand-crafted and Deep Learning Age: State-of-the-Art

U2-ONet: A Two-level Nested Octave U-structure with Multiscale Attention Mechanism for Moving Instances Segmentation

Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks

Landmark Guidance Independent Spatio-channel Attention and Complementary Context Information based Facial Expression Recognition

A global method to identify trees outside of closed-canopy forests with medium-resolution satellite imagery

HEU Emotion: A Large-scale Database for Multi-modal Emotion Recognition in the Wild

Some Limit Properties of Markov Chains Induced by Stochastic Recursive Algorithms

ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation

History Repeats Itself: Human Motion Prediction via Motion Attention

Attention based Multiple Instance Learning for Classification of Blood Cell Disorders

Attend and Segment: Attention Guided Active Semantic Segmentation

Learning Disentangled Feature Representation for Hybrid-distorted Image Restoration

SAG-VAE: End-to-end Joint Inference of Data Representations and Feature Relations

Improving Monocular Depth Estimation by Leveraging Structural Awareness and Complementary Datasets

Self-supervised Feature Learning via Exploiting Multi-modal Data for Retinal Disease Diagnosis

Multi-label Thoracic Disease Image Classification with Cross-Attention Networks

Multi-branch and Multi-scale Attention Learning for Fine-Grained Visual Categorization

Complementing Representation Deficiency in Few-shot Image Classification: A Meta-Learning Approach

Fine-Grained Image Captioning with Global-Local Discriminative Objective

Learning Person Re-identification Models from Videos with Weak Supervision

Tensor Regression Using Low-rank and Sparse Tucker Decompositions

Unified Multisensory Perception: Weakly-Supervised Audio-Visual Video Parsing

Relatable Clothing: Detecting Visual Relationships between People and Clothing

Improving Attention-Based Handwritten Mathematical Expression Recognition with Scale Augmentation and Drop Attention

Attention Sequence to Sequence Model for Machine Remaining Useful Life Prediction

Forecasting Human-Object Interaction: Joint Prediction of Motor Attention and Actions in First Person Video

A Generic Visualization Approach for Convolutional Neural Networks

Unsupervised Domain Attention Adaptation Network for Caricature Attribute Recognition

Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification

Learning to Generate Grounded Visual Captions without Localization Supervision

Efficient Graph Generation with Graph Recurrent Attention Networks

DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization

Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors

A Differential Game Theoretic Neural Optimizer for Training Residual Networks

Cross-Identity Motion Transfer for Arbitrary Objects through Pose-Attentive Video Reassembling

RobustScanner: Dynamically Enhancing Positional Clues for Robust Text Recognition

The Devil is in the Details: Self-Supervised Attention for Vehicle Re-Identification

Prediction of the onset of cardiovascular diseases from electronic health records using multi-task gated recurrent units

Cascade Network with Guided Loss and Hybrid Attention for Two-view Geometry

A-MAL: Automatic Movement Assessment Learning from Properly Performed Movements in 3D Skeleton Videos

Learning Delicate Local Representations for Multi-Person Pose Estimation

Learning Multiplicative Interactions with Bayesian Neural Networks for Visual-Inertial Odometry

Relational Deep Feature Learning for Heterogeneous Face Recognition

JSENet: Joint Semantic Segmentation and Edge Detection Network for 3D Point Clouds

Robust Identifiability in Linear Structural Equation Models of Causal Inference

High-Resolution Image Inpainting with Iterative Confidence Feedback and Guided Upsampling

DA4AD: End-to-End Deep Attention-based Visual Localization for Autonomous Driving

Expert Training: Task Hardness Aware Meta-Learning for Few-Shot Classification

Probabilistic Crowd GAN: Multimodal Pedestrian Trajectory Prediction using a Graph Vehicle-Pedestrian Attention Network

Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?

Applying recent advances in Visual Question Answering to Record Linkage

Generalization of Deep Convolutional Neural Networks -- A Case-study on Open-source Chest Radiographs

Driver Behavior Modelling at the Urban Intersection via Canonical Correlation Analysis

NestFuse: An Infrared and Visible Image Fusion Architecture based on Nest Connection and Spatial/Channel Attention Models

RGCF: Refined Graph Convolution Collaborative Filtering with concise and expressive embedding

Learning Accurate and Human-Like Driving using Semantic Maps and Attention

Fair comparison of skin detection approaches on publicly available datasets

Affine Non-negative Collaborative Representation Based Pattern Classification

DCANet: Learning Connected Attentions for Convolutional Neural Networks

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation

Dual-attention Guided Dropblock Module for Weakly Supervised Object Localization

Alleviating the Burden of Labeling: Sentence Generation by Attention Branch Encoder-Decoder Network

Attention-based Residual Speech Portrait Model for Speech to Face Generation

Multi-view Drone-based Geo-localization via Style and Spatial Alignment

Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets

Learning Enriched Features for Real Image Restoration and Enhancement

Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentation

DAM: Deliberation, Abandon and Memory Networks for Generating Detailed and Non-repetitive Responses in Visual Dialogue

Pix2Vox++: Multi-scale Context-aware 3D Object Reconstruction from Single and Multiple Images

Decoupled Spatial-Temporal Attention Network for Skeleton-Based Action Recognition

VPN: Learning Video-Pose Embedding for Activities of Daily Living

Traffic Agent Trajectory Prediction Using Social Convolution and Attention Mechanism

Tree-Augmented Cross-Modal Encoding for Complex-Query Video Retrieval

Automatically Generating Codes from Graphical Screenshots Based on Deep Autocoder

Wind speed prediction using multidimensional convolutional neural networks

Multi-Head Attention based Probabilistic Vehicle Trajectory Prediction

Modality Shifting Attention Network for Multi-modal Video Question Answering

Egocentric Action Recognition by Video Attention and Temporal Context

Image-based Vehicle Re-identification Model with Adaptive Attention Modules and Metadata Re-ranking

AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction

Balanced Symmetric Cross Entropy for Large Scale Imbalanced and Noisy Data

Deep Learning for Image Search and Retrieval in Large Remote Sensing Archives

DeepFakes Evolution: Analysis of Facial Regions and Fake Detection Performance

Estimating Blink Probability for Highlight Detection in Figure Skating Videos

Attention-Oriented Action Recognition for Real-Time Human-Robot Interaction

Channel Compression: Rethinking Information Redundancy among Channels in CNN Architecture

M3d-CAM: A PyTorch library to generate 3D data attention maps for medical deep learning

Using Human Psychophysics to Evaluate Generalization in Scene Text Recognition Models

Classification of cancer pathology reports: a large-scale comparative study

A Survey on Deep Learning for Localization and Mapping: Towards the Age of Spatial Machine Intelligence

MILA: Multi-Task Learning from Videos via Efficient Inter-Frame Local Attention

Many-Class Few-Shot Learning on Multi-Granularity Class Hierarchy

Weak Supervision and Referring Attention for Temporal-Textual Association Learning

ULSAM: Ultra-Lightweight Subspace Attention Module for Compact Convolutional Neural Networks

Dynamically Mitigating Data Discrepancy with Balanced Focal Loss for Replay Attack Detection

PropagationNet: Propagate Points to Curve to Learn Structure Information

Multimodal grid features and cell pointers for Scene Text Visual Question Answering

Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation

Domain Decluttering: Simplifying Images to Mitigate Synthetic-Real Domain Shift and Improve Depth Estimation

On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools

FBK-HUPBA Submission to the EPIC-Kitchens Action Recognition 2020 Challenge

Robust Domain Adaptation: Representations, Weights and Inductive Bias

IA-MOT: Instance-Aware Multi-Object Tracking with Motion Consistency

Principled learning method for Wasserstein distributionally robust optimization with local perturbations

Feature Alignment and Restoration for Domain Generalization and Adaptation

MultiImport: Inferring Node Importance in a Knowledge Graph from Multiple Input Signals

A Cross-Modal Image Fusion Method Guided by Human Visual Characteristics

Self-Attention Enhanced Patient Journey Understanding in Healthcare System

A Simple and Effective Framework for Pairwise Deep Metric Learning

Automated Radiological Report Generation For Chest X-Rays With Weakly-Supervised End-to-End Deep Learning

Cascaded Regression Tracking: Towards Online Hard Distractor Discrimination

Shallow Feature Based Dense Attention Network for Crowd Counting

Analysing Risk of Coronary Heart Disease through Discriminative Neural Networks

Revealing the Invisible with Model and Data Shrinking for Composite-database Micro-expression Recognition

Cross-Correlated Attention Networks for Person Re-Identification

Mining Label Distribution Drift in Unsupervised Domain Adaptation

SQuINTing at VQA Models: Introspecting VQA Models with Sub-Questions

Focus of Attention Improves Information Transfer in Visual Features

Learning to Solve Vehicle Routing Problems with Time Windows through Joint Attention

COMPOSE: Cross-Modal Pseudo-Siamese Network for Patient Trial Matching

Deep Multi-attributed Graph Translation with Node-Edge Co-evolution

ORD: Object Relationship Discovery for Visual Dialogue Generation

Survey on Deep Multi-modal Data Analytics: Collaboration, Rivalry and Fusion

Sensorless Freehand 3D Ultrasound Reconstruction via Deep Contextual Learning

Uncertainty-aware Score Distribution Learning for Action Quality Assessment

Learning scale-variant features for robust iris authentication with deep learning based ensemble framework

Attribute-aware Identity-hard Triplet Loss for Video-based Person Re-identification

Learning from the Scene and Borrowing from the Rich: Tackling the Long Tail in Scene Graph Generation

Understanding the Role of Training Regimes in Continual Learning

On Improving the Generalization of Face Recognition in the Presence of Occlusions

Exploring Category-Agnostic Clusters for Open-Set Domain Adaptation

Single Image Deraining via Scale-space Invariant Attention Neural Network

Towards Robust Fine-grained Recognition by Maximal Separation of Discriminative Features

Embedding Task Knowledge into 3D Neural Networks via Self-supervised Learning

Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification

A Machine Learning Early Warning System: Multicenter Validation in Brazilian Hospitals

Breaking the Limits of Remote Sensing by Simulation and Deep Learning for Flood and Debris Flow Mapping

Learning Shared Cross-modality Representation Using Multispectral-LiDAR and Hyperspectral Data

Distributional Robustness with IPMs and links to Regularization and GANs

SDCT-AuxNet$^θ$: DCT Augmented Stain Deconvolutional CNN with Auxiliary Classifier for Cancer Diagnosis

Towards Assessment of Randomized Smoothing Mechanisms for Certifying Adversarial Robustness

DAugNet: Unsupervised, Multi-source, Multi-target, and Life-long Domain Adaptation for Semantic Segmentation of Satellite Images

FMA-ETA: Estimating Travel Time Entirely Based on FFN With Attention

Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition

Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning to End

Multi-modal Feature Fusion with Feature Attention for VATEX Captioning Challenge 2020

A Computational Model of Early Word Learning from the Infant's Point of View

Channel Distillation: Channel-Wise Attention for Knowledge Distillation

Channel Attention based Iterative Residual Learning for Depth Map Super-Resolution

Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining

From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models

A multimodal approach for multi-label movie genre classification

Pedestrian Tracking with Gated Recurrent Units and Attention Mechanisms

A General-Purpose Dehazing Algorithm based on Local Contrast Enhancement Approaches

AP-MTL: Attention Pruned Multi-task Learning Model for Real-time Instrument Detection and Segmentation in Robot-assisted Surgery

Attribute-Induced Bias Eliminating for Transductive Zero-Shot Learning

Challenge report: Recognizing Families In the Wild Data Challenge

Exploration of Input Patterns for Enhancing the Performance of Liquid State Machines

CASTNet: Community-Attentive Spatio-Temporal Networks for Opioid Overdose Forecasting

Vispi: Automatic Visual Perception and Interpretation of Chest X-rays

Self-Attention Dense Depth Estimation Network for Unrectified Video Sequences

Combining Fine- and Coarse-Grained Classifiers for Diabetic Retinopathy Detection

Robust Encoder-Decoder Learning Framework towards Offline Handwritten Mathematical Expression Recognition Based on Multi-Scale Deep Neural Network

Stereo Vision Based Single-Shot 6D Object Pose Estimation for Bin-Picking by a Robot Manipulator

Attention-based Neural Bag-of-Features Learning for Sequence Data

Deep Convolutional Neural Network-based Bernoulli Heatmap for Head Pose Estimation

Stacked Bidirectional and Unidirectional LSTM Recurrent Neural Network for Forecasting Network-wide Traffic State with Missing Values

Investigating Vulnerability to Adversarial Examples on Multimodal Data Fusion in Deep Learning

Focus Longer to See Better:Recursively Refined Attention for Fine-Grained Image Classification

BARNet: Bilinear Attention Network with Adaptive Receptive Fields for Surgical Instrument Segmentation

Nonconvex Rectangular Matrix Completion via Gradient Descent without $\ell_{2,\infty}$ Regularization

Dual-Sampling Attention Network for Diagnosis of COVID-19 from Community Acquired Pneumonia

Deep Learning Guided Building Reconstruction from Satellite Imagery-derived Point Clouds

Large Margin Mechanism and Pseudo Query Set on Cross-Domain Few-Shot Learning

Point Cloud Completion by Skip-attention Network with Hierarchical Folding

Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings

CATA++: A Collaborative Dual Attentive Autoencoder Method for Recommending Scientific Articles

Simultaneous imputation and disease classification in incomplete medical datasets using Multigraph Geometric Matrix Completion (MGMC)

Surrogate-assisted parallel tempering for Bayesian neural learning

Pose Proposal Critic: Robust Pose Refinement by Learning Reprojection Errors

Multiple Attentional Pyramid Networks for Chinese Herbal Recognition

Arbitrary Talking Face Generation via Attentional Audio-Visual Coherence Learning

Occlusion-Adaptive Deep Network for Robust Facial Expression Recognition

AttViz: Online exploration of self-attention for transparent neural language modeling

GoGNN: Graph of Graphs Neural Network for Predicting Structured Entity Interactions

Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence

Towards Utilizing Unlabeled Data in Federated Learning: A Survey and Prospective

Co-Saliency Spatio-Temporal Interaction Network for Person Re-Identification in Videos

Synetgy: Algorithm-hardware Co-design for ConvNet Accelerators on Embedded FPGAs

Attentional Bottleneck: Towards an Interpretable Deep Driving Network

An Effective Dynamic Spatio-temporal Framework with Multi-Source Information for Traffic Prediction

Efficient Computation Reduction in Bayesian Neural Networks Through Feature Decomposition and Memorization

Comparison and Benchmarking of AI Models and Frameworks on Mobile Devices

Toward Improving the Evaluation of Visual Attention Models: a Crowdsourcing Approach

SCAttNet: Semantic Segmentation Network with Spatial and Channel Attention Mechanism for High-Resolution Remote Sensing Images

Warwick Image Forensics Dataset for Device Fingerprinting In Multimedia Forensics

End-to-End Domain Adaptive Attention Network for Cross-Domain Person Re-Identification

Forecasting future action sequences with attention: a new approach to weakly supervised action forecasting

One-step regression and classification with crosspoint resistive memory arrays

Comparing SNNs and RNNs on Neuromorphic Vision Datasets: Similarities and Differences

PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data

To Reduce Gross NPA and Classify Defaulters Using Shannon Entropy

Metric learning by Similarity Network for Deep Semi-Supervised Learning

Domain Adaptive Transfer Attack (DATA)-based Segmentation Networks for Building Extraction from Aerial Images

Deep convolutional neural networks for face and iris presentation attack detection: Survey and case study

Schoenberg-Rao distances: Entropy-based and geometry-aware statistical Hilbert distances

Deep Auto-Encoders with Sequential Learning for Multimodal Dimensional Emotion Recognition

Self-Supervised Attention Learning for Depth and Ego-motion Estimation

PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation

Taking Care of The Discretization Problem: A Comprehensive Study of the Discretization Problem and A Black-Box Adversarial Attack in Discrete Integer Domain

Deep Interleaved Network for Image Super-Resolution With Asymmetric Co-Attention

What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation

Self-Constructing Graph Convolutional Networks for Semantic Labeling

Attentive Modality Hopping Mechanism for Speech Emotion Recognition

TCNN: Triple Convolutional Neural Network Models for Retrieval-based Question Answering System in E-commerce

Group Activity Detection from Trajectory and Video Data in Soccer

Airborne LiDAR Point Cloud Classification with Graph Attention Convolution Neural Network

MER-GCN: Micro Expression Recognition Based on Relation Modeling with Graph Convolutional Network

A Review on Object Pose Recovery: from 3D Bounding Box Detectors to Full 6D Pose Estimators

Are we pretraining it right? Digging deeper into visio-linguistic pretraining

Example-Guided Image Synthesis across Arbitrary Scenes using Masked Spatial-Channel Attention and Self-Supervision

Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features

Dynamic Feature Integration for Simultaneous Detection of Salient Object, Edge and Skeleton

An integrated light management system with real-time light measurement and human perception

Attention-based Multi-modal Fusion Network for Semantic Scene Completion

An Evaluation of DNN Architectures for Page Segmentation of Historical Newspapers

Contextual Pyramid Attention Network for Building Segmentation in Aerial Imagery

Combining Visible Light and Infrared Imaging for Efficient Detection of Respiratory Infections such as COVID-19 on Portable Device

PDANet: Pyramid Density-aware Attention Net for Accurate Crowd Counting

An Attention-Based System for Damage Assessment Using Satellite Imagery

Deep Entwined Learning Head Pose and Face Alignment Inside an Attentional Cascade with Doubly-Conditional fusion

Estimation of Classification Rules from Partially Classified Data

Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks

MLPSVM:A new parallel support vector machine to multi-label learning

Pyramid Focusing Network for mutation prediction and classification in CT images

Spatially-Attentive Patch-Hierarchical Network for Adaptive Motion Deblurring

Parsing-based View-aware Embedding Network for Vehicle Re-Identification

Domain-aware Visual Bias Eliminating for Generalized Zero-Shot Learning

Training few-shot classification via the perspective of minibatch and pretraining

HopGAT: Hop-aware Supervision Graph Attention Networks for Sparsely Labeled Graphs

Beyond Disentangled Representations: An Attentive Angular Distillation Approach to Large-scale Lightweight Age-Invariant Face Recognition

Weakly Supervised Semantic Point Cloud Segmentation:Towards 10X Fewer Labels

U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation

Context-Aware Group Captioning via Self-Attention and Contrastive Features

pAElla: Edge-AI based Real-Time Malware Detection in Data Centers

Multi-Task Learning via Co-Attentive Sharing for Pedestrian Attribute Recognition

Predicting Camera Viewpoint Improves Cross-dataset Generalization for 3D Human Pose Estimation

Cars Can't Fly up in the Sky: Improving Urban-Scene Segmentation via Height-driven Attention Networks

ReADS: A Rectified Attentional Double Supervised Network for Scene Text Recognition

Temporally Distributed Networks for Fast Video Semantic Segmentation

Manifold-driven Attention Maps for Weakly Supervised Segmentation

Network Adjustment: Channel Search Guided by FLOPs Utilization Ratio

The perceptual boost of visual attention is task-dependent in naturalistic settings

Forecast Network-Wide Traffic States for Multiple Steps Ahead: A Deep Learning Approach Considering Dynamic Non-Local Spatial Correlation and Non-Stationary Temporal Dependency

MNEW: Multi-domain Neighborhood Embedding and Weighting for Sparse Point Clouds Segmentation

Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification

FAIRS -- Soft Focus Generator and Attention for Robust Object Segmentation from Extreme Points

Granular Computing: An Augmented Scheme of Degranulation Through a Modified Partition Matrix

A Unified Object Motion and Affinity Model for Online Multi-Object Tracking

Knowing What, Where and When to Look: Efficient Video Action Modeling with Attention

An Attention-Based Deep Learning Model for Multiple Pedestrian Attributes Recognition

MCEN: Bridging Cross-Modal Gap between Cooking Recipes and Dish Images with Latent Variable Model

MineGAN: effective knowledge transfer from GANs to target domains with few images

Drug-disease Graph: Predicting Adverse Drug Reaction Signals via Graph Neural Network with Clinical Data

More Grounded Image Captioning by Distilling Image-Text Matching Model

Creating Something from Nothing: Unsupervised Knowledge Distillation for Cross-Modal Hashing

Looking at the right stuff: Guided semantic-gaze for autonomous driving

Self-supervised Monocular Trained Depth Estimation using Self-attention and Discrete Disparity Volume

Weakly-Supervised Action Localization by Generative Attention Modeling

Disturbance-immune Weight Sharing for Neural Architecture Search

Deep Face Super-Resolution with Iterative Collaboration between Attentive Recovery and Landmark Estimation

Multi-Path Region Mining For Weakly Supervised 3D Semantic Segmentation on Point Clouds

LAMP-HQ: A Large-Scale Multi-Pose High-Quality Database and Benchmark for NIR-VIS Face Recognition

Multi-Scale Progressive Fusion Network for Single Image Deraining

Infant brain MRI segmentation with dilated convolution pyramid downsampling and self-attention

Towards Accurate Scene Text Recognition with Semantic Reasoning Networks

Cross-Modality Attention with Semantic Graph Embedding for Multi-Label Classification

Multi-Granularity Reference-Aided Attentive Feature Aggregation for Video-based Person Re-identification

A New Gene Selection Algorithm using Fuzzy-Rough Set Theory for Tumor Classification

Training Binary Neural Networks with Real-to-Binary Convolutions

Towards Train-Test Consistency for Semi-supervised Temporal Action Localization

Deep learning with noisy labels: exploring techniques and remedies in medical image analysis

Predicting Diabetes Disease Evolution Using Financial Records and Recurrent Neural Networks

Testing and verification of neural-network-based safety-critical control software: A systematic literature review

Joint Event Extraction along Shortest Dependency Paths using Graph Convolutional Networks

Agriculture-Vision: A Large Aerial Image Database for Agricultural Pattern Analysis

PIC: Permutation Invariant Convolution for Recognizing Long-range Activities

MagicEyes: A Large Scale Eye Gaze Estimation Dataset for Mixed Reality

Transferring Cross-domain Knowledge for Video Sign Language Recognition

Geometric Approaches to Increase the Expressivity of Deep Neural Networks for MR Reconstruction

M$^5$L: Multi-Modal Multi-Margin Metric Learning for RGBT Tracking

A comprehensive study on the prediction reliability of graph neural networks for virtual screening

Feedback Graph Convolutional Network for Skeleton-based Action Recognition

Augmented Parallel-Pyramid Net for Attention Guided Pose-Estimation

Looking Ahead: Anticipating Pedestrians Crossing with Future Frames Prediction

SeqXY2SeqZ: Structure Learning for 3D Shapes by Sequentially Predicting 1D Occupancy Segments From 2D Coordinates

End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds

Constructing Gradient Controllable Recurrent Neural Networks Using Hamiltonian Dynamics

Weakly-Supervised Multi-Level Attentional Reconstruction Network for Grounding Textual Queries in Videos

A Spatial-Temporal Attentive Network with Spatial Continuity for Trajectory Prediction

EmotiCon: Context-Aware Multimodal Emotion Recognition using Frege's Principle

TAFSSL: Task-Adaptive Feature Sub-Space Learning for few-shot classification

Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detection

Inference, Learning and Attention Mechanisms that Exploit and Preserve Sparsity in Convolutional Networks

Learning with Sets in Multiple Instance Regression Applied to Remote Sensing

Privacy Preserving Point-of-interest Recommendation Using Decentralized Matrix Factorization

VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutions

Multi-Stream Networks and Ground-Truth Generation for Crowd Counting

Bi-Directional Attention for Joint Instance and Semantic Segmentation in Point Clouds

Context-aware Non-linear and Neural Attentive Knowledge-based Models for Grade Prediction

Composition of kernel and acquisition functions for High Dimensional Bayesian Optimization

Searching Central Difference Convolutional Networks for Face Anti-Spoofing

MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification

ROSE: Real One-Stage Effort to Detect the Fingerprint Singular Point Based on Multi-scale Spatial Attention

IMRAM: Iterative Matching with Recurrent Attention Memory for Cross-Modal Image-Text Retrieval

AlphaNet: An Attention Guided Deep Network for Automatic Image Matting

MVC-Net: A Convolutional Neural Network Architecture for Manifold-Valued Images With Applications

D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features

Suppressing Uncertainties for Large-Scale Facial Expression Recognition

GeoConv: Geodesic Guided Convolution for Facial Action Unit Recognition

Semi-supervised Learning Meets Factorization: Learning to Recommend with Chain Graph Model

VESR-Net: The Winning Solution to Youku Video Enhancement and Super-Resolution Challenge

Novel Meta-Heuristic Model for Discrimination between Iron Deficiency Anemia and B-Thalassemia with CBC Indices Based on Dynamic Harmony Search

Understanding Contexts Inside Robot and Human Manipulation Tasks through a Vision-Language Model and Ontology System in a Video Stream

Benefits of Jointly Training Autoencoders: An Improved Neural Tangent Kernel Analysis

A-TVSNet: Aggregated Two-View Stereo Network for Multi-View Stereo Depth Estimation

Uncertainty-Gated Stochastic Sequential Model for EHR Mortality Prediction

SimGNN: A Neural Network Approach to Fast Graph Similarity Computation

Deep Attention Aware Feature Learning for Person Re-Identification

Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning

Deep differentiable forest with sparse attention for the tabular data

Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices

On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning

Infrared and 3D skeleton feature fusion for RGB-D action recognition

MANet: Multimodal Attention Network based Point- View fusion for 3D Shape Recognition

Heterogeneous Graph Neural Networks for Malicious Account Detection

Multiple Discrimination and Pairwise CNN for View-based 3D Object Retrieval

Transferring Robustness for Graph Neural Network Against Poisoning Attacks

Adversarial Attack on Deep Product Quantization Network for Image Retrieval

Modelling response to trypophobia trigger using intermediate layers of ImageNet networks

DDet: Dual-path Dynamic Enhancement Network for Real-World Image Super-Resolution

ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network

Context-Integrated and Feature-Refined Network for Lightweight Object Parsing

Learning Attentive Pairwise Interaction for Fine-Grained Classification

PDA: Progressive Data Augmentation for General Robustness of Deep Neural Networks

See, Attend and Brake: An Attention-based Saliency Map Prediction Model for End-to-End Driving

Improving the Harmony of the Composite Image by Spatial-Separated Attention Module

Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction

HMS-Net: Hierarchical Multi-scale Sparsity-invariant Network for Sparse Depth Completion

Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations

Stroke Constrained Attention Network for Online Handwritten Mathematical Expression Recognition

Expressing Objects just like Words: Recurrent Visual Embedding for Image-Text Matching

MADAN: Multi-source Adversarial Domain Aggregation Network for Domain Adaptation

DeFraudNet:End2End Fingerprint Spoof Detection using Patch Level Attention

Analysis Of Multi Field Of View Cnn And Attention Cnn On H&E Stained Whole-slide Images On Hepatocellular Carcinoma

Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent

PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization

Spatiotemporal Tile-based Attention-guided LSTMs for Traffic Video Prediction

Deep Multi-task Prediction of Lung Cancer and Cancer-free Progression from Censored Heterogenous Clinical Imaging

Video Question Generation via Cross-Modal Self-Attention Networks Learning

Block Annotation: Better Image Annotation for Semantic Segmentation with Sub-Image Decomposition

Breast Cancer Histopathology Image Classification and Localization using Multiple Instance Learning

Prior-Knowledge and Attention-based Meta-Learning for Few-Shot Learning

Convolutional Hierarchical Attention Network for Query-Focused Video Summarization

Social-WaGDAT: Interaction-aware Trajectory Prediction via Wasserstein Graph Double-Attention Network

GSANet: Semantic Segmentation with Global and Selective Attention

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides

Chaotic Phase Synchronization and Desynchronization in an Oscillator Network for Object Selection

Recurrent Attention Model with Log-Polar Mapping is Robust against Adversarial Attacks

An End-to-End Visual-Audio Attention Network for Emotion Recognition in User-Generated Videos

Deep Multi-Task Augmented Feature Learning via Hierarchical Graph Neural Network

Learning to Incorporate Structure Knowledge for Image Inpainting

Firearm Detection and Segmentation Using an Ensemble of Semantic Neural Networks

Upper, Middle and Lower Region Learning for Facial Action Unit Detection

Deep Multi-task Multi-label CNN for Effective Facial Attribute Classification

A New Perspective for Flexible Feature Gathering in Scene Text Recognition Via Character Anchor Pooling

Weakly Supervised Attention Pyramid Convolutional Neural Network for Fine-Grained Visual Classification

Ensemble of Deep Convolutional Neural Networks for Automatic Pavement Crack Detection and Measurement

A General Scoring Rule for Randomized Kernel Approximation with Application to Canonical Correlation Analysis

MGpi: A Computational Model of Multiagent Group Perception and Interaction

iqiyi Submission to ActivityNet Challenge 2019 Kinetics-700 challenge: Hierarchical Group-wise Attention

DS-PASS: Detail-Sensitive Panoramic Annular Semantic Segmentation through SwaftNet for Surrounding Sensing

Fine-Grained Fashion Similarity Learning by Attribute-Specific Embedding Network

Memory-Efficient Hierarchical Neural Architecture Search for Image Denoising

Looking GLAMORous: Vehicle Re-Id in Heterogeneous Cameras Networks with Global and Local Attention

Faster On-Device Training Using New Federated Momentum Algorithm

Melanoma detection with electrical impedance spectroscopy and dermoscopy using joint deep learning models

GTC: Guided Training of CTC Towards Efficient and Accurate Scene Text Recognition

Selective Convolutional Network: An Efficient Object Detector with Ignoring Background

A Neural Network-Based On-device Learning Anomaly Detector for Edge Devices

DASNet: Reducing Pixel-level Annotations for Instance and Semantic Segmentation

Lossless Attention in Convolutional Networks for Facial Expression Recognition in the Wild

Depth Based Semantic Scene Completion with Position Importance Aware Loss

Developing a gender classification approach in human face images using modified local binary patterns and tani-moto based nearest neighbor algorithm

Understanding and Robustifying Differentiable Architecture Search

Modeling Winner-Take-All Competition in Sparse Binary Projections

Estimating Aggregate Properties In Relational Networks With Unobserved Data

Detection of Thin Boundaries between Different Types of Anomalies in Outlier Detection using Enhanced Neural Networks

6D Object Pose Regression via Supervised Learning on Point Clouds

Small, Accurate, and Fast Vehicle Re-ID on the Edge: the SAFR Approach

Progressive Local Filter Pruning for Image Retrieval Acceleration

Weakly-Supervised Lesion Segmentation on CT Scans using Co-Segmentation

Discovering Salient Anatomical Landmarks by Predicting Human Gaze

Graph-Bert: Only Attention is Needed for Learning Graph Representations

Zeroth-Order Algorithms for Nonconvex Minimax Problems with Improved Complexities

What and Where to Translate: Local Mask-based Image-to-Image Translation

VMRFANet:View-Specific Multi-Receptive Field Attention Network for Person Re-identification

Spectral Pyramid Graph Attention Network for Hyperspectral Image Classification

Accuracy vs. Complexity: A Trade-off in Visual Question Answering Models

Adaptive Dithering Using Curved Markov-Gaussian Noise in the Quantized Domain for Mapping SDR to HDR Image

DeepTIO: A Deep Thermal-Inertial Odometry with Visual Hallucination

See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks

Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks

Graph Attentional Autoencoder for Anticancer Hyperfood Prediction

A Two-Stream Meticulous Processing Network for Retinal Vessel Segmentation

Event Recognition with Automatic Album Detection based on Sequential Processing, Neural Attention and Image Captioning

Automated Anonymisation of Visual and Audio Data in Classroom Studies

High--Dimensional Brain in a High-Dimensional World: Blessing of Dimensionality

ECGadv: Generating Adversarial Electrocardiogram to Misguide Arrhythmia Classification System

Saliency Guided Self-attention Network for Weakly and Semi-supervised Semantic Segmentation

MHSAN: Multi-Head Self-Attention Network for Visual Semantic Embedding

On the Relationship between Self-Attention and Convolutional Layers

TAB-VCR: Tags and Attributes based Visual Commonsense Reasoning Baselines

Differentially Private Distributed Data Summarization under Covariate Shift

Band Selection from Hyperspectral Images Using Attention-based Convolutional Neural Networks

Control What You Can: Intrinsically Motivated Task-Planning Agent

Weighted Bilinear Coding over Salient Body Parts for Person Re-identification

Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk

Deeper Insights into Weight Sharing in Neural Architecture Search

FACLSTM: ConvLSTM with Focused Attention for Scene Text Recognition

Spatio-Temporal Relation and Attention Learning for Facial Action Unit Detection

Res3ATN -- Deep 3D Residual Attention Network for Hand Gesture Recognition in Videos

Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data

Large Batch Optimization for Deep Learning: Training BERT in 76 minutes

Ultrafast Video Attention Prediction with Coupled Knowledge Distillation

Learning Reinforced Attentional Representation for End-to-End Visual Tracking

Multi-lane Detection Using Instance Segmentation and Attentive Voting

Understanding Architectures Learnt by Cell-based Neural Architecture Search

Ensemble emotion recognizing with multiple modal physiological signals

A Coarse-to-Fine Adaptive Network for Appearance-Based Gaze Estimation

TextScanner: Reading Characters in Order for Robust Scene Text Recognition

SelectFusion: A Generic Framework to Selectively Learn Multisensory Fusion

Siamese Attentional Keypoint Network for High Performance Visual Tracking

A 3D-Deep-Learning-based Augmented Reality Calibration Method for Robotic Environments using Depth Sensor Data

Academic Performance Estimation with Attention-based Graph Convolutional Networks

Feature-Attention Graph Convolutional Networks for Noise Resilient Learning

Multi-Modal Attention-based Fusion Model for Semantic Segmentation of RGB-Depth Images

Ranking and Classification driven Feature Learning for Person Re_identification

Exploring Object Relation in Mean Teacher for Cross-Domain Detection

Focusing and Diffusion: Bidirectional Attentive Graph Convolutional Networks for Skeleton-based Action Recognition

Cross-Modal Image Fusion Theory Guided by Subjective Visual Attention

Learning Dynamics of Attention: Human Prior for Interpretable Machine Reasoning

Transductive Zero-Shot Learning for 3D Point Cloud Classification

Hierarchical Target-Attentive Diagnosis Prediction in Heterogeneous Information Networks

Bringing Giant Neural Networks Down to Earth with Unlabeled Data

Multi-Head Attention for Multi-Modal Joint Vehicle Motion Forecasting

Gaussian Process Latent Variable Model Factorization for Context-aware Recommender Systems

Combinational Class Activation Maps for Weakly Supervised Object Localization

Embedding Human Knowledge into Deep Neural Network via Attention Map

AANet: Attribute Attention Network for Person Re-Identifications

Model Weight Theft With Just Noise Inputs: The Curious Case of the Petulant Attacker

Deep Connectomics Networks: Neural Network Architectures Inspired by Neuronal Networks

Attention-Based Face AntiSpoofing of RGB Images, using a Minimal End-2-End Neural Network

One-Stage Inpainting with Bilateral Attention and Pyramid Filling Block

DADA: A Large-scale Benchmark and Model for Driver Attention Prediction in Accidental Scenarios

Self-Attention Network for Skeleton-based Human Action Recognition

CoulGAT: An Experiment on Interpretability of Graph Attention Networks

Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions

Shape and Margin-Aware Lung Nodule Classification in Low-dose CT Images via Soft Activation Mapping

MVP-Net: Multi-view FPN with Position-aware Attention for Deep Universal Lesion Detection

Latent Complete Row Space Recovery for Multi-view Subspace Clustering

Internal-transfer Weighting of Multi-task Learning for Lung Cancer Detection

Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional Networks

Gated-Dilated Networks for Lung Nodule Classification in CT scans

Aff-Wild2: Extending the Aff-Wild Database for Affect Recognition

A Self Validation Network for Object-Level Human Attention Estimation

Recurrently Exploring Class-wise Attention in A Hybrid Convolutional and Bidirectional LSTM Network for Multi-label Aerial Image Classification

CDPM: Convolutional Deformable Part Models for Semantically Aligned Person Re-identification

A Feasible Framework for Arbitrary-Shaped Scene Text Recognition

CCCNet: An Attention Based Deep Learning Framework for Categorized Crowd Counting

Detection of Collision-Prone Vehicle Behavior at Intersections using Siamese Interaction LSTM

ATZSL: Defensive Zero-Shot Recognition in the Presence of Adversaries

A Stochastic Large-scale Machine Learning Algorithm for Distributed Features and Observations

Graph-augmented Convolutional Networks on Drug-Drug Interactions Prediction

A Real-time Global Inference Network for One-stage Referring Expression Comprehension

Saccader: Improving Accuracy of Hard Attention Models for Vision

What Do You Mean I'm Funny? Personalizing the Joke Skill of a Voice-Controlled Virtual Assistant

Methods and open-source toolkit for analyzing and visualizing challenge results

E2-Capsule Neural Networks for Facial Expression Recognition Using AU-Aware Attention

FFA-Net: Feature Fusion Attention Network for Single Image Dehazing

Why Should we Combine Training and Post-Training Methods for Out-of-Distribution Detection?

Towards Robust Image Classification Using Sequential Attention Models

Beyond Visual Semantics: Exploring the Role of Scene Text in Image Understanding

Algorithmic Discrimination: Formulation and Exploration in Deep Learning-based Face Biometrics

Drone-based Joint Density Map Estimation, Localization and Tracking with Space-Time Multi-Scale Attention Network

Deep Metric Learning by Online Soft Mining and Class-Aware Attention

Recognition of Images of Korean Characters Using Embedded Networks

Efficient Relaxed Gradient Support Pursuit for Sparsity Constrained Non-convex Optimization

CNNs, LSTMs, and Attention Networks for Pathology Detection in Medical Data

Skeleton based Activity Recognition by Fusing Part-wise Spatio-temporal and Attention Driven Residues

Semantic-Guided Multi-Attention Localization for Zero-Shot Learning

Fast Stochastic Ordinal Embedding with Variance Reduction and Adaptive Step Size

Understanding Goal-Oriented Active Learning via Influence Functions

Attended End-to-end Architecture for Age Estimation from Facial Expression Videos

Disentanglement Challenge: From Regularization to Reconstruction

Expressive power of tensor-network factorizations for probabilistic modeling, with applications from hidden Markov models to quantum machine learning

Echo: Compiler-based GPU Memory Footprint Reduction for LSTM RNN Training

Understand Dynamic Regret with Switching Cost for Online Decision Making

Gated Convolutional Networks with Hybrid Connectivity for Image Classification

Rethinking Temporal Fusion for Video-based Person Re-identification on Semantic and Time Aspect

Action Recognition via Pose-Based Graph Convolutional Networks with Intermediate Dense Supervision

On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models

Social Attention for Autonomous Decision-Making in Dense Traffic

ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context

Example-Guided Scene Image Synthesis using Masked Spatial-Channel Attention and Patch-Based Self-Supervision

AdaSample: Adaptive Sampling of Hard Positives for Descriptor Learning

Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting

Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing

Methods of Weighted Combination for Text Field Recognition in a Video Stream

AdapNet: Adaptability Decomposing Encoder-Decoder Network for Weakly Supervised Action Recognition and Localization

Pose-Guided Multi-Granularity Attention Network for Text-Based Person Search

Calibrated Domain-Invariant Learning for Highly Generalizable Large Scale Re-Identification

PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer

Distraction-Aware Feature Learning for Human Attribute Recognition via Coarse-to-Fine Attention Mechanism

Deep Image Deraining Via Intrinsic Rainy Image Priors and Multi-scale Auxiliary Decoding

Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation

Neural Storyboard Artist: Visualizing Stories with Coherent Image Sequences

Recurrent Neural Networks (RNNs): A gentle Introduction and Overview

Locality Constraint Dictionary Learning with Support Vector for Pattern Classification

Characterizing the impact of using features extracted from pre-trained models on the quality of video captioning sequence-to-sequence models

PAG-Net: Progressive Attention Guided Depth Super-resolution Network

SCR-Graph: Spatial-Causal Relationships based Graph Reasoning Network for Human Action Prediction

Synaptic Partner Assignment Using Attentional Voxel Association Networks

Unified Multifaceted Feature Learning for Person Re-Identification

Discriminative and Robust Online Learning for Siamese Visual Tracking

FLNet: Landmark Driven Fetching and Learning Network for Faithful Talking Facial Animation Synthesis

Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking

Improving Semantic Segmentation of Aerial Images Using Patch-based Attention

Learning to Localize Sound Sources in Visual Scenes: Analysis and Applications

Weak Supervision for Generating Pixel-Level Annotations in Scene Text Segmentation

Differentiating Features for Scene Segmentation Based on Dedicated Attention Mechanisms

Constructing Multiple Tasks for Augmentation: Improving Neural Image Classification With K-means Features

NAIS: Neural Architecture and Implementation Search and its Applications in Autonomous Driving

Sequence-Aware Factorization Machines for Temporal Predictive Analytics

On Extended Long Short-term Memory and Dependent Bidirectional Recurrent Neural Network

ELoPE: Fine-Grained Visual Classification with Efficient Localization, Pooling and Embedding

Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks

DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue

Multi-attention Networks for Temporal Localization of Video-level Labels

Harmonic Mean Point Processes: Proportional Rate Error Minimization for Obtundation Prediction

TDAPNet: Prototype Network with Recurrent Top-Down Attention for Robust Object Classification under Partial Occlusion

Understanding the Disharmony between Weight Normalization Family and Weight Decay: $ε-$shifted $L_2$ Regularizer

Exploiting Local and Global Structure for Point Cloud Semantic Segmentation with Contextual Point Representations

Pose Guided Attention for Multi-label Fashion Image Classification

SharpNet: Fast and Accurate Recovery of Occluding Contours in Monocular Depth Estimation

FSD: Feature Skyscraper Detector for Stem End and Blossom End of Navel Orange

Logo-2K+: A Large-Scale Logo Dataset for Scalable Logo Classification

Asymptotic Soft Filter Pruning for Deep Convolutional Neural Networks

Semi-Heterogeneous Three-Way Joint Embedding Network for Sketch-Based Image Retrieval

Community-preserving Graph Convolutions for Structural and Functional Joint Embedding of Brain Networks

Regularized Deep Networks in Intelligent Transportation Systems: A Taxonomy and a Case Study

PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation

PointGrow: Autoregressively Learned Point Cloud Generation with Self-Attention

Deep Sequential Models for Suicidal Ideation from Multiple Source Data

Interpretable Self-Attention Temporal Reasoning for Driving Behavior Understanding

SRINet: Learning Strictly Rotation-Invariant Representations for Point Cloud Classification and Segmentation

Application of Multi-channel 3D-cube Successive Convolution Network for Convective Storm Nowcasting

Mobile Recognition of Wikipedia Featured Sites using Deep Learning and Crowd-sourced Imagery

Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction

Debiased distributed learning for sparse partial linear models in high dimensions

Unsupervised Multi-Domain Multimodal Image-to-Image Translation with Explicit Domain-Constrained Disentanglement

Multimodal Video-based Apparent Personality Recognition Using Long Short-Term Memory and Convolutional Neural Networks

Audience measurement using a top-view camera and oriented trajectories

Low-Rank HOCA: Efficient High-Order Cross-Modal Attention for Video Captioning

Learning pairwise Markov network structures using correlation neighborhoods

Deep Learning Emulation of Multi-Angle Implementation of Atmospheric Correction (MAIAC)

The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least Squares

SID4VAM: A Benchmark Dataset with Synthetic Images for Visual Attention Modeling

Understanding Attention and Generalization in Graph Neural Networks

Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded

Neural Shuffle-Exchange Networks -- Sequence Processing in O(n log n) Time

A Temporal Attentive Approach for Video-Based Pedestrian Attribute Recognition

An End-to-End Network for Co-Saliency Detection in One Single Image

Attend to the Difference: Cross-Modality Person Re-identification via Contrastive Correlation

Extending Event Detection to New Types with Learning from Keywords

Controllable Attention for Structured Layered Video Decomposition

Indoor Depth Completion with Boundary Consistency and Self-Attention

Identification of primary angle-closure on AS-OCT images with Convolutional Neural Networks

A Survey of Optimization Methods from a Machine Learning Perspective

Beyond Human Parts: Dual Part-Aligned Representations for Person Re-Identification

Double Supervised Network with Attention Mechanism for Scene Text Recognition

Weakly-Supervised Completion Moment Detection using Temporal Attention

A Review of Visual Trackers and Analysis of its Application to Mobile Robot

Tracking system of Mine Patrol Robot for Low Illumination Environment

Forced Spatial Attention for Driver Foot Activity Classification

Sequential Image-based Attention Network for Inferring Force Estimation without Haptic Sensor

Endowing Deep 3D Models with Rotation Invariance Based on Principal Component Analysis

Unsupervised High-Resolution Depth Learning From Videos With Dual Networks

TextSR: Content-Aware Text Super-Resolution Guided by Recognition

Component Attention Guided Face Super-Resolution Network: CAGFace

CreditPrint: Credit Investigation via Geographic Footprints by Deep Learning

Coordinated Joint Multimodal Embeddings for Generalized Audio-Visual Zeroshot Classification and Retrieval of Videos

ACFNet: Attentional Class Feature Network for Semantic Segmentation

Facial Action Unit Detection Using Attention and Relation Learning

Deep Contextual Attention for Human-Object Interaction Detection

Iterative augmentation of visual evidence for weakly-supervised lesion localization in deep interpretability frameworks

Integrating Temporal and Spatial Attentions for VATEX Video Captioning Challenge 2019

Depth Completion from Sparse LiDAR Data with Depth-Normal Constraints

Being the center of attention: A Person-Context CNN framework for Personality Recognition

Forecasting People Trajectories and Head Poses by Jointly Reasoning on Tracklets and Vislets

Exploring Overall Contextual Information for Image Captioning in Human-Like Cognitive Style

Graph-based regularization for regression problems with alignment and highly-correlated designs

Adaptive template systems: Data-driven feature selection for learning with persistence diagrams

Improving Pedestrian Attribute Recognition With Weakly-Supervised Multi-Scale Attribute-Specific Localization

Orthogonality Constrained Multi-Head Attention For Keyword Spotting

NRTR: A No-Recurrence Sequence-to-Sequence Model For Scene Text Recognition

Relation-Aware Graph Attention Network for Visual Question Answering

Perception of Image Features in Post-Mortem Iris Recognition: Humans vs Machines

Eyenet: Attention based Convolutional Encoder-Decoder Network for Eye Region Segmentation

Which Ads to Show? Advertisement Image Assessment with Auxiliary Information via Multi-step Modality Fusion

Pay Attention: Leveraging Sequence Models to Predict the Useful Life of Batteries

Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning

To React or not to React: End-to-End Visual Pose Forecasting for Personalized Avatar during Dyadic Conversations

Emotion Recognition with Spatial Attention and Temporal Softmax Pooling

CAN: Composite Appearance Network for Person Tracking and How to Model Errors in a Tracking System

Causal Induction from Visual Observations for Goal Directed Tasks

Scalable Generative Models for Graphs with Graph Attention Mechanism

Large-scale Tag-based Font Retrieval with Generative Feature Learning

RAUNet: Residual Attention U-Net for Semantic Segmentation of Cataract Surgical Instruments

BioNLP-OST 2019 RDoC Tasks: Multi-grain Neural Relevance Ranking Using Topics and Attention Based Query-Document-Sentence Interactions

RITnet: Real-time Semantic Segmentation of the Eye for Gaze Tracking

Spatiotemporal Co-attention Recurrent Neural Networks for Human-Skeleton Motion Prediction

Contextual Graph Attention for Answering Logical Queries over Incomplete Knowledge Graphs

Weakly Supervised Attention Networks for Fine-Grained Opinion Mining and Public Health

LIP: Learning Instance Propagation for Video Object Segmentation

EdgeCNN: Convolutional Neural Network Classification Model with small inputs for Edge Computing

Residual Attention Graph Convolutional Network for Geometric 3D Scene Classification

PyramNet: Point Cloud Pyramid Attention Network and Graph Embedding Module for Classification and Segmentation

GLA-Net: An Attention Network with Guided Loss for Mismatch Removal

Point Attention Network for Semantic Segmentation of 3D Point Clouds

Video-Based Convolutional Attention for Person Re-Identification

ALCNN: Attention-based Model for Fine-grained Demand Inference of Dock-less Shared Bike in New Cities

Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels

A Dual-Path Model With Adaptive Attention For Vehicle Re-Identification

Learning Coupled Spatial-temporal Attention for Skeleton-based Action Recognition

Interact as You Intend: Intention-Driven Human-Object Interaction Detection

EATEN: Entity-aware Attention for Single Shot Visual Text Extraction

Pose-aware Multi-level Feature Network for Human Object Interaction Detection

Instance Enhancement Batch Normalization: an Adaptive Regulator of Batch Noise

Extended Local Binary Patterns for Efficient and Robust Spontaneous Facial Micro-Expression Recognition

Building Change Detection for Remote Sensing Images Using a Dual Task Constrained Deep Siamese Convolutional Network Model

Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation

Evaluating and Boosting Uncertainty Quantification in Classification

Classification-Specific Parts for Improving Fine-Grained Visual Categorization

Inference for multiple object tracking: A Bayesian nonparametric approach

Using an AI creativity system to explore how aesthetic experiences are processed along the brains perceptual neural pathways

DashNet: A Hybrid Artificial and Spiking Neural Network for High-speed Object Tracking

A Linearly Constrained Nonparametric Framework for Imitation Learning

An Empirical Study towards Characterizing Deep Learning Development and Deployment across Different Frameworks and Platforms

Temporal Attentive Alignment for Large-Scale Video Domain Adaptation

Adversarial Examples Versus Cloud-based Detectors: A Black-box Empirical Study

Frame attention networks for facial expression recognition in videos

Human Visual Attention Prediction Boosts Learning & Performance of Autonomous Driving Agents

PDANet: Polarity-consistent Deep Attention Network for Fine-grained Visual Emotion Regression

Dual-attention Focused Module for Weakly Supervised Object Localization

Reasoning About Human-Object Interactions Through Dual Attention Networks

Deep Hashing Learning for Visual and Semantic Retrieval of Remote Sensing Images

Structure-Attentioned Memory Network for Monocular Depth Estimation

Robust Multiple Kernel k-means Clustering using Min-Max Optimization

Multimodal Attention Branch Network for Perspective-Free Sentence Generation

Crowd Counting on Images with Scale Variation and Isolated Clusters

Dynamic Gesture Recognition by Using CNNs and Star RGB: a Temporal Information Condensation

Anatomy-Aware Self-supervised Fetal MRI Synthesis from Unpaired Ultrasound Images

RANet: Ranking Attention Network for Fast Video Object Segmentation

HeteSpaceyWalk: A Heterogeneous Spacey Random Walk for Heterogeneous Information Network Embedding

HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking

Coarse2Fine: A Two-stage Training Method for Fine-grained Visual Classification

What can computational models learn from human selective attention? A review from an audiovisual crossmodal perspective

Stack-VS: Stacked Visual-Semantic Attention for Image Caption Generation

Knowledge-guided Pairwise Reconstruction Network for Weakly Supervised Referring Expression Grounding

A Better Way to Attend: Attention with Trees for Video Question Answering

Learning with Correntropy-induced Losses for Regression with Mixture of Symmetric Stable Noise

Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition

Understanding Human Gaze Communication by Spatio-Temporal Graph Reasoning

Multi-level Attention network using text, audio and video for Depression Prediction

Unsupervised Video Depth Estimation Based on Ego-motion and Disparity Consensus

EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks

View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition

Action Recognition in Untrimmed Videos with Composite Self-Attention Two-Stream Framework

Second-order Non-local Attention Networks for Person Re-identification

Max-C and Min-D Projection Autoassociative Fuzzy Morphological Memories: Theory and an Application for Face Recognition

Dual Attention MobDenseNet(DAMDNet) for Robust 3D Face Alignment

WPU-Net: Boundary Learning by Using Weighted Propagation in Convolution Network

TGG: Transferable Graph Generation for Zero-shot and Few-shot Learning

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images

PoreNet: CNN-based Pore Descriptor for High-resolution Fingerprint Recognition

Deep Floor Plan Recognition Using a Multi-Task Network with Room-Boundary-Guided Attention

Dual Attention Networks for Visual Reference Resolution in Visual Dialog

Adaptive Reconstruction Network for Weakly Supervised Referring Expression Grounding

Fingerspelling recognition in the wild with iterative visual attention

Multiresolution Transformer Networks: Recurrence is Not Essential for Modeling Hierarchical Structure

Permutohedral Attention Module for Efficient Non-Local Neural Networks

Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale

Fingerprint Presentation Attack Detection Based on Local Features Encoding for Unknown Attacks

Cooperative Cross-Stream Network for Discriminative Action Representation

Automatic Detection of ECG Abnormalities by using an Ensemble of Deep Residual Networks with Attention

Global-Local Temporal Representations For Video Person Re-Identification

Attention-based Dropout Layer for Weakly Supervised Object Localization

Dual Directed Capsule Network for Very Low Resolution Image Recognition

Learning single-image 3D reconstruction by generative modelling of shape, pose and shading

Attend To Count: Crowd Counting with Adaptive Capacity Multi-scale CNNs

Adaptive Embedding Gate for Attention-Based Scene Text Recognition

MGCN: Semi-supervised Classification in Multi-layer Graphs with Graph Convolutional Networks

Dynamic Fusion with Intra- and Inter- Modality Attention Flow for Visual Question Answering

Controlling for Confounders in Multimodal Emotion Classification via Adversarial Learning

Cephalometric Landmark Detection by AttentiveFeature Pyramid Fusion and Regression-Voting

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums

Progressive Face Super-Resolution via Attention to Facial Landmark

Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes

Multiple instance dense connected convolution neural network for aerial image scene classification

Deep Learning based Computer-Aided Diagnosis Systems for Diabetic Retinopathy: A Survey

RelGAN: Multi-Domain Image-to-Image Translation via Relative Attributes

Searching for Ambiguous Objects in Videos using Relational Referring Expressions

PCAS: Pruning Channels with Attention Statistics for Deep Network Compression

Multimodal Unified Attention Networks for Vision-and-Language Interactions

Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset

Robust Attentional Aggregation of Deep Feature Sets for Multi-view 3D Reconstruction

Language Features Matter: Effective Language Representations for Vision-Language Tasks

Attentional Feature-Pair Relation Networks for Accurate Face Recognition

Expectation-Maximization Attention Networks for Semantic Segmentation

LumiPath -- Towards Real-time Physically-based Rendering on Embedded Devices

Self-Attention Based Molecule Representation for Predicting Drug-Target Interaction

Semi-Supervised Semantic Segmentation with High- and Low-level Consistency

Fine-Grained Age Estimation in the wild with Attention LSTM Networks

A Single-Shot Arbitrarily-Shaped Text Detector based on Context Attended Multi-Task Learning

Once a MAN: Towards Multi-Target Attack via Learning Multi-Target Adversarial Network Once

Constrained Multi-Objective Optimization for Automated Machine Learning

Feature Prioritization and Regularization Improve Standard Accuracy and Adversarial Robustness

Multi-Frame Content Integration with a Spatio-Temporal Attention Mechanism for Person Video Motion Transfer

MC-ISTA-Net: Adaptive Measurement and Initialization and Channel Attention Optimization inspired Neural Network for Compressive Sensing

Attentive Deep Regression Networks for Real-Time Visual Face Tracking in Video Surveillance

SCAR: Spatial-/Channel-wise Attention Regression Networks for Crowd Counting

VisualBERT: A Simple and Performant Baseline for Vision and Language

GridDehazeNet: Attention-Based Multi-Scale Network for Image Dehazing

DAWN: Dual Augmented Memory Network for Unsupervised Video Object Tracking

Towards Generating Stylized Image Captions via Adversarial Training

Sharpen Focus: Learning with Attention Separability and Consistency

Advocacy Learning: Learning through Competition and Class-Conditional Representations

Improved Adversarial Robustness by Reducing Open Space Risk via Tent Activations

SCAN: Self-and-Collaborative Attention Network for Video Person Re-identification

Aligning Linguistic Words and Visual Semantic Units for Image Captioning

AUNet: Attention-guided dense-upsampling networks for breast mass segmentation in whole mammograms

Contour Loss: Boundary-Aware Learning for Salient Object Segmentation

REAPS: Towards Better Recognition of Fine-grained Images by Region Attending and Part Sequencing

Symmetry-constrained Rectification Network for Scene Text Recognition

Semi-Supervised Segmentation of Salt Bodies in Seismic Images using an Ensemble of Convolutional Neural Networks

Spatially and Temporally Efficient Non-local Attention Network for Video-based Person Re-Identification

Permutation-invariant Feature Restructuring for Correlation-aware Image Set-based Recognition

L2G Auto-encoder: Understanding Point Clouds by Local-to-Global Reconstruction with Hierarchical Self-Attention

Physical Cue based Depth-Sensing by Color Coding with Deaberration Network

Convolutional Auto-encoding of Sentence Topics for Image Paragraph Generation

Pay attention to the activations: a modular attention mechanism for fine-grained image recognition

SkeleMotion: A New Representation of Skeleton Joint Sequences Based on Motion Information for 3D Action Recognition

Towards Pure End-to-End Learning for Recognizing Multiple Text Sequences from an Image

Deep Multi-Kernel Convolutional LSTM Networks and an Attention-Based Mechanism for Videos

Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network

Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization

Self-attention based BiLSTM-CNN classifier for the prediction of ischemic and non-ischemic cardiomyopathy

Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images

AiAds: Automated and Intelligent Advertising System for Sponsored Search

Conditional Generative Neural System for Probabilistic Trajectory Prediction

A HVS-inspired Attention to Improve Loss Metrics for CNN-based Perception-Oriented Super-Resolution

Hybrid-Attention based Decoupled Metric Learning for Zero-Shot Image Retrieval

Universal Pooling -- A New Pooling Method for Convolutional Neural Networks

SceneGraphNet: Neural Message Passing for 3D Indoor Scene Augmentation

Real-Time Correlation Tracking via Joint Model Compression and Transfer

Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network

Class-specific Anchoring Proposal for 3D Object Recognition in LIDAR and RGB Images

TARN: Temporal Attentive Relation Network for Few-Shot and Zero-Shot Action Recognition

Attention Filtering for Multi-person Spatiotemporal Action Detection on Deep Two-Stream CNN Architectures

Construct Dynamic Graphs for Hand Gesture Recognition via Spatial-Temporal Attention

Order Matters: Shuffling Sequence Generation for Video Prediction

A Coarse-to-Fine Framework for Learned Color Enhancement with Non-Local Attention

Attending Category Disentangled Global Context for Image Classification

Analysis of "User-Specific Effect" and Impact of Operator Skills on Fingerprint PAD Systems

Incorporating Temporal Prior from Motion Flow for Instrument Segmentation in Minimally Invasive Surgery Video

Learning Bodily and Temporal Attention in Protective Movement Behavior Detection

FMHash: Deep Hashing of In-Air-Handwriting for User Identification

FilterReg: Robust and Efficient Probabilistic Point-Set Registration using Gaussian Filter and Twist Parameterization

Understanding and Accelerating Particle-Based Variational Inference

Evaluating Sequence-to-Sequence Models for Handwritten Text Recognition

Neural-Attention-Based Deep Learning Architectures for Modeling Traffic Dynamics on Lane Graphs

PaccMann: Prediction of anticancer compound sensitivity with multi-modal attention-based neural networks

Multi-Element Long Distance Dependencies: Using SPk Languages to Explore the Characteristics of Long-Distance Dependencies

AMAD: Adversarial Multiscale Anomaly Detection on High-Dimensional and Time-Evolving Categorical Data

Label-aware Document Representation via Hybrid Attention for Extreme Multi-Label Text Classification

Hybrid Residual Attention Network for Single Image Super Resolution

Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting

Purifying Real Images with an Attention-guided Style Transfer Network for Gaze Estimation

A Targeted Acceleration and Compression Framework for Low bit Neural Networks

Graph-based Knowledge Distillation by Multi-head Attention Network

Self-Supervised Model Adaptation for Multimodal Semantic Segmentation

SAN: Scale-Aware Network for Semantic Segmentation of High-Resolution Aerial Images

Patch Transformer for Multi-tagging Whole Slide Histopathology Images

Cascade Attention Guided Residue Learning GAN for Cross-Modal Translation

The ApolloScape Open Dataset for Autonomous Driving and its Application

Image Super-Resolution Using Attention Based DenseNet with Residual Deconvolution

Sequence to Sequence with Attention for Influenza Prevalence Prediction using Google Trends

AMI-Net+: A Novel Multi-Instance Neural Network for Medical Diagnosis from Incomplete and Imbalanced Data

Semantically-Aware Attentive Neural Embeddings for Image-based Visual Localization

An Analysis of Deep Neural Networks with Attention for Action Recognition from a Neurophysiological Perspective

The Resale Price Prediction of Secondhand Jewelry Items Using a Multi-modal Deep Model with Iterative Co-Attention

BiRA-Net: Bilinear Attention Net for Diabetic Retinopathy Grading

Mechanisms of Artistic Creativity in Deep Learning Neural Networks

Learning Where to Look While Tracking Instruments in Robot-assisted Surgery

Riemannian adaptive stochastic gradient algorithms on matrix manifolds

Deep Instance-Level Hard Negative Mining Model for Histopathology Images

Deep Modular Co-Attention Networks for Visual Question Answering

End-to-End Learning of Multi-scale Convolutional Neural Network for Stereo Matching

Incremental Few-Shot Learning for Pedestrian Attribute Recognition

CORAL8: Concurrent Object Regression for Area Localization in Medical Image Panels

Deep Single Image Deraining Via Estimating Transmission and Atmospheric Light in rainy Scenes

KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images

Efficient data augmentation using graph imputation neural networks

Local Bures-Wasserstein Transport: A Practical and Fast Mapping Approximation

PoseConvGRU: A Monocular Approach for Visual Ego-motion Estimation by Learning

Analyzing the Robustness of Nearest Neighbors to Adversarial Examples

Joint Iris Segmentation and Localization Using Deep Multi-task Learning Framework

A Study of the Learning Progress in Neural Architecture Search Techniques

A One-step Pruning-recovery Framework for Acceleration of Convolutional Neural Networks

ParNet: Position-aware Aggregated Relation Network for Image-Text matching

Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks

Image Captioning with Integrated Bottom-Up and Multi-level Residual Top-Down Attention for Game Scene Understanding

Attributed Graph Clustering: A Deep Attentional Embedding Approach

RECAL: Reuse of Established CNN classifer Apropos unsupervised Learning paradigm

Confidence intervals for class prevalences under prior probability shift

A stochastic alternating minimizing method for sparse phase retrieval

Topological Data Analysis for Arrhythmia Detection through Modular Neural Networks

MIMA: MAPPER-Induced Manifold Alignment for Semi-Supervised Fusion of Optical Image and Polarimetric SAR Data

Skeleton-Based Action Recognition with Synchronous Local and Non-local Spatio-temporal Learning and Frequency Attention

Medium-Term Load Forecasting Using Support Vector Regression, Feature Selection, and Symbiotic Organism Search Optimization

Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-grained Image Recognition

Band Attention Convolutional Networks For Hyperspectral Image Classification

An Attention-based Recurrent Convolutional Network for Vehicle Taillight Recognition

Attention-based Conditioning Methods for External Knowledge Integration

Understanding overfitting peaks in generalization error: Analytical risk curves for $l_2$ and $l_1$ penalized interpolation

InfoMask: Masked Variational Latent Representation to Localize Chest Disease

Attention is all you need for Videos: Self-attention based Video Summarization using Universal Transformers

Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms

Removing Rain in Videos: A Large-scale Database and A Two-stream ConvLSTM Approach

A Robust Deep Learning Approach for Automatic Classification of Seizures Against Non-seizures

A GLCM Embedded CNN Strategy for Computer-aided Diagnosis in Intracerebral Hemorrhage

Texture Synthesis Guided Deep Hashing for Texture Image Retrieval

Don't Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are Better Without the Outer Loop

Show, Attend and Translate: Unsupervised Image Translation with Self-Regularization and Attention

Visual Tree Convolutional Neural Network in Image Classification

Multi-step Reasoning via Recurrent Dual Attention for Visual Dialog

Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs

Interpretable Spatio-temporal Attention for Video Action Recognition

Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph

Consensus Clustering: An Embedding Perspective, Extension and Beyond

Deep Dual Relation Modeling for Egocentric Interaction Recognition

Riemannian stochastic variance reduced gradient algorithm with retraction and vector transport

Point Clouds Learning with Attention-based Graph Convolution Networks

Align-and-Attend Network for Globally and Locally Coherent Video Inpainting

End-to-End Pore Extraction and Matching in Latent Fingerprints: Going Beyond Minutiae

Attention: A Big Surprise for Cross-Domain Person Re-Identification

Multi-level Multimodal Common Semantic Space for Image-Phrase Grounding

A Novel Multi-Attention Driven System For Multi-Label Remote Sensing Image Classification

Decentralized Online Learning: Take Benefits from Others' Data without Sharing Your Own to Track Global Trend

A Symmetric Encoder-Decoder with Residual Block for Infrared and Visible Image Fusion

Audio2Face: Generating Speech/Face Animation from Single Audio with Attention-Based Bidirectional LSTM Networks

SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models

Attention-based Supply-Demand Prediction for Autonomous Vehicles

Distributionally Robust Optimization and Generalization in Kernel Methods

Combining Model and Parameter Uncertainty in Bayesian Neural Networks

Multi-view Information-theoretic Co-clustering for Co-occurrence Data

Instance-level Sketch-based Retrieval by Deep Triplet Classification Siamese Network

Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional Networks

Domain Adaptive Attention Model for Unsupervised Cross-Domain Person Re-Identification

Direction-aware Spatial Context Features for Shadow Detection and Removal

Saliency Prediction in the Deep Learning Era: Successes, Limitations, and Future Challenges

Multi-Scale Dual-Branch Fully Convolutional Network for Hand Parsing

ACNet: Attention Based Network to Exploit Complementary Features for RGBD Semantic Segmentation

STG2Seq: Spatial-temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting

Pose-adaptive Hierarchical Attention Network for Facial Expression Recognition

Group-Attention Single-Shot Detector (GA-SSD): Finding Pulmonary Nodules in Large-Scale CT Images

Meta-GNN: On Few-shot Node Classification in Graph Meta-learning

Learning Fully Dense Neural Networks for Image Semantic Segmentation

GAPNet: Graph Attention based Point Neural Network for Exploiting Local Feature of Point Cloud

Marginalized Average Attentional Network for Weakly-Supervised Learning

Intentional Attention Mask Transformation for Robust CNN Classification

Predicting Model Failure using Saliency Maps in Autonomous Driving Systems

Parts4Feature: Learning 3D Global Features from Generally Semantic Parts in Multiple Views

3DViewGraph: Learning Global Features for 3D Shapes from A Graph of Unordered Views with Attention

Decision-Oriented Communications: Application to Energy-Efficient Resource Allocation

Texture Fields: Learning Texture Representations in Function Space

Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis

Generating Adversarial Perturbation with Root Mean Square Gradient

Dynamic mode decomposition in vector-valued reproducing kernel Hilbert spaces for extracting dynamical structure among observables

Recurrent Convolutional Strategies for Face Manipulation Detection in Videos

Beyond Bilinear: Generalized Multimodal Factorized High-order Pooling for Visual Question Answering

Arbitrary Shape Scene Text Detection with Adaptive Text Region Representation

End to End Recognition System for Recognizing Offline Unconstrained Vietnamese Handwriting

A human-inspired recognition system for premodern Japanese historical documents

Graph Attribute Aggregation Network with Progressive Margin Folding

Rao-Blackwellized Stochastic Gradients for Discrete Distributions

A Deep Spatio-Temporal Fuzzy Neural Network for Passenger Demand Prediction

Medical image super-resolution method based on dense blended attention network

LEDNet: A Lightweight Encoder-Decoder Network for Real-Time Semantic Segmentation

Densifying Assumed-sparse Tensors: Improving Memory Efficiency and MPI Collective Performance during Tensor Accumulation for Parallelized Training of Neural Machine Translation Models

Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations

Traffic Queue Length and Pressure Estimation for Road Networks with Geometric Deep Learning Algorithms

Hierarchical Cross-Modal Talking Face Generationwith Dynamic Pixel-Wise Loss

A Baseline for Multi-Label Image Classification Using An Ensemble of Deep Convolutional Neural Networks

Skin Lesion Classification Using CNNs with Patch-Based Attention and Diagnosis-Guided Loss Weighting

Multi-Person Pose Estimation with Enhanced Channel-wise and Spatial Information

EDVR: Video Restoration with Enhanced Deformable Convolutional Networks

Dynamic Graph Modules for Modeling Object-Object Interactions in Activity Recognition

Feature-Fused Context-Encoding Network for Neuroanatomy Segmentation

Saliency for Fine-grained Object Recognition in Domains with Scarce Training Data

Temporal Deformable Convolutional Encoder-Decoder Networks for Video Captioning

Physicist's Journeys Through the AI World - A Topical Review. There is no royal road to unsupervised learning

Similarity Learning with Higher-Order Graph Convolutions for Brain Network Analysis

Cross Domain Knowledge Learning with Dual-branch Adversarial Network for Vehicle Re-identification

DeepHMap++: Combined Projection Grouping and Correspondence Learning for Full DoF Pose Estimation

Video-based Person Re-identification via 3D Convolutional Networks and Non-local Attention

Feature selection as Monte-Carlo Search in Growing Single Rooted Directed Acyclic Graph by Best Leaf Identification

Actional-Structural Graph Convolutional Networks for Skeleton-based Action Recognition

Learning Better Features for Face Detection with Feature Fusion and Segmentation Supervision

A Double-Deep Spatio-Angular Learning Framework for Light Field based Face Recognition

Multi-Scale Body-Part Mask Guided Attention for Person Re-identification

Improving Few-Shot User-Specific Gaze Adaptation via Gaze Redirection Synthesis

Computer-aided diagnosis in histopathological images of the endometrium using a convolutional neural network and attention mechanisms

Latent Variable Algorithms for Multimodal Learning and Sensor Fusion

Connection Sensitive Attention U-NET for Accurate Retinal Vessel Segmentation

DenseAttentionSeg: Segment Hands from Interacted Objects Using Depth Input

DADA-2000: Can Driving Accident be Predicted by Driver Attention? Analyzed by A Benchmark

Spatio-temporal crop classification of low-resolution satellite imagery with capsule layers and distributed attention

PCAN: 3D Attention Map Learning Using Contextual Information for Point Cloud Based Retrieval

A Unified Framework for Structured Graph Learning via Spectral Constraints

Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness

iQIYI-VID: A Large Dataset for Multi-modal Person Identification

FeatherNets: Convolutional Neural Networks as Light as Feather for Face Anti-spoofing

DDGK: Learning Graph Representations for Deep Divergence Graph Kernels

Attention Based Glaucoma Detection: A Large-scale Database and CNN Model

XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation

Progressive Attention Memory Network for Movie Story Question Answering

An Unsupervised Feature Learning Approach to Reduce False Alarm Rate in ICUs

BS-Nets: An End-to-End Framework For Band Selection of Hyperspectral Image

Deep learning investigation for chess player attention prediction using eye-tracking and game data

Predicting drug-target interaction using 3D structure-embedded graph representations from graph neural networks

SCE: A manifold regularized set-covering method for data partitioning

Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation

Deep Learning Under the Microscope: Improving the Interpretability of Medical Imaging Neural Networks

What I See Is What You See: Joint Attention Learning for First and Third Person Video Co-analysis

Complete the Look: Scene-based Complementary Product Recommendation

Gyroscope-aided Relative Pose Estimation for Rolling Shutter Cameras

Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout

MAANet: Multi-view Aware Attention Networks for Image Super-Resolution

Supersaliency: A Novel Pipeline for Predicting Smooth Pursuit-Based Attention Improves Generalizability of Video Saliency

LSTA: Long Short-Term Attention for Egocentric Action Recognition

Ranking-Based Autoencoder for Extreme Multi-label Classification

An Empirical Study of Spatial Attention Mechanisms in Deep Networks

ADCrowdNet: An Attention-injective Deformable Convolutional Network for Crowd Understanding

The Pros and Cons: Rank-aware Temporal Attention for Skill Determination in Long Videos

Attention Branch Network: Learning of Attention Mechanism for Visual Explanation

Convolutional Temporal Attention Model for Video-based Person Re-identification

Manipulation-skill Assessment from Videos with Spatial Attention Network

Semi-Supervised Graph Classification: A Hierarchical Graph Perspective

DeepLiDAR: Deep Surface Normal Guided Depth Prediction for Outdoor Scene from Sparse LiDAR Data and Single Color Image

Attention-based Multi-instance Neural Network for Medical Diagnosis from Incomplete and Low Quality Data

Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers

Heterogeneous Memory Enhanced Multimodal Attention Model for Video Question Answering

L2AE-D: Learning to Aggregate Embeddings for Few-shot Learning with Meta-level Dropout

Unsupervised learning of action classes with continuous temporal embedding

VayuAnukulani: Adaptive Memory Networks for Air Pollution Forecasting

Referring to Objects in Videos using Spatio-Temporal Identifying Descriptions

Unsupervised Person Re-identification by Soft Multilabel Learning

Attention-based Adaptive Selection of Operations for Image Restoration in the Presence of Unknown Combined Distortions

Learning Metrics from Teachers: Compact Networks for Image Embedding

Modeling Point Clouds with Self-Attention and Gumbel Subset Sampling

CoSpace: Common Subspace Learning from Hyperspectral-Multispectral Correspondences

Dense Haze: A benchmark for image dehazing with dense-haze and haze-free images

Snap and Find: Deep Discrete Cross-domain Garment Image Retrieval

Beyond Tracking: Selecting Memory and Refining Poses for Deep Visual Odometry

Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning

Focus On What's Important: Self-Attention Model for Human Pose Estimation

DeCaFA: Deep Convolutional Cascade for Face Alignment In The Wild

A Weighted Sparse Sampling and Smoothing Frame Transition Approach for Semantic Fast-Forward First-Person Videos

A Survey on Practical Applications of Multi-Armed and Contextual Bandits

Aiding Intra-Text Representations with Visual Context for Multimodal Named Entity Recognition

Improving Referring Expression Grounding with Cross-modal Attention-guided Erasing

Deep Built-Structure Counting in Satellite Imagery Using Attention Based Re-Weighting

Beyond saliency: understanding convolutional neural networks from saliency prediction on layer-wise relevance propagation

Discriminative Feature Learning with Foreground Attention for Person Re-Identification

Adaptive Adjustment with Semantic Feature Space for Zero-Shot Recognition

An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition

GrAMME: Semi-Supervised Learning using Multi-layered Graph Attention Models

Video Relationship Reasoning using Gated Spatio-Temporal Energy Graph

Attention-based Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors

Probabilistic Load Forecasting via Point Forecast Feature Integration

Down-Scaling with Learned Kernels in Multi-Scale Deep Neural Networks for Non-Uniform Single Image Deblurring

Predicting Multiple Demographic Attributes with Task Specific Embedding Transformation and Attention Network

Attention-based Few-Shot Person Re-identification Using Meta Learning

Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets

Periphery-Fovea Multi-Resolution Driving Model guided by Human Attention

See Better Before Looking Closer: Weakly Supervised Data Augmentation Network for Fine-Grained Visual Classification

Aggregated Deep Local Features for Remote Sensing Image Retrieval

On Approximate Nonlinear Gaussian Message Passing On Factor Graphs

Learning with Batch-wise Optimal Transport Loss for 3D Shape Recognition

Context-Constrained Accurate Contour Extraction for Occlusion Edge Detection

Value of Temporal Dynamics Information in Driving Scene Segmentation

Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays

Regularize, Expand and Compress: Multi-task based Lifelong Learning via NonExpansive AutoML

A Hybrid Method for Traffic Flow Forecasting Using Multimodal Deep Learning

Boosted Attention: Leveraging Human Attention for Image Captioning

Approximating exponential family models (not single distributions) with a two-network architecture

Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition

Pose Graph Optimization for Unsupervised Monocular Visual Odometry

Unsupervised and interpretable scene discovery with Discrete-Attend-Infer-Repeat

Audiovisual Speaker Tracking using Nonlinear Dynamical Systems with Dynamic Stream Weights

Exemplar Guided Unsupervised Image-to-Image Translation with Semantic Consistency

AdaFlow: Domain-Adaptive Density Estimator with Application to Anomaly Detection and Unpaired Cross-Domain Translation

Learning Feature Aggregation in Temporal Domain for Re-Identification

Alignment Based Matching Networks for One-Shot Classification and Open-Set Recognition

Spatial-Aware Non-Local Attention for Fashion Landmark Detection

Machine Learning by Unitary Tensor Network of Hierarchical Tree Structure

Deep Robust Subjective Visual Property Prediction in Crowdsourcing

Combining 3D Morphable Models: A Large scale Face-and-Head Model

Feature Selection for Survival Analysis with Competing Risks using Deep Learning

SR-LSTM: State Refinement for LSTM towards Pedestrian Trajectory Prediction

CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning

Efficient Winograd or Cook-Toom Convolution Kernel Implementation on Widely Used Mobile CPUs

Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function

Calibration of Encoder Decoder Models for Neural Machine Translation

Machine learning in policy evaluation: new tools for causal inference

Imaging and Classification Techniques for Seagrass Mapping and Monitoring: A Comprehensive Survey

Real-world plant species identification based on deep convolutional neural networks and visual attention

AFS: An Attention-based mechanism for Supervised Feature Selection

Weakly Supervised Bilinear Attention Network for Fine-Grained Visual Classification

Look, Investigate, and Classify: A Deep Hybrid Attention Method for Breast Cancer Classification

Multi-Scale Convolutional-Stack Aggregation for Robust White Matter Hyperintensities Segmentation

An Efficient Approach to Boosting Performance of Deep Spiking Network Training

Center Emphasized Visual Saliency and a Contrast-based Full Reference Image Quality Index

Interaction-aware Factorization Machines for Recommender Systems

MUREL: Multimodal Relational Reasoning for Visual Question Answering

Beyond Photometric Loss for Self-Supervised Ego-Motion Estimation

Statistical Method to Model the Quality Inconsistencies of the Welding Process

Prediction of Malignant & Benign Breast Cancer: A Data Mining Approach in Healthcare Applications

A Regularized Framework for Sparse and Structured Neural Attention

A Review, Framework and R toolkit for Exploring, Evaluating, and Comparing Visualizations

Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic Segmentation

An Intelligent Safety System for Human-Centered Semi-Autonomous Vehicles

Learning Transferable Self-attentive Representations for Action Recognition in Untrimmed Videos with Weak Supervision

Deeply Supervised Multimodal Attentional Translation Embeddings for Visual Relationship Detection

Breaking the Spatio-Angular Trade-off for Light Field Super-Resolution via LSTM Modelling on Epipolar Plane Images

3D Graph Embedding Learning with a Structure-aware Loss Function for Point Cloud Semantic Instance Segmentation

Situation-Aware Pedestrian Trajectory Prediction with Spatio-Temporal Attention Model

ConnNet: A Long-Range Relation-Aware Pixel-Connectivity Network for Salient Segmentation

Using Deep Cross Modal Hashing and Error Correcting Codes for Improving the Efficiency of Attribute Guided Facial Image Retrieval

Deep supervision with additional labels for retinal vessel segmentation task

Contextual Hourglass Network for Semantic Segmentation of High Resolution Aerial Imagery

Region based Ensemble Learning Network for Fine-grained Classification

An Optimal Policy for Dynamic Assortment Planning Under Uncapacitated Multinomial Logit Models

iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making

Multi-modal Ensemble Classification for Generalized Zero Shot Learning

3D PersonVLAD: Learning Deep Global Representations for Video-based Person Re-identification

Deep Convolutional Neural Network for Automated Detection of Mind Wandering using EEG Signals

Wavelet based edge feature enhancement for convolutional neural networks

Dual Path Multi-Scale Fusion Networks with Attention for Crowd Counting

Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network

Automatic trajectory measurement of large numbers of crowded objects

Online Multi-Object Tracking with Dual Matching Attention Networks

SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging

Bayesian posterior approximation via greedy particle optimization

Saliency detection for seismic applications using multi-dimensional spectral projections and directional comparisons

Understanding spatial correlation in eye-fixation maps for visual attention in videos

Attention-driven Tree-structured Convolutional LSTM for High Dimensional Data Understanding

Adversarial Examples Are a Natural Consequence of Test Error in Noise

Attention-based Context Aggregation Network for Monocular Depth Estimation

Fairness in representation: quantifying stereotyping as a representational harm

Challenges in Designing Datasets and Validation for Autonomous Driving

Visual Categorization of Objects into Animal and Plant Classes Using Global Shape Descriptors

Subjective Annotations for Vision-Based Attention Level Estimation

DF-SLAM: A Deep-Learning Enhanced Visual SLAM System based on Deep Local Features

Re-evaluating Continual Learning Scenarios: A Categorization and Case for Strong Baselines

Pattern Generation Strategies for Improving Recognition of Handwritten Mathematical Expressions

Improving generation quality of pointer networks via guided attention

Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images

Multisource Region Attention Network for Fine-Grained Object Recognition in Remote Sensing Imagery

Enhance the Motion Cues for Face Anti-Spoofing using CNN-LSTM Architecture

Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing

Visual Reasoning of Feature Attribution with Deep Recurrent Neural Networks

GASL: Guided Attention for Sparsity Learning in Deep Neural Networks

Deep Fusion: An Attention Guided Factorized Bilinear Pooling for Audio-video Emotion Recognition

MGANet: A Robust Model for Quality Enhancement of Compressed Video

Spatiotemporal Recurrent Convolutional Networks for Recognizing Spontaneous Micro-expressions

Interpretable machine learning: definitions, methods, and applications

Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements

Predicting Video Saliency with Object-to-Motion CNN and Two-layer Convolutional LSTM

Learning Efficient Detector with Semi-supervised Adaptive Distillation

Learning Semantic Segmentation from Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach

3D Feature Pyramid Attention Module for Robust Visual Speech Recognition

On the Turing Completeness of Modern Neural Network Architectures

Quantized Epoch-SGD for Communication-Efficient Distributed Learning

Multi-feature Distance Metric Learning for Non-rigid 3D Shape Retrieval

A Multi-Object Rectified Attention Network for Scene Text Recognition

Grey matter sublayer thickness estimation in themouse cerebellum

DPPNet: Approximating Determinantal Point Processes with Deep Networks

Double Weighted Truncated Nuclear Norm Regularization for Low-Rank Matrix Completion

Semi-supervised learning in unbalanced and heterogeneous networks

Unsupervised uncertainty estimation using spatiotemporal cues in video saliency detection

Amortized Context Vector Inference for Sequence-to-Sequence Networks

Efficient Image Retrieval via Decoupling Diffusion into Online and Offline Processing

Wider Channel Attention Network for Remote Sensing Image Super-resolution

Not All Words are Equal: Video-specific Information Loss for Video Captioning

Feature Preserving and Uniformity-controllable Point Cloud Simplification on Graph

Future semantic segmentation of time-lapsed videos with large temporal displacement

A Two-Stream Mutual Attention Network for Semi-supervised Biomedical Segmentation with Noisy Labels

Self-Attention Equipped Graph Convolutions for Disease Prediction

TextNet: Irregular Text Reading from Images with an End-to-End Trainable Network

Chinese Herbal Recognition based on Competitive Attentional Fusion of Multi-hierarchies Pyramid Features

An Empirical Analysis of Deep Audio-Visual Models for Speech Recognition

Binary Constrained Deep Hashing Network for Image Retrieval without Manual Annotation

Towards Robust Human Activity Recognition from RGB Video Stream with Limited Labeled Data

Combining Deep and Depth: Deep Learning and Face Depth Maps for Driver Attention Monitoring

Bandit Structured Prediction for Neural Sequence-to-Sequence Learning

EasiCSDeep: A deep learning model for Cervical Spondylosis Identification using surface electromyography signal

Learning models for visual 3D localization with implicit mapping

Homogeneous Feature Transfer and Heterogeneous Location Fine-tuning for Cross-City Property Appraisal Framework

Coarse-to-fine: A RNN-based hierarchical attention model for vehicle re-identification

Deep Learning with Attention to Predict Gestational Age of the Fetal Brain

Real-Time Referring Expression Comprehension by Single-Stage Grounding Network

Skeleton-based Gesture Recognition Using Several Fully Connected Layers with Path Signature Features and Temporal Transformer Module

Spatial-Spectral Regularized Local Scaling Cut for Dimensionality Reduction in Hyperspectral Image Classification

Simultaneous Recognition of Horizontal and Vertical Text in Natural Images

Classifying a specific image region using convolutional nets with an ROI mask as input

VideoMem: Constructing, Analyzing, Predicting Short-term and Long-term Video Memorability

Less but Better: Generalization Enhancement of Ordinal Embedding via Distributional Margin

Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition

Towards Theoretical Understanding of Large Batch Training in Stochastic Gradient Descent

Multi-task Learning of Hierarchical Vision-Language Representation

PVRNet: Point-View Relation Neural Network for 3D Shape Recognition

Plan-Recognition-Driven Attention Modeling for Visual Recognition

Interpretable Graph Convolutional Neural Networks for Inference on Noisy Knowledge Graphs

Improved Fusion of Visual and Language Representations by Dense Symmetric Co-Attention for Visual Question Answering

Stochastic Training of Residual Networks: a Differential Equation Viewpoint

An Efficient Image Retrieval Based on Fusion of Low-Level Visual Features

ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving

Attacks on State-of-the-Art Face Recognition using Attentional Adversarial Attack Generative Network

CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks

Parameter-Free Spatial Attention Network for Person Re-Identification

Two-level Attention with Two-stage Multi-task Learning for Facial Emotion Recognition

3D Shape Reconstruction from a Single 2D Image via 2D-3D Self-Consistency

ICPRAI 2018 SI: On dynamic ensemble selection and data preprocessing for multi-class imbalance learning

Sequence-based Person Attribute Recognition with Joint CTC-Attention Model

Noise-tolerant Audio-visual Online Person Verification using an Attention-based Neural Network Fusion

Generating Attention from Classifier Activations for Fine-grained Recognition

Principled Deep Neural Network Training through Linear Programming

Attentioned Convolutional LSTM InpaintingNetwork for Anomaly Detection in Videos

Visual Attention on the Sun: What Do Existing Models Actually Predict?

Discriminative Feature Learning for Unsupervised Video Summarization

Alternating Loss Correction for Preterm-Birth Prediction from EHR Data with Noisy Labels

Mean Local Group Average Precision (mLGAP): A New Performance Metric for Hashing-based Retrieval

Detailed Investigation of Deep Features with Sparse Representation and Dimensionality Reduction in CBIR: A Comparative Study

Teaching UAVs to Race: End-to-End Regression of Agile Controls in Simulation

Mask R-CNN with Pyramid Attention Network for Scene Text Detection

AttentionMask: Attentive, Efficient Object Proposal Generation Focusing on Small Objects

Diffusion-based nonlinear filtering for multimodal data fusion with application to sleep stage assessment

Sketch-R2CNN: An Attentive Network for Vector Sketch Recognition

Beyond Attributes: Adversarial Erasing Embedding Network for Zero-shot Learning

Factorized Distillation: Training Holistic Person Re-identification Model by Distilling an Ensemble of Partial ReID Models

Modeling Local Geometric Structure of 3D Point Clouds using Geo-CNN

CA3Net: Contextual-Attentional Attribute-Appearance Network for Person Re-Identification

Multi-scale 3D Convolution Network for Video Based Person Re-Identification

Segregated Temporal Assembly Recurrent Networks for Weakly Supervised Multiple Action Detection

Attention Mechanisms for Object Recognition with Event-Based Cameras

Implementation of Robust Face Recognition System Using Live Video Feed Based on CNN

Deep Interest Evolution Network for Click-Through Rate Prediction

Generative Model for Material Experiments Based on Prior Knowledge and Attention Mechanism

Learning to Generate and Reconstruct 3D Meshes with only 2D Supervision

Psychophysical evaluation of individual low-level feature influences on visual attention

Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-based Sequence to Sequence Network

Repeatability of Multiparametric Prostate MRI Radiomics Features

Granger-causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks

Child Gender Determination with Convolutional Neural Networks on Hand Radio-Graphs

NeXtVLAD: An Efficient Neural Network to Aggregate Frame-level Features for Large-scale Video Classification

Holistic Multi-modal Memory Network for Movie Question Answering

Coronary Calcium Detection using 3D Attention Identical Dual Deep Network Based on Weakly Supervised Learning

STA: Spatial-Temporal Attention for Large-Scale Video-based Person Re-Identification

Scene Parsing via Dense Recurrent Neural Networks with Attentional Selection

Multi-shot Person Re-identification through Set Distance with Visual Distributional Representation

ExGate: Externally Controlled Gating for Feature-based Attention in Artificial Neural Networks

Anomaly Detection Using GANs for Visual Inspection in Noisy Training Data

A Quasi-Newton algorithm on the orthogonal manifold for NMF with transform learning

Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction

An Element Sensitive Saliency Model with Position Prior Learning for Web Pages

To Find Where You Talk: Temporal Sentence Localization in Video with Attention Based Location Regression

Understanding and Comparing Scalable Gaussian Process Regression for Big Data

Efficiently Learning Nonstationary Gaussian Processes for Real World Impact

Independent Vector Analysis for Data Fusion Prior to Molecular Property Prediction with Machine Learning

Skeleton-based Activity Recognition with Local Order Preserving Match of Linear Patches

Attention-Mechanism-based Tracking Method for Intelligent Internet of Vehicles

Cascaded Pyramid Mining Network for Weakly Supervised Temporal Action Localization

Automatic Graphics Program Generation using Attention-Based Hierarchical Decoder

Proximal SCOPE for Distributed Sparse Learning: Better Data Partition Implies Faster Convergence Rate

Video-based Person Re-identification Using Spatial-Temporal Attention Networks

Attentive Semantic Alignment with Offset-Aware Correlation Kernels

Fine-grained Video Categorization with Redundancy Reduction Attention

Deep Predictive Coding Network with Local Recurrent Processing for Object Recognition

Forecasting Individualized Disease Trajectories using Interpretable Deep Learning

Multistep Speed Prediction on Traffic Networks: A Graph Convolutional Sequence-to-Sequence Learning Approach with Attention Mechanism

Cross-Resolution Person Re-identification with Deep Antithetical Learning

Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks

Action and intention recognition of pedestrians in urban traffic

Exploring Correlations in Multiple Facial Attributes through Graph Attention Network

A Method for Robust Online Classification using Dictionary Learning: Development and Assessment for Monitoring Manual Material Handling Activities Using Wearable Sensors

CNNPred: CNN-based stock market prediction using several data sources

SCPNet: Spatial-Channel Parallelism Network for Joint Holistic and Partial Person Re-Identification

Hyper-Process Model: A Zero-Shot Learning algorithm for Regression Problems based on Shape Analysis

Channel Attention and Multi-level Features Fusion for Single Image Super-Resolution

Contrast and visual saliency similarity-induced index for assessing image quality

Morph: Flexible Acceleration for 3D CNN-based Video Understanding

Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identification

Dense Object Reconstruction from RGBD Images with Embedded Deep Shape Representations

Introducing a hybrid model of DEA and data mining in evaluating efficiency. Case study: Bank Branches

Invariance Analysis of Saliency Models versus Human Gaze During Scene Free Viewing

Knowing Where to Look? Analysis on Attention of Visual Question Answering System

Deeply learning molecular structure-property relationships using attention- and gate-augmented graph convolutional network

Triple Attention Mixed Link Network for Single Image Super Resolution

Semi-Coupled Two-Stream Fusion ConvNets for Action Recognition at Extremely Low Resolutions

Scaling Submodular Optimization Approaches for Control Applications in Networked Systems

From BoW to CNN: Two Decades of Texture Representation for Texture Classification

Visual Object Tracking based on Adaptive Siamese and Motion Estimation Network

Audio-Visual Speech Recognition With A Hybrid CTC/Attention Architecture

Channel-wise and Spatial Feature Modulation Network for Single Image Super-Resolution

Learning to Remember, Forget and Ignore using Attention Control in Memory

Local Frequency Interpretation and Non-Local Self-Similarity on Graph for Point Cloud Inpainting

An Interactive Greedy Approach to Group Sparsity in High Dimensions

Sharp Attention Network via Adaptive Sampling for Person Re-identification

Unconstrained Face Detection and Open-Set Face Recognition Challenge

RGB Video Based Tennis Action Recognition Using a Deep Historical Long Short-Term Memory

Variational Collaborative Learning for User Probabilistic Representation

Targeted Kernel Networks: Faster Convolutions with Attentive Regularization

Multimodal Dual Attention Memory for Video Story Question Answering

SG-FCN: A Motion and Memory-Based Deep Learning Model for Video Saliency Detection

Implementing Adaptive Separable Convolution for Video Frame Interpolation

Crowd Counting by Adaptively Fusing Predictions from an Image Pyramid

Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability

Rehabilitating the ColorChecker Dataset for Illuminant Estimation

Efficient Rank Minimization via Solving Non-convexPenalties by Iterative Shrinkage-Thresholding Algorithm

Toward Characteristic-Preserving Image-based Virtual Try-On Network

Deep Inferential Spatial-Temporal Network for Forecasting Air Pollution Concentrations

Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding

Aligned to the Object, not to the Image: A Unified Pose-aligned Representation for Fine-grained Recognition

An Efficient ADMM-Based Algorithm to Nonconvex Penalized Support Vector Machines

Annotating shadows, highlights and faces: the contribution of a 'human in the loop' for digital art history

RealPoint3D: Point Cloud Generation from a Single Image with Complex Background

DensSiam: End-to-End Densely-Siamese Network with Self-Attention Model for Object Tracking

Multi-level hypothesis testing for populations of heterogeneous networks

Deep Neural Net with Attention for Multi-channel Multi-touch Attribution

AffinityNet: semi-supervised few-shot learning for disease type prediction

Deep learning bank distress from news and numerical financial data

Detail Preserving Depth Estimation from a Single Image Using Attention Guided Networks

Prediction of Electric Multiple Unit Fleet Size Based on Convolutional Neural Network

VoxSegNet: Volumetric CNNs for Semantic Part Segmentation of 3D Shapes

A Self-Attention Network for Hierarchical Data Structures with an Application to Claims Management

iCAN: Instance-Centric Attention Network for Human-Object Interaction Detection

Top-down Attention Recurrent VLAD Encoding for Action Recognition in Videos

Matrix Factorization Equals Efficient Co-occurrence Representation

Localization Guided Learning for Pedestrian Attribute Recognition

PVNet: A Joint Convolutional Network of Point Cloud and Multi-View for 3D Shape Recognition

Capsule Networks for Protein Structure Classification and Prediction

Learning to Support: Exploiting Structure Information in Support Sets for One-Shot Learning

Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally

Deep multiscale convolutional feature learning for weakly supervised localization of chest pathologies in X-ray images

On a New Improvement-Based Acquisition Function for Bayesian Optimization

Self-supervised learning of a facial attribute embedding from video

Glimpse Clouds: Human Activity Recognition from Unstructured Feature Points

VERAM: View-Enhanced Recurrent Attention Model for 3D Shape Classification

Triangle Lasso for Simultaneous Clustering and Optimization in Graph Datasets

Measuring the Temporal Behavior of Real-World Person Re-Identification

Temporal Sequence Distillation: Towards Few-Frame Action Recognition in Videos

Multispectral Pedestrian Detection via Simultaneous Detection and Segmentation

Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence

Looking Beyond a Clever Narrative: Visual Context and Attention are Primary Drivers of Affect in Video Advertisements

Improving Native Ads CTR Prediction by Large Scale Event Embedding and Recurrent Networks

Incremental Non-Rigid Structure-from-Motion with Unknown Focal Length

Deep Adversarial Attention Alignment for Unsupervised Domain Adaptation: the Benefit of Target Expectation Maximization

Image Registration and Predictive Modeling: Learning the Metric on the Space of Diffeomorphisms

Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results

Question-Guided Hybrid Convolution for Visual Question Answering

A Joint Sequence Fusion Model for Video Question Answering and Retrieval

SchiNet: Automatic Estimation of Symptoms of Schizophrenia from Facial Behaviour Analysis

DeepPhys: Video-Based Physiological Measurement Using Convolutional Attention Networks

Multi-Label Zero-Shot Learning with Transfer-Aware Label Embedding Projection

Script Identification in Natural Scene Image and Video Frame using Attention based Convolutional-LSTM Network

Paying Attention to Attention: Highlighting Influential Samples in Sequential Analysis

Visual Reference Resolution using Attention Memory for Visual Dialog

Normalization Before Shaking Toward Learning Symmetrically Distributed Representation Without Margin in Speech Emotion Recognition

Self-produced Guidance for Weakly-supervised Object Localization

Interaction-aware Spatio-temporal Pyramid Attention Networks for Action Classification

Learning Visual Question Answering by Bootstrapping Hard Attention

Attention-based Pyramid Aggregation Network for Visual Place Recognition

Interpretable Visual Question Answering by Visual Grounding from Attention Supervision Mining

Attention is All We Need: Nailing Down Object-centric Attention for Egocentric Activity Recognition

End-to-End Deep Kronecker-Product Matching for Person Re-identification

"Factual" or "Emotional": Stylized Image Captioning with Adaptive Learning and Attention

Pairwise Body-Part Attention for Recognizing Human-Object Interactions

Diverse feature visualizations reveal invariances in early layers of deep neural networks

Connecting Gaze, Scene, and Attention: Generalized Attention Estimation via Joint Modeling of Gaze and Scene Saliency

Zero-shot keyword spotting for visual speech recognition in-the-wild

Deep Imbalanced Attribute Classification using Visual Attention Aggregation

Comparison of methods for early-readmission prediction in a high-dimensional heterogeneous covariates and time-to-event outcome framework

On dynamic ensemble selection and data preprocessing for multi-class imbalance learning

3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration

Attend and Rectify: a Gated Attention Mechanism for Fine-Grained Recovery

Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment

RAIM: Recurrent Attentive and Intensive Model of Multimodal Patient Monitoring Data

R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering

Attention-Guided Curriculum Learning for Weakly Supervised Classification and Localization of Thoracic Diseases on Chest Radiographs

Gradient Band-based Adversarial Training for Generalized Attack Immunity of A3C Path Finding

Bridging the Accuracy Gap for 2-bit Quantized Neural Networks (QNN)

Attention-Based Guided Structured Sparsity of Deep Neural Networks

Image Super-Resolution Using Very Deep Residual Channel Attention Networks

Adding Attentiveness to the Neurons in Recurrent Neural Networks

Deep attention-based classification network for robust depth prediction

DeepDiff: Deep-learning for predicting Differential gene expression from histone modifications

ChestNet: A Deep Neural Network for Classification of Thoracic Diseases on Chest Radiography

Predicting Human Eye Fixations via an LSTM-based Saliency Attentive Model

Jointly learning relevant subgraph patterns and nonlinear models of their indicators

Attention to Refine through Multi-Scales for Semantic Segmentation

On the Robustness of Semantic Segmentation Models to Adversarial Attacks

Video Captioning with Boundary-aware Hierarchical Language Decoding and Joint Video Prediction

Representing a Partially Observed Non-Rigid 3D Human Using Eigen-Texture and Eigen-Deformation

Understanding Visual Ads by Aligning Symbols and Objects using Co-Attention

Iterative Attention Mining for Weakly Supervised Thoracic Disease Pattern Localization in Chest X-Rays

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices

Logical Explanations for Deep Relational Machines Using Relevance Information

Deep Reasoning with Knowledge Graph for Social Relationship Understanding

Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector

Weakly Supervised One-Shot Detection with Attention Similarity Networks

Bayesian methods for low-rank matrix estimation: short survey and theoretical study

Ensemble p-Laplacian Regularization for Remote Sensing Image Recognition

Long-Term On-Board Prediction of People in Traffic Scenes under Uncertainty

A Contrastive Learning Approach to Auroral Identification and Classification

A multi-stage semi-supervised improved deep embedded clustering (MS-SSIDEC) method for bearing fault diagnosis under the situation of insufficient labeled samples

ChangeChip: A Reference-Based Unsupervised Change Detection for PCB Defect Detection

Towards Automatic Threat Detection: A Survey of Advances of Deep Learning within X-ray Security Imaging

Supervised Linear Dimension-Reduction Methods: Review, Extensions, and Comparisons

Toward Realistic Single-View 3D Object Reconstruction with Unsupervised Learning from Multiple Images

Communication Efficient Tensor Factorization for Decentralized Healthcare Networks

Investigate the Correlation of Breast Cancer Dataset using Different Clustering Technique

Efficient channel charting via phase-insensitive distance computation

Unsupervised Monocular Depth Perception: Focusing on Moving Objects

Computer-aided Interpretable Features for Leaf Image Classification

Coverage Hole Detection for mmWave Networks: An Unsupervised Learning Approach

Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma

Generating Cyber Threat Intelligence to Discover Potential Security Threats Using Classification and Topic Modeling

Warp Consistency for Unsupervised Learning of Dense Correspondences

Sparsely Activated Networks: A new method for decomposing and compressing data

Panoramic Depth Estimation via Supervised and Unsupervised Learning in Indoor Scenes

Statistical Learning Guarantees for Compressive Clustering and Compressive Mixture Modeling

Semantic-embedded Unsupervised Spectral Reconstruction from Single RGB Images in the Wild

Unsupervised Person Re-identification with Stochastic Training Strategy

Unsupervised Learning for Target Tracking and Background Subtraction in Satellite Imagery

Unsupervised Driver Behavior Profiling leveraging Recurrent Neural Networks

A Framework for Joint Unsupervised Learning of Cluster-Aware Embedding for Heterogeneous Networks

Unsupervised Learning of Fine Structure Generation for 3D Point Clouds by 2D Projection Matching

Hierarchical View Predictor: Unsupervised 3D Global Feature Learning through Hierarchical Prediction among Unordered Views

Unsupervised Learning of Debiased Representations with Pseudo-Attributes

UPDesc: Unsupervised Point Descriptor Learning for Robust Registration

Unsupervised and Unregistered Hyperspectral Image Super-Resolution with Mutual Dirichlet-Net

The Minimum Edit Arborescence Problem and Its Use in Compressing Graph Collections [Extended Version]

Semi-Supervised Active Learning with Temporal Output Discrepancy

Mixture Model Framework for Traumatic Brain Injury Prognosis Using Heterogeneous Clinical and Outcome Data

Point Cloud Distortion Quantification based on Potential Energy for Human and Machine Perception

A Comparison of Supervised and Unsupervised Deep Learning Methods for Anomaly Detection in Images

Unsupervised Embedding Learning from Uncertainty Momentum Modeling

A novel approach for modelling and classifying sit-to-stand kinematics using inertial sensors

Interpretable Anomaly Detection with DIFFI: Depth-based Isolation Forest Feature Importance

The Three Ensemble Clustering (3EC) Algorithm for Pattern Discovery in Unsupervised Learning

Staying in Shape: Learning Invariant Shape Representations using Contrastive Learning

Continual Contrastive Self-supervised Learning for Image Classification

iMiGUE: An Identity-free Video Dataset for Micro-Gesture Understanding and Emotion Analysis

A Robust Classification-autoencoder to Defend Outliers and Adversaries

Continual Competitive Memory: A Neural System for Online Task-Free Lifelong Learning

Deep Learning for High-Impedance Fault Detection: Convolutional Autoencoders

Generation and frame characteristics of predefined evenly-distributed class centroids for pattern classification

Objective discovery of dominant dynamical processes with intelligible machine learning

Unsupervised Deep Learning by Injecting Low-Rank and Sparse Priors

Learning and Generalization in Overparameterized Normalizing Flows

A Distance-based Separability Measure for Internal Cluster Validation

Deep Contrastive Graph Representation via Adaptive Homotopy Learning

SAR Image Classification Based on Spiking Neural Network through Spike-Time Dependent Plasticity and Gradient Descent

Crowdsourcing via Annotator Co-occurrence Imputation and Provable Symmetric Nonnegative Matrix Factorization

Low Budget Active Learning via Wasserstein Distance: An Integer Programming Approach

Progressive Stage-wise Learning for Unsupervised Feature Representation Enhancement

Unsupervised Feature Learning for Manipulation with Contrastive Domain Randomization

Understand and Improve Contrastive Learning Methods for Visual Representation: A Review

Occlusion-aware Unsupervised Learning of Depth from 4-D Light Fields

Unsupervised detection of mouse behavioural anomalies using two-stream convolutional autoencoders

A survey on Semi-, Self- and Unsupervised Learning for Image Classification

Joint Triplet Autoencoder for Histopathological Colon Cancer Nuclei Retrieval

Unsupervised learning of text line segmentation by differentiating coarse patterns

Self-supervised Graph Neural Networks without explicit negative sampling

Trajectory saliency detection using consistency-oriented latent codes from a recurrent auto-encoder

CDPA: Common and Distinctive Pattern Analysis between High-dimensional Datasets

RelDenClu: A Relative Density based Biclustering Method for identifying non-linear feature relations

Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification

Learning Good State and Action Representations via Tensor Decomposition

Contrastive Learning for Sports Video: Unsupervised Player Classification

Unsupervised Learning of Multi-level Structures for Anomaly Detection

IIoT-Enabled Health Monitoring for Integrated Heat Pump System Using Mixture Slow Feature Analysis

Unsupervised Shape Completion via Deep Prior in the Neural Tangent Kernel Perspective

Contradistinguisher: A Vapnik's Imperative to Unsupervised Domain Adaptation

Scalable Power Control/Beamforming in Heterogeneous Wireless Networks with Graph Neural Networks

Self-supervised Learning of Depth Inference for Multi-view Stereo

TSception: Capturing Temporal Dynamics and Spatial Asymmetry from EEG for Emotion Recognition

Pretrained equivariant features improve unsupervised landmark discovery

Unsupervised Behaviour Analysis and Magnification (uBAM) using Deep Learning

Variational models for signal processing with Graph Neural Networks

A Front-End for Dense Monocular SLAM using a Learned Outlier Mask Prior

Unsupervised Learning of Monocular Depth and Ego-Motion Using Multiple Masks

Unsupervised Learning of 3D Object Categories from Videos in the Wild

Weakly Supervised Temporal Action Localization Through Learning Explicit Subspaces for Action and Context

Deep Unsupervised Learning for Generalized Assignment Problems: A Case-Study of User-Association in Wireless Networks

Unsupervised Learning on Monocular Videos for 3D Human Pose Estimation

Augmenting Supervised Learning by Meta-learning Unsupervised Local Rules

Student-Teacher Feature Pyramid Matching for Unsupervised Anomaly Detection

Unsupervised Learning for Identifying Events in Active Target Experiments

Learning Robust Representation for Clustering through Locality Preserving Variational Discriminative Network

Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs

LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment

PanRep: Graph neural networks for extracting universal node embeddings in heterogeneous graphs

Unsupervised Depth and Ego-motion Estimation for Monocular Thermal Video using Multi-spectral Consistency Loss

Online Orthogonal Dictionary Learning Based on Frank-Wolfe Method

Analysis of feature learning in weight-tied autoencoders via the mean field lens

Improving memory banks for unsupervised learning with large mini-batch, consistency and hard negative mining

Neighborhood Structure Assisted Non-negative Matrix Factorization and its Application in Unsupervised Point-wise Anomaly Detection

Learning based signal detection for MIMO systems with unknown noise statistics

Multi-Source Data Fusion for Cyberattack Detection in Power Systems

Disentangling Observed Causal Effects from Latent Confounders using Method of Moments

DeepMI: A Mutual Information Based Framework For Unsupervised Deep Learning of Tasks

Semantic Segmentation of Remote Sensing Images with Sparse Annotations

Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels

Unsupervised Learning of Visual Features by Contrasting Cluster Assignments

Unsupervised Learning of Category-Specific Symmetric 3D Keypoints from Point Sets

An Internal Cluster Validity Index Using a Distance-based Separability Measure

Learn by Guessing: Multi-Step Pseudo-Label Refinement for Person Re-Identification

Joint Intensity-Gradient Guided Generative Modeling for Colorization

Latent Feature Representation via Unsupervised Learning for Pattern Discovery in Massive Electron Microscopy Image Volumes

Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation

Unsupervised Learning of Global Factors in Deep Generative Models

AI Discovering a Coordinate System of Chemical Elements: Dual Representation by Variational Autoencoders

Active Learning for Node Classification: The Additional Learning Ability from Unlabelled Nodes

Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport

Unsupervised Regionalization of Particle-resolved Aerosol Mixing State Indices on the Global Scale

Video Anomaly Detection by Estimating Likelihood of Representations

Boosting the Performance of Semi-Supervised Learning with Unsupervised Clustering

MUSCLE: Strengthening Semi-Supervised Learning Via Concurrent Unsupervised Learning Using Mutual Information Maximization

reval: a Python package to determine best clustering solutions with stability-based relative clustering validation

Ensemble- and Distance-Based Feature Ranking for Unsupervised Learning

Enriching ImageNet with Human Similarity Judgments and Psychological Embeddings

SNoRe: Scalable Unsupervised Learning of Symbolic Node Representations

An efficient label-free analyte detection algorithm for time-resolved spectroscopy

Unsupervised Multimodal Image Registration with Adaptative Gradient Guidance

Pixel precise unsupervised detection of viral particle proliferation in cellular imaging data

Unsupervised Learning of Depth and Ego-Motion from Cylindrical Panoramic Video with Applications for Virtual Reality

Differentiable Unsupervised Feature Selection based on a Gated Laplacian

Deep Learning based Monocular Depth Prediction: Datasets, Methods and Applications

A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis

Unsupervised Embedding of Hierarchical Structure in Euclidean Space

Deep Shells: Unsupervised Shape Correspondence with Optimal Transport

A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation

Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control

Flame Stability Analysis of Flame Spray Pyrolysis by Artificial Intelligence

Unsupervised deep learning for grading of age-related macular degeneration using retinal fundus images

Simple and Scalable Sparse k-means Clustering via Feature Ranking

Geometry-based Occlusion-Aware Unsupervised Stereo Matching for Autonomous Driving

Efficient Similarity-Preserving Unsupervised Learning using Modular Sparse Distributed Codes and Novelty-Contingent Noise

Deep Autoencoder based Energy Method for the Bending, Vibration, and Buckling Analysis of Kirchhoff Plates

A Comparative Study on Effects of Original and Pseudo Labels for Weakly Supervised Learning for Car Localization Problem

Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences

An Adaptive EM Accelerator for Unsupervised Learning of Gaussian Mixture Models

Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination

Deep Transparent Prediction through Latent Representation Analysis

The Next Big Thing(s) in Unsupervised Machine Learning: Five Lessons from Infant Learning

Unsupervised learning for vascular heterogeneity assessment of glioblastoma based on magnetic resonance imaging: The Hemodynamic Tissue Signature

Symbolic Pregression: Discovering Physical Laws from Distorted Video

Machine Learning and Data Science approach towards trend and predictors analysis of CDC Mortality Data for the USA

Structure-Aware Generation Network for Recipe Generation from Images

Rank-one partitioning: formalization, illustrative examples, and a new cluster enhancing strategy

AUTO3D: Novel view synthesis through unsupervisely learned variational viewpoint and global 3D representation

Unsupervised Surgical Instrument Segmentation via Anchor Generation and Semantic Diffusion

iCVI-ARTMAP: Accelerating and improving clustering using adaptive resonance theory predictive mapping and incremental cluster validity indices

Unsupervised Learning Facial Parameter Regressor for Action Unit Intensity Estimation via Differentiable Renderer

Variational mean-field theory for training restricted Boltzmann machines with binary synapses

TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images

Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs

A Commentary on the Unsupervised Learning of Disentangled Representations

Corella: A Private Multi Server Learning Approach based on Correlated Queries

An unsupervised learning approach to solving heat equations on chip based on Auto Encoder and Image Gradient

Disentangling Multiple Features in Video Sequences using Gaussian Processes in Variational Autoencoders

A new nature inspired modularity function adapted for unsupervised learning involving spatially embedded networks: A comparative analysis

Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models

GraphCL: Contrastive Self-Supervised Learning of Graph Representations

Deep Heterogeneous Autoencoder for Subspace Clustering of Sequential Data

Unsupervised Feature Selection for Tumor Profiles using Autoencoders and Kernel Methods

Deep least-squares methods: an unsupervised learning-based numerical method for solving elliptic PDEs

AutoEmbedder: A semi-supervised DNN embedding system for clustering

AutoTrajectory: Label-free Trajectory Extraction and Prediction from Videos using Dynamic Points

Novel Subtypes of Pulmonary Emphysema Based on Spatially-Informed Lung Texture Learning

Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization

Human Action Attribute Learning From Video Data Using Low-Rank Representations

Unsupervised Learning Consensus Model for Dynamic Texture Videos Segmentation

Abnormal activity capture from passenger flow of elevator based on unsupervised learning and fine-grained multi-label recognition

MiniNet: An extremely lightweight convolutional neural network for real-time unsupervised monocular depth estimation

Pushing the Limit of Unsupervised Learning for Ultrasound Image Artifact Removal

DeepTracking-Net: 3D Tracking with Unsupervised Learning of Continuous Flow

Machine-learning-based methods for output only structural modal identification

A Neural Network for Determination of Latent Dimensionality in Nonnegative Matrix Factorization

Subspace Clustering for Action Recognition with Covariance Representations and Temporal Pruning

Unsupervised Meta-Learning through Latent-Space Interpolation in Generative Models

Semantics-Driven Unsupervised Learning for Monocular Depth and Ego-Motion Estimation

Unsupervised learning of multimodal image registration using domain adaptation with projected Earth Move's discrepancies

An Incremental Clustering Method for Anomaly Detection in Flight Data

Unsupervised Learning for Intrinsic Image Decomposition from a Single Image

Improving Semantic Segmentation through Spatio-Temporal Consistency Learned from Videos

Deep feature fusion for self-supervised monocular depth prediction

Accelerating Generative Neural Networks on Unmodified Deep Learning Processors -- A Software Approach

A Deeper Look at the Unsupervised Learning of Disentangled Representations in $β$-VAE from the Perspective of Core Object Recognition

Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild

Non-exchangeable feature allocation models with sublinear growth of the feature sizes

Learning Invariant Representation for Unsupervised Image Restoration

Learning representations in Bayesian Confidence Propagation neural networks

Unsupervised Learning of Intrinsic Structural Representation Points

Unsupervised Learning of GMM with a Uniform Background Component

Unsupervised Learning of Object Structure and Dynamics from Videos

Dimensionality reduction to maximize prediction generalization capability

Weakly supervised discriminative feature learning with state information for person identification

Deform-GAN:An Unsupervised Learning Model for Deformable Registration

Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration

Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems

A Unified Framework for Tuning Hyperparameters in Clustering Problems

Clustering and Recognition of Spatiotemporal Features through Interpretable Embedding of Sequence to Sequence Recurrent Neural Networks

Imputation and low-rank estimation with Missing Not At Random data

Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition under Reshuffling

Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations

Unsupervised Learning Methods for Visual Place Recognition in Discretely and Continuously Changing Environments

Mode-Assisted Unsupervised Learning of Restricted Boltzmann Machines

The Role of Minimal Complexity Functions in Unsupervised Learning of Semantic Mappings

Single Image Depth Estimation Trained via Depth from Defocus Cues

Unsupervised Domain Adaptation in Person re-ID via k-Reciprocal Clustering and Large-Scale Heterogeneous Environment Synthesis

Domain Independent Unsupervised Learning to grasp the Novel Objects

SuSi: Supervised Self-Organizing Maps for Regression and Classification in Python

Deep Clustering with a Dynamic Autoencoder: From Reconstruction towards Centroids Construction

Fast Estimation of Information Theoretic Learning Descriptors using Explicit Inner Product Spaces

Topic subject creation using unsupervised learning for topic modeling

VarNet: Variational Neural Networks for the Solution of Partial Differential Equations

SPIN: A High Speed, High Resolution Vision Dataset for Tracking and Action Recognition in Ping Pong

Inverse Graphics: Unsupervised Learning of 3D Shapes from Single Images

An Introduction to Probabilistic Spiking Neural Networks: Probabilistic Models, Learning Rules, and Applications

Deep Unsupervised Learning of 3D Point Clouds via Graph Topology Inference and Filtering

A Domain Adaptive Density Clustering Algorithm for Data with Varying Density Distribution

Unsupervised Monocular Depth Prediction for Indoor Continuous Video Streams

Deep-seismic-prior-based reconstruction of seismic data using convolutional neural networks

Structure of Deep Neural Networks with a Priori Information in Wireless Tasks

High-dimensional Nonlinear Profile Monitoring based on Deep Probabilistic Autoencoders

Unsupervised 3D End-to-End Medical Image Registration with Volume Tweening Network

Unsupervised Learning of Depth and Ego-Motion from Cylindrical Panoramic Video

Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning

Total Denoising: Unsupervised Learning of 3D Point Cloud Cleaning

Quantitative stability of optimal transport maps and linearization of the 2-Wasserstein space

An unsupervised approach to Geographical Knowledge Discovery using street level and street network images

Reciprocal Translation between SAR and Optical Remote Sensing Images with Cascaded-Residual Adversarial Networks

Joint Learning of Semantic Alignment and Object Landmark Detection

Supervised Vector Quantized Variational Autoencoder for Learning Interpretable Global Representations

Adversarial Framework for Unsupervised Learning of Motion Dynamics in Videos

Sparse-View X-Ray CT Reconstruction Using $\ell_1$ Prior with Learned Transform

ScieNet: Deep Learning with Spike-assisted Contextual Information Extraction

Augmenting Monte Carlo Dropout Classification Models with Unsupervised Learning Tasks for Detecting and Diagnosing Out-of-Distribution Faults

Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations

MVS^2: Deep Unsupervised Multi-view Stereo with Multi-View Symmetry

Solve fraud detection problem by using graph based learning methods

Unsupervised Learning of Landmarks by Descriptor Vector Exchange

Detecting abnormalities in resting-state dynamics: An unsupervised learning approach

Unsupervised Feature Learning for Point Cloud by Contrasting and Clustering With Graph Convolutional Neural Network

Training products of expert capsules with mixing by dynamic routing

Unsupervised Learning Framework of Interest Point Via Properties Optimization

Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces

Unsupervised Anomaly Localization using Variational Auto-Encoders

Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection

Covariance-based Dissimilarity Measures Applied to Clustering Wide-sense Stationary Ergodic Processes

A Semi-Supervised Self-Organizing Map for Clustering and Classification

Location Anomalies Detection for Connected and Autonomous Vehicles

FAIM -- A ConvNet Method for Unsupervised 3D Medical Image Registration

AVT: Unsupervised Learning of Transformation Equivariant Representations by Autoencoding Variational Transformations

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations

Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics

Learning robust visual representations using data augmentation invariance

Deep Learning-Based Classification Of the Defective Pistachios Via Deep Autoencoder Neural Networks

From Caesar Cipher to Unsupervised Learning: A New Method for Classifier Parameter Estimation

Self-Supervised Deep Learning on Point Clouds by Reconstructing Space

Joint Representation of Multiple Geometric Priors via a Shape Decomposition Model for Single Monocular 3D Pose Estimation

Supervised Discriminative Sparse PCA for Com-Characteristic Gene Selection and Tumor Classification on Multiview Biological Data

A Review of Semi Supervised Learning Theories and Recent Advances

Learning to Optimize with Unsupervised Learning: Training Deep Neural Networks for URLLC

Prediction of Progression to Alzheimer's disease with Deep InfoMax

Lifting AutoEncoders: Unsupervised Learning of a Fully-Disentangled 3D Morphable Model using Deep Non-Rigid Structure from Motion

Deep Collective Matrix Factorization for Augmented Multi-View Learning

Revisit Lmser and its further development based on convolutional layers

Unsupervised Image Matching and Object Discovery as Optimization

Nonparametric Density Estimation for High-Dimensional Data - Algorithms and Applications

EE-AE: An Exclusivity Enhanced Unsupervised Feature Learning Approach

Towards Stable Symbol Grounding with Zero-Suppressed State AutoEncoder

Automatic microscopic cell counting by use of unsupervised adversarial domain adaptation and supervised density regression

Unsupervised Deformable Registration for Multi-Modal Images via Disentangled Representations

An End-to-End Joint Unsupervised Learning of Deep Model and Pseudo-Classes for Remote Sensing Scene Representation

Competitive Training of Mixtures of Independent Deep Generative Models

Unsupervised learning of the brain connectivity dynamic using residual D-net

Incremental Cluster Validity Indices for Hard Partitions: Extensions and Comparative Study

Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey

Enhancing Remote Sensing Image Retrieval with Triplet Deep Metric Learning Network

A Distributed and Approximated Nearest Neighbors Algorithm for an Efficient Large Scale Mean Shift Clustering

Spectral-Spatial Diffusion Geometry for Hyperspectral Image Clustering

Generalization Bounds For Unsupervised and Semi-Supervised Learning With Autoencoders

The Wilderness Area Data Set: Adapting the Covertype data set for unsupervised learning

Learning to compress and search visual data in large-scale systems

Soft Rasterizer: Differentiable Rendering for Unsupervised Single-View Mesh Reconstruction

Unsupervised Learning-based Depth Estimation aided Visual SLAM Approach

From Principal Subspaces to Principal Components with Linear Autoencoders

Variational Inference of Disentangled Latent Concepts from Unlabeled Observations

Effective Feature Learning with Unsupervised Learning for Improving the Predictive Models in Massive Open Online Courses

Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection

Learning to Read by Spelling: Towards Unsupervised Text Recognition

Unsupervised Learning of Monocular Depth Estimation with Bundle Adjustment, Super-Resolution and Clip Loss

Restricted Boltzmann Machines with Gaussian Visible Units Guided by Pairwise Constraints

From biological vision to unsupervised hierarchical sparse coding

Unsupervised learning with GLRM feature selection reveals novel traumatic brain injury phenotypes

Study and Observation of the Variation of Accuracies of KNN, SVM, LMNN, ENN Algorithms on Eleven Different Datasets from UCI Machine Learning Repository

A snapshot on nonstandard supervised learning problems: taxonomy, relationships and methods

Mechanisms of dimensionality reduction and decorrelation in deep neural networks

Incorporating Deep Features in the Analysis of Tissue Microarray Images

Unsupervised Learning of Shape Concepts - From Real-World Objects to Mental Simulation

Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos

A Bayesian Perspective of Statistical Machine Learning for Big Data

Exploiting Capacity of Sewer System Using Unsupervised Learning Algorithms Combined with Dimensionality Reduction

Unsupervised Learning of Shape and Pose with Differentiable Point Clouds

Learning overcomplete, low coherence dictionaries with linear inference

Unsupervised Clustering and Active Learning of Hyperspectral Images with Nonlinear Diffusion

Unsupervised learning from videos using temporal coherency deep networks

A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines

Unique Metric for Health Analysis with Optimization of Clustering Activity and Cross Comparison of Results from Different Approach

Constructing Graph Node Embeddings via Discrimination of Similarity Distributions

Convex Clustering: Model, Theoretical Guarantee and Efficient Algorithm

Unsupervised Hypergraph Feature Selection via a Novel Point-Weighting Framework and Low-Rank Representation

Unsupervised Learning of Artistic Styles with Archetypal Style Analysis

Laplacian Mixture Modeling for Network Analysis and Unsupervised Learning on Graphs

Efficient and Scalable Batch Bayesian Optimization Using K-Means

Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration

Joint Active Learning with Feature Selection via CUR Matrix Decomposition

PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors

Unsupervised/Semi-supervised Deep Learning for Low-dose CT Enhancement

Unsupervised Learning of Latent Physical Properties Using Perception-Prediction Networks

Unsupervised Probabilistic Deformation Modeling for Robust Diffeomorphic Registration

Improving Image Clustering With Multiple Pretrained CNN Feature Extractors

An Unsupervised Learning Classifier with Competitive Error Performance

An Adaptive Cluster-based Filtering Framework for Speckle Reduction of OCT Skin Images

Scalable Factorized Hierarchical Variational Autoencoder Training

Deep Generative Models in the Real-World: An Open Challenge from Medical Imaging

Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints

Unsupervised Learning for Surgical Motion by Learning to Predict the Future

Cluster Naturalistic Driving Encounters Using Deep Unsupervised Learning

Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease

A Classification approach towards Unsupervised Learning of Visual Representations

Neural Inverse Rendering for General Reflectance Photometric Stereo

Unsupervised Learning for Large-Scale Fiber Detection and Tracking in Microscopic Material Images

Incorporating Privileged Information to Unsupervised Anomaly Detection

Clustering - What Both Theoreticians and Practitioners are Doing Wrong

Unsupervised Learning of Neural Networks to Explain Neural Networks

Unsupervised Learning using Pretrained CNN and Associative Memory Bank

Learning Explicit Deep Representations from Deep Kernel Networks

Unsupervised Learning of Sequence Representations by Autoencoders

An Unsupervised Learning Model for Deformable Medical Image Registration

A Deep Unsupervised Learning Approach Toward MTBI Identification Using Diffusion MRI

Seed-Point Detection of Clumped Convex Objects by Short-Range Attractive Long-Range Repulsive Particle Clustering

Towards Training Probabilistic Topic Models on Neuromorphic Multi-chip Systems

Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction

Substitute Teacher Networks: Learning with Almost No Supervision

Supervising Unsupervised Learning with Evolutionary Algorithm in Deep Neural Network

Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification

Unsupervised Learning and Segmentation of Complex Activities from Video

Identification of release sources in advection-diffusion system by machine learning combined with Green function inverse method

Unsupervised Body Part Regression via Spatially Self-ordering Convolutional Neural Networks

Unsupervised Deep Homography: A Fast and Robust Homography Estimation Model

Green Stability Assumption: Unsupervised Learning for Statistics-Based Illumination Estimation

Expectation Learning for Adaptive Crossmodal Stimuli Association

Simultaneous Clustering and Estimation of Heterogeneous Graphical Models

Bayesian Estimation of Multidimensional Latent Variables and Its Asymptotic Accuracy

Learning Sight from Sound: Ambient Sound Provides Supervision for Visual Learning

Introduction to Tensor Decompositions and their Applications in Machine Learning

Unsupervised 3D Reconstruction from a Single Image via Adversarial Learning

Deep Recurrent Gaussian Process with Variational Sparse Spectrum Approximation

Robust Matrix Elastic Net based Canonical Correlation Analysis: An Effective Algorithm for Multi-View Unsupervised Learning

Sparse-TDA: Sparse Realization of Topological Data Analysis for Multi-Way Classification

Unsupervised Learning of Geometry with Edge-aware Depth-Normal Consistency

A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning

Visual Speech Recognition Using PCA Networks and LSTMs in a Tandem GMM-HMM System

Driving Behavior Analysis through CAN Bus Data in an Uncontrolled Environment

Dynamic Label Graph Matching for Unsupervised Video Re-Identification

Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data

ScatterNet Hybrid Deep Learning (SHDL) Network For Object Classification

Limiting the Reconstruction Capability of Generative Neural Network using Negative Learning

Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision

Towards Understanding Sparse Filtering: A Theoretical Perspective

Unsupervised learning of object landmarks by factorized spatial embeddings

Unsupervised Learning of Important Objects from First-Person Videos

Least Square Variational Bayesian Autoencoder with Regularization

Unsupervised Person Re-identification: Clustering and Fine-tuning

Accelerating Eulerian Fluid Simulation With Convolutional Networks

Deep Learning Autoencoder Approach for Handwritten Arabic Digits Recognition

Video Imagination from a Single Image with Transformation Generation

Criteria Sliders: Learning Continuous Database Criteria via Interactive Ranking

Unsupervised Adaptive Re-identification in Open World Dynamic Camera Networks

Unsupervised Learning of Disentangled Representations from Video

Unsupervised Sequence Classification using Sequential Output Statistics

Learning to Associate Words and Images Using a Large-scale Graph

Influence Function and Robust Variant of Kernel Canonical Correlation Analysis

No More Discrimination: Cross City Adaptation of Road Scene Segmenters

Unsupervised object segmentation in video by efficient selection of highly probable positive features

Unsupervised Construction of Human Body Models Using Principles of Organic Computing

Detection, Recognition and Tracking of Moving Objects from Real-time Video via SP Theory of Intelligence and Species Inspired PSO

Deep Unsupervised Similarity Learning using Partially Ordered Sets

Reconstruction of three-dimensional porous media using generative adversarial neural networks

Quad-networks: unsupervised learning to rank for interest point detection

Unsupervised learning from video to detect foreground objects in single images

Efficient Two-Dimensional Sparse Coding Using Tensor-Linear Combination

Multiple Instance Learning with the Optimal Sub-Pattern Assignment Metric

Recursive Autoconvolution for Unsupervised Learning of Convolutional Neural Networks

Statistical mechanics of unsupervised feature learning in a restricted Boltzmann machine with binary synapses

Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data

Anomaly Detection in Bitcoin Network Using Unsupervised Learning Methods

Learning from Label Proportions in Brain-Computer Interfaces: Online Unsupervised Learning with Guarantees

Automatic Discoveries of Physical and Semantic Concepts via Association Priors of Neuron Groups

Meta-Unsupervised-Learning: A supervised approach to unsupervised learning

Clustering with Confidence: Finding Clusters with Statistical Guarantees

From Virtual to Real World Visual Perception using Domain Adaptation -- The DPM as Example

A Non-generative Framework and Convex Relaxations for Unsupervised Learning

Explaining Radiological Emphysema Subtypes with Unsupervised Texture Prototypes: MESA COPD Study

Deep Image Category Discovery using a Transferred Similarity Function

Unsupervised learning of object semantic parts from internal states of CNNs by population encoding

Unsupervised Learning For Effective User Engagement on Social Media

End-to-End Kernel Learning with Supervised Convolutional Kernel Networks

Unsupervised Learning for Physical Interaction through Video Prediction

An image compression and encryption scheme based on deep learning

Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network

Fundamental principles of cortical computation: unsupervised learning with prediction, compression and feedback

Shuffle and Learn: Unsupervised Learning using Temporal Order Verification

Hierarchical Spatial Sum-Product Networks for Action Recognition in Still Images

Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Model

subgraph2vec: Learning Distributed Representations of Rooted Sub-graphs from Large Graphs

Bio-inspired Unsupervised Learning of Visual Features Leads to Robust Invariant Object Recognition

Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification

Unsupervised Learning of Predictors from Unpaired Input-Output Samples

Discovery of Latent Factors in High-dimensional Data Using Tensor Methods

Learning Contextualized Music Semantics from Tags via a Siamese Network

Classification under Streaming Emerging New Classes: A Solution using Completely Random Trees

Recurrent Exponential-Family Harmoniums without Backprop-Through-Time

Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning

Local Binary Pattern for Word Spotting in Handwritten Historical Document

Churn analysis using deep convolutional neural networks and autoencoders

Nested Invariance Pooling and RBM Hashing for Image Instance Retrieval

Robust Kernel (Cross-) Covariance Operators in Reproducing Kernel Hilbert Space toward Kernel Methods

Unsupervised Learning on Neural Network Outputs: with Application in Zero-shot Learning

Unsupervised Learning of Visual Structure using Predictive Generative Networks

Dropout Training of Matrix Factorization and Autoencoder for Link Prediction in Sparse Graphs

Unsupervised Deep Feature Extraction for Remote Sensing Image Classification

Unsupervised Extraction of Video Highlights Via Robust Recurrent Auto-encoders

Multilayer bootstrap network for unsupervised speaker recognition

A Ternary Non-Commutative Latent Factor Model for Scalable Three-Way Real Tensor Completion

Learning Sparse Feature Representations using Probabilistic Quadtrees and Deep Belief Nets

Hierarchical Deep Learning Architecture For 10K Objects Classification

Dependent Indian Buffet Process-based Sparse Nonparametric Nonnegative Matrix Factorization

Multi-Cue Structure Preserving MRF for Unconstrained Video Segmentation

Natural Scene Recognition Based on Superpixels and Deep Boltzmann Machines

Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks

Domain Adaptation Extreme Learning Machines for Drift Compensation in E-nose Systems

The Best of Both Worlds: Combining Data-independent and Data-driven Approaches for Action Recognition

The Boundary Forest Algorithm for Online Supervised and Unsupervised Learning

Lateral Connections in Denoising Autoencoders Support Supervised Learning

Unsupervised learning of clutter-resistant visual representations from natural videos

Unsupervised Feature Learning for Dense Correspondences across Scenes

Learning Arbitrary Statistical Mixtures of Discrete Distributions

Accuracy of Latent-Variable Estimation in Bayesian Semi-Supervised Learning

Unsupervised model compression for multilayer bootstrap networks

An Outlier Detection-based Tree Selection Approach to Extreme Pruning of Random Forests

Classification and its applications for drug-target interaction identification

Minimum message length estimation of mixtures of multivariate Gaussian and von Mises-Fisher distributions

Maximally Informative Hierarchical Representations of High-Dimensional Data

Application of the SP theory of intelligence to the understanding of natural vision and the development of computer vision

Statistical-mechanical analysis of pre-training and fine tuning in deep learning

Conditional Random Field Autoencoders for Unsupervised Structured Prediction

Comment on "Ensemble Projection for Semi-supervised Image Classification"

Unsupervised Parallel Extraction based Texture for Efficient Image Representation

Inducing Language Networks from Continuous Space Word Representations

Stopping Criteria in Contrastive Divergence: Alternatives to the Reconstruction Error

Sparse Coding: A Deep Learning using Unlabeled Data for High - Level Representation

Unsupervised Learning of Invariant Representations in Hierarchical Architectures

Asymptotic Accuracy of Bayes Estimation for Latent Variables with Redundancy

Learned versus Hand-Designed Feature Representations for 3d Agglomeration

Learning with Submodular Functions: A Convex Optimization Perspective

Multiple Kernel Sparse Representations for Supervised and Unsupervised Learning

Learning Mixtures of Arbitrary Distributions over Large Discrete Domains

Optimistic Concurrency Control for Distributed Unsupervised Learning

An Analysis of the Connections Between Layers of Deep Neural Networks

Clustering Unclustered Data: Unsupervised Binary Labeling of Two Datasets Having Different Class Balances

Unsupervised Feature Learning for low-level Local Image Descriptors

An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering

Fuzzy soft rough K-Means clustering approach for gene expression data

Biologically Inspired Spiking Neurons : Piecewise Linear Models and Digital Implementation

Exploiting compositionality to explore a large space of model structures

Super-resolution using Sparse Representations over Learned Dictionaries: Reconstruction of Brain Structure using Electron Microscopy

Learning Probability Measures with respect to Optimal Transport Metrics

Are You Imitating Me? Unsupervised Sparse Modeling for Group Activity Analysis from a Single Video

Building high-level features using large scale unsupervised learning

Efficient Methods for Unsupervised Learning of Probabilistic Models

Bregman divergence as general framework to estimate unnormalized statistical models

Nonnegative Matrix Factorization for Semi-supervised Dimensionality Reduction

An Analytical Study on Behavior of Clusters Using K Means, EM and K* Means Algorithm

SparseCodePicking: feature extraction in mass spectrometry using sparse coding algorithms

A Unified Semi-Supervised Dimensionality Reduction Framework for Manifold Learning

Combining Supervised and Unsupervised Learning for GIS Classification

Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning

Automatic Pattern Classification by Unsupervised Learning Using Dimensionality Reduction of Data with Mirroring Neural Networks

Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews

Unsupervised Learning of Semantic Orientation from a Hundred-Billion-Word Corpus

Principal Manifolds and Nonlinear Dimension Reduction via Local Tangent Space Alignment

Not Color Blind: AI Predicts Racial Identity from Black and White Retinal Vessel Segmentations

SAND-mask: An Enhanced Gradient Masking Strategy for the Discovery of Invariances in Domain Generalization

Weakly-Supervised Monocular Depth Estimationwith Resolution-Mismatched Data

A Method For Adding Motion-Blur on Arbitrary Objects By using Auto-Segmentation and Color Compensation Techniques

Deep Edge-Aware Interactive Colorization against Color-Bleeding Effects

Tensor Pooling Driven Instance Segmentation Framework for Baggage Threat Recognition

Spatial-Separated Curve Rendering Network for Efficient and High-Resolution Image Harmonization

Predicting 3D shapes, masks, and properties of materials, liquids, and objects inside transparent containers, using the TransProteus CGI dataset

Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color

A deep learning guided memetic framework for graph coloring problems

Image-based Plant Disease Diagnosis with Unsupervised Anomaly Detection Based on Reconstructability of Colors

Multi-view Image-based Hand Geometry Refinement using Differentiable Monte Carlo Ray Tracing

A realistic approach to generate masked faces applied on two novel masked face recognition data sets

Spatially varying white balancing for mixed and non-uniform illuminants

Shot boundary detection method based on a new extensive dataset and mixed features

Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering

Detecting Mitosis against Domain Shift using a Fused Detector and Deep Ensemble Classification Model for MIDOG Challenge

Personalizing image enhancement for critical visual tasks: improved legibility of papyri using color processing and visual illusions

Product-oriented Machine Translation with Cross-modal Cross-lingual Pre-training

An Adaptive Framework for Learning Unsupervised Depth Completion

Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition

Graph-LDA: Graph Structure Priors to Improve the Accuracy in Few-Shot Classification

Towards Real-world X-ray Security Inspection: A High-Quality Benchmark and Lateral Inhibition Module for Prohibited Items Detection

Classification of Urban Morphology with Deep Learning: Application on Urban Vitality

Self-supervision on Unlabelled OR Data for Multi-person 2D/3D Human Pose Estimation

MVOR: A Multi-view RGB-D Operating Room Dataset for 2D and 3D Human Pose Estimation

Evaluation of Correctness in Unsupervised Many-to-Many Image Translation

Rendering and Tracking the Directional TSDF: Modeling Surface Orientation for Coherent Maps

Spatially and color consistent environment lighting estimation using deep neural networks for mixed reality

FCFR-Net: Feature Fusion based Coarse-to-Fine Residual Learning for Depth Completion

LIF-Seg: LiDAR and Camera Image Fusion for 3D LiDAR Semantic Segmentation

Spatio-Temporal Representation Factorization for Video-based Person Re-Identification

RIN: Textured Human Model Recovery and Imitation with a Single Image

Focusing on Persons: Colorizing Old Images Learning from Modern Historical Movies

NeuLF: Efficient Novel View Synthesis with Neural 4D Light Field

Probing the State of the Art: A Critical Look at Visual Representation Evaluation

DiagViB-6: A Diagnostic Benchmark Suite for Vision Models in the Presence of Shortcut and Generalization Opportunities

ReDAL: Region-based and Diversity-aware Active Learning for Point Cloud Semantic Segmentation

High-frequency shape recovery from shading by CNN and domain adaptation

Essential Features: Content-Adaptive Pixel Discretization to Improve Model Robustness to Adaptive Adversarial Attacks

HyperColor: A HyperNetwork Approach for Synthesizing Auto-colored 3D Models for Game Scenes Population

SDEdit: Image Synthesis and Editing with Stochastic Differential Equations

Enhancing Underwater Image via Adaptive Color and Contrast Enhancement, and Denoising

No-Reference Quality Assessment for 3D Colored Point Cloud and Mesh Models

Attribute-based Explanations of Non-Linear Embeddings of High-Dimensional Data

A Multiple-Instance Learning Approach for the Assessment of Gallbladder Vascularity from Laparoscopic Images

Vehicle-Rear: A New Dataset to Explore Feature Fusion for Vehicle Identification Using Convolutional Neural Networks

Estimation of excess air coefficient on coal combustion processes via gauss model and artificial neural network

Monocular Visual Analysis for Electronic Line Calling of Tennis Games

Occlusion-Aware Depth Estimation with Adaptive Normal Constraints

RGBD-Net: Predicting color and depth images for novel views synthesis

StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation

Pragmatic Image Compression for Human-in-the-Loop Decision-Making

E-PixelHop: An Enhanced PixelHop Method for Object Classification

Predictive Modeling in the Presence of Nuisance-Induced Spurious Correlations

Non-Local Representation based Mutual Affine-Transfer Network for Photorealistic Stylization

A Structured Analysis of the Video Degradation Effects on the Performance of a Machine Learning-enabled Pedestrian Detector

Multimodal End-to-End Learning for Autonomous Steering in Adverse Road and Weather Conditions

Making Images Real Again: A Comprehensive Survey on Deep Image Composition

MatchVIE: Exploiting Match Relevancy between Entities for Visual Information Extraction

Towards Automated Biometric Identification of Sea Turtles (Chelonia mydas)

Creating A New Color Space utilizing PSO and FCM to Perform Skin Detection by using Neural Network and ANFIS

Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanations

Supervised learning for crop/weed classification based on color and texture features

PatchNet: Unsupervised Object Discovery based on Patch Embedding

Encouraging Intra-Class Diversity Through a Reverse Contrastive Loss for Better Single-Source Domain Generalization

Learning to Aggregate and Personalize 3D Face from In-the-Wild Photo Collection

Cluster-guided Asymmetric Contrastive Learning for Unsupervised Person Re-Identification

Discerning the painter's hand: machine learning on surface topography

Finding Physical Adversarial Examples for Autonomous Driving with Fast and Differentiable Image Compositing

A machine learning pipeline for aiding school identification from child trafficking images

Segmentation and ABCD rule extraction for skin tumors classification

Chromatic and spatial analysis of one-pixel attacks against an image classifier

Ukiyo-e Analysis and Creativity with Attribute and Geometry Annotation

Incentivized Bandit Learning with Self-Reinforcing User Preferences

An Efficient Style Virtual Try on Network for Clothing Business Industry

Parallelized Computation and Backpropagation Under Angle-Parametrized Orthogonal Matrices

Fit without fear: remarkable mathematical phenomena of deep learning through the prism of interpolation

cofga: A Dataset for Fine Grained Classification of Objects from Aerial Imagery

There and Back Again: Self-supervised Multispectral Correspondence Estimation

Automatic Test Suite Generation for Key-Points Detection DNNs using Many-Objective Search (Experience Paper)

Learning Better Visual Dialog Agents with Pretrained Visual-Linguistic Representation

Crowd Counting by Self-supervised Transfer Colorization Learning and Global Prior Classification

Low-Rank and Sparse Enhanced Tucker Decomposition for Tensor Completion

A Multi-spectral Dataset for Evaluating Motion Estimation Systems

Instance segmentation of fallen trees in aerial color infrared imagery using active multi-contour evolution with fully convolutional network-based intensity priors

Multi-modal Bifurcated Network for Depth Guided Image Relighting

Detection and Longitudinal Tracking of Pigmented Skin Lesions in 3D Total-Body Skin Textured Meshes

Analysis of Manual and Automated Skin Tone Assignments for Face Recognition Applications

SPSG: Self-Supervised Photometric Scene Generation from RGB-D Scans

Neural Ray-Tracing: Learning Surfaces and Reflectance for Relighting and View Synthesis

Online Multi-Object Tracking with delta-GLMB Filter based on Occlusion and Identity Switch Handling

Sketch-QNet: A Quadruplet ConvNet for Color Sketch-based Image Retrieval

Training Deep Learning Based Denoisers without Ground Truth Data

Open-Edit: Open-Domain Image Manipulation with Open-Vocabulary Instructions

Evaluating Deep Neural Networks Trained on Clinical Images in Dermatology with the Fitzpatrick 17k Dataset

Image Inpainting with External-internal Learning and Monochromic Bottleneck

Invisible Perturbations: Physical Adversarial Examples Exploiting the Rolling Shutter Effect

Occlusion-aware Visual Tracker using Spatial Structural Information and Dominant Features

Monocular Real-time Full Body Capture with Inter-part Correlations

Deep Denoising of Flash and No-Flash Pairs for Photography in Low-Light Environments

Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes

Holistic Image Manipulation Detection using Pixel Co-occurrence Matrices

A Novel Unified Model for Multi-exposure Stereo Coding Based on Low Rank Tucker-ALS and 3D-HEVC

Modulated Periodic Activations for Generalizable Local Functional Representations

A Sparse Representation Based Joint Demosaicing Method for Single-Chip Polarized Color Sensor

A Person Re-identification Data Augmentation Method with Adversarial Defense Effect

Robust Semantic Interpretability: Revisiting Concept Activation Vectors

Test-Time Adaptation for Super-Resolution: You Only Need to Overfit on a Few More Images

IronMask: Modular Architecture for Protecting Deep Face Template

Lipstick ain't enough: Beyond Color Matching for In-the-Wild Makeup Transfer

Unconstrained Face Recognition using ASURF and Cloud-Forest Classifier optimized with VLAD

A Combined Deep Learning based End-to-End Video Coding Architecture for YUV Color Space

Scalable Visual Attribute Extraction through Hidden Layers of a Residual ConvNet

Remote Sensing Image Translation via Style-Based Recalibration Module and Improved Style Discriminator

Ego2Hands: A Dataset for Egocentric Two-hand Segmentation and Detection

AdaStereo: A Simple and Efficient Approach for Adaptive Stereo Matching

Hierarchically Compositional Tasks and Deep Convolutional Networks

Learning Scene Structure Guidance via Cross-Task Knowledge Transfer for Single Depth Super-Resolution

Degrade is Upgrade: Learning Degradation for Low-light Image Enhancement

WheatNet: A Lightweight Convolutional Neural Network for High-throughput Image-based Wheat Head Detection and Counting

You Only Need Adversarial Supervision for Semantic Image Synthesis

The VISIONE Video Search System: Exploiting Off-the-Shelf Text Search Engines for Large-Scale Video Retrieval

PENet: Towards Precise and Efficient Image Guided Depth Completion

Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser

Fast block-coordinate Frank-Wolfe algorithm for semi-relaxed optimal transport

CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds

Color-Coded Symbology and New Computer Vision Tool to Predict the Historical Color Pallets of the Renaissance Oil Artworks

Dynamic Object Removal and Spatio-Temporal RGB-D Inpainting via Geometry-Aware Adversarial Learning

DeepCorn: A Semi-Supervised Deep Learning Method for High-Throughput Image-Based Corn Kernel Counting and Yield Estimation

SFANet: A Spectrum-aware Feature Augmentation Network for Visible-Infrared Person Re-Identification

FaceController: Controllable Attribute Editing for Face in the Wild

Out-of-distribution Prediction with Invariant Risk Minimization: The Limitation and An Effective Fix

Weed Density and Distribution Estimation for Precision Agriculture using Semi-Supervised Learning

Culture-inspired Multi-modal Color Palette Generation and Colorization: A Chinese Youth Subculture Case

Leaf Image-based Plant Disease Identification using Color and Texture Features

Facial Manipulation Detection Based on the Color Distribution Analysis in Edge Region

Enabling energy efficient machine learning on a Ultra-Low-Power vision sensor for IoT

Global-Local Propagation Network for RGB-D Semantic Segmentation

Depth-Enhanced Feature Pyramid Network for Occlusion-Aware Verification of Buildings from Oblique Images

FWB-Net:Front White Balance Network for Color Shift Correction in Single Image Dehazing via Atmospheric Light Estimation

Real Time Incremental Foveal Texture Mapping for Autonomous Vehicles

Context-Aware Image Denoising with Auto-Threshold Canny Edge Detection to Suppress Adversarial Perturbation

Joint Demosaicking and Denoising in the Wild: The Case of Training Under Ground Truth Uncertainty

BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration

Combining Deep Learning and Mathematical Morphology for Historical Map Segmentation

NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections

Support Vector Machine and YOLO for a Mobile Food Grading System

Recovery of underdrawings and ghost-paintings via style transfer by deep convolutional neural networks: A digital tool for art scholars

Low Light Image Enhancement via Global and Local Context Modeling

Shed Various Lights on a Low-Light Image: Multi-Level Enhancement Guided by Arbitrary References

A Switched View of Retinex: Deep Self-Regularized Low-Light Image Enhancement

Assigning Apples to Individual Trees in Dense Orchards using 3D Color Point Clouds

Color Channel Perturbation Attacks for Fooling Convolutional Neural Networks and A Defense Against Such Attacks

Fairkit, Fairkit, on the Wall, Who's the Fairest of Them All? Supporting Data Scientists in Training Fair Models

Overcoming Language Priors with Self-supervised Learning for Visual Question Answering

FAWA: Fast Adversarial Watermark Attack on Optical Character Recognition (OCR) Systems

WDNet: Watermark-Decomposition Network for Visible Watermark Removal

Deep Learning for Material recognition: most recent advances and open challenges

Seeing eye-to-eye? A comparison of object recognition performance in humans and deep convolutional neural networks under image manipulation

An Overview of Depth Cameras and Range Scanners Based on Time-of-Flight Technologies

Video Camera Identification from Sensor Pattern Noise with a Constrained ConvNet

Color-related Local Binary Pattern: A Learned Local Descriptor for Color Image Recognition

Physics-Guided Spoof Trace Disentanglement for Generic Face Anti-Spoofing

Perceptual Robust Hashing for Color Images with Canonical Correlation Analysis

Sparse Fooling Images: Fooling Machine Perception through Unrecognizable Images

Geo-PIFu: Geometry and Pixel Aligned Implicit Functions for Single-view Human Reconstruction

PeR-ViS: Person Retrieval in Video Surveillance using Semantic Description

BoxInst: High-Performance Instance Segmentation with Box Annotations

Learning Two-Stream CNN for Multi-Modal Age-related Macular Degeneration Categorization

Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training

Open Source 3-D Filament Diameter Sensor for Recycling, Winding and Additive Manufacturing Machines

Fast, Self Supervised, Fully Convolutional Color Normalization of H&E Stained Images

A smartphone based multi input workflow for non-invasive estimation of haemoglobin levels using machine learning techniques

Depth-Aware Action Recognition: Pose-Motion Encoding through Temporal Heatmaps

Robust Correlation Tracking via Multi-channel Fused Features and Reliable Response Map

Reference-Based Video Colorization with Spatiotemporal Correspondence

Multi-Scale Progressive Fusion Learning for Depth Map Super-Resolution

Deep learning model trained on mobile phone-acquired frozen section images effectively detects basal cell carcinoma

A Genetic Algorithm Approach for ImageRepresentation Learning through Color Quantization

Deep Snapshot HDR Imaging Using Multi-Exposure Color Filter Array

Whose hand is this? Person Identification from Egocentric Hand Gestures

NeurIPS 2019 Disentanglement Challenge: Improved Disentanglement through Learned Aggregation of Convolutional Feature Maps

Non-Local Robust Quaternion Matrix Completion for Large-Scale Color Images and Videos Inpainting

Deep multi-modal networks for book genre classification based on its cover

Understanding the hand-gestures using Convolutional Neural Networks and Generative Adversial Networks

Efficient Robust Watermarking Based on Quaternion Singular Value Decomposition and Coefficient Pair Selection

AOT: Appearance Optimal Transport Based Identity Swapping for Forgery Detection

The Origins and Prevalence of Texture Bias in Convolutional Neural Networks

Leveraging Adaptive Color Augmentation in Convolutional Neural Networks for Deep Skin Lesion Segmentation

Automatic joint damage quantification using computer vision and deep learning

Population-based Gradient Descent Weight Learning for Graph Coloring Problems

Scribble-based Weakly Supervised Deep Learning for Road Surface Extraction from Remote Sensing Images

High-Throughput Image-Based Plant Stand Count Estimation Using Convolutional Neural Networks

Homography Estimation with Convolutional Neural Networks Under Conditions of Variance

Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional Entropies

Poisoned classifiers are not only backdoored, they are fundamentally broken

Introducing Pose Consistency and Warp-Alignment for Self-Supervised 6D Object Pose Estimation in Color Images

An Empirical Analysis of Visual Features for Multiple Object Tracking in Urban Scenes

A Human Eye-based Text Color Scheme Generation Method for Image Synthesis

Audio-Visual Self-Supervised Terrain Type Discovery for Mobile Platforms

Increasing the Robustness of Semantic Segmentation Models with Painting-by-Numbers

SDE-AWB: a Generic Solution for 2nd International Illumination Estimation Challenge

A deep learning based interactive sketching system for fashion images design

Computational analysis of pathological image enables interpretable prediction for microsatellite instability

Trainable Structure Tensors for Autonomous Baggage Threat Detection Under Extreme Occlusion

Generalized Two-Dimensional Quaternion Principal Component Analysis with Weighting for Color Image Recognition

AIM 2020: Scene Relighting and Illumination Estimation Challenge

Implicit Feature Networks for Texture Completion from Partial 3D Data

Light Direction and Color Estimation from Single Image with Deep Regression

Event-based visual place recognition with ensembles of temporal windows

Data Augmentation and Clustering for Vehicle Make/Model Classification

Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction

Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks

3D dynamic hand gestures recognition using the Leap Motion sensor and convolutional neural networks

A Systematic Evaluation: Fine-Grained CNN vs. Traditional CNN Classifiers

Measurement-driven Security Analysis of Imperceptible Impersonation Attacks

CA-GAN: Weakly Supervised Color Aware GAN for Controllable Makeup Transfer

Improving Multispectral Pedestrian Detection by Addressing Modality Imbalance Problems

A Deep Convolutional Neural Network for the Detection of Polyps in Colonoscopy Images

Pixel-level Corrosion Detection on Metal Constructions by Fusion of Deep Learning Semantic and Contour Segmentation

Dual In-painting Model for Unsupervised Gaze Correction and Animation in the Wild

Adversarial Color Enhancement: Generating Unrestricted Adversarial Images by Optimizing a Color Filter

Fully Automated Photogrammetric Data Segmentation and Object Information Extraction Approach for Creating Simulation Terrain

PROPEL: Probabilistic Parametric Regression Loss for Convolutional Neural Networks

Transmission Map and Atmospheric Light Guided Iterative Updater Network for Single Image Dehazing

NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

Color-complexity enabled exhaustive color-dots identification and spatial patterns testing in images

Crowdsourced 3D Mapping: A Combined Multi-View Geometry and Self-Supervised Learning Approach

Deep Models and Shortwave Infrared Information to Detect Face Presentation Attacks

Monte Carlo Dropout Ensembles for Robust Illumination Estimation

Reducing Language Biases in Visual Question Answering with Visually-Grounded Question Encoder

Correlation filter tracking with adaptive proposal selection for accurate scale estimation

A new approach to descriptors generation for image retrieval by analyzing activations of deep neural network layers

Disentanglement of Color and Shape Representations for Continual Learning

Towards High-Fidelity 3D Face Reconstruction from In-the-Wild Images Using Graph Convolutional Networks

Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal Transport

Development and Validation of a Novel Prognostic Model for Predicting AMD Progression Using Longitudinal Fundus Images

StyPath: Style-Transfer Data Augmentation For Robust Histology Image Classification

Animated GIF optimization by adaptive color local table management

Interpretation of ResNet by Visualization of Preferred Stimulus in Receptive Fields

Monocular Vision based Crowdsourced 3D Traffic Sign Positioning with Unknown Camera Intrinsics and Distortion Coefficients

Comparative Study and Optimization of Feature-Extraction Techniques for Content based Image Retrieval

The Scattering Compositional Learner: Discovering Objects, Attributes, Relationships in Analogical Reasoning

Enhancing Underexposed Photos using Perceptually Bidirectional Similarity

Weakly Supervised Domain Adaptation for Built-up Region Segmentation in Aerial and Satellite Imagery

Automatic Page Segmentation Without Decompressing the Run-Length Compressed Text Documents

Forgery Detection in a Questioned Hyperspectral Document Image using K-means Clustering

A Novel Nudity Detection Algorithm for Web and Mobile Application Development

Automated Stitching of Coral Reef Images and Extraction of Features for Damselfish Shoaling Behavior Analysis

CIE XYZ Net: Unprocessing Images for Low-Level Computer Vision Tasks

The color out of space: learning self-supervised representations for Earth Observation imagery

Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination

Sky Optimization: Semantically aware image processing of skies in low-light photography

Towards Verifying Robustness of Neural Networks Against Semantic Perturbations

PCAAE: Principal Component Analysis Autoencoder for organising the latent space of generative networks

Early Blindness Detection Based on Retinal Images Using Ensemble Learning

Partial Optimal Transport with Applications on Positive-Unlabeled Learning

A Hybrid Framework for Matching Printing Design Files to Product Photos

Scene relighting with illumination estimation in the latent space on an encoder-decoder scheme

Fast Enhancement for Non-Uniform Illumination Images using Light-weight CNNs

FCN+RL: A Fully Convolutional Network followed by Refinement Layers to Offline Handwritten Signature Segmentation

Leveraging Photogrammetric Mesh Models for Aerial-Ground Feature Point Matching Toward Integrated 3D Reconstruction

Deepzzle: Solving Visual Jigsaw Puzzles with Deep Learning andShortest Path Optimization

A New Unified Method for Detecting Text from Marathon Runners and Sports Players in Video

Style Normalization and Restitution for Generalizable Person Re-identification

Reducing Overlearning through Disentangled Representations by Suppressing Unknown Tasks

Tensor completion via nonconvex tensor ring rank minimization with guaranteed convergence

Recognition of 26 Degrees of Freedom of Hands Using Model-based approach and Depth-Color Images

A Novel Deep Learning Pipeline for Retinal Vessel Detection in Fluorescein Angiography

NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results

Multi-Target Deep Learning for Algal Detection and Classification

Small, Sparse, but Substantial: Techniques for Segmenting Small Agricultural Fields Using Sparse Ground Data

Domain Siamese CNNs for Sparse Multispectral Disparity Estimation

Channel-by-Channel Demosaicking Networks with Embedded Spectral Correlation

Towards Real-Time DNN Inference on Mobile Platforms with Model Pruning and Compiler Optimization

Super-Resolution-based Snake Model -- An Unsupervised Method for Large-Scale Building Extraction using Airborne LiDAR Data and Optical Image

Conservative Plane Releasing for Spatial Privacy Protection in Mixed Reality

Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology

Constrained Multi-shape Evolution for Overlapping Cytoplasm Segmentation

Intuitive, Interactive Beard and Hair Synthesis with Generative Models

BlendedMVS: A Large-scale Dataset for Generalized Multi-view Stereo Networks

Cross-domain Correspondence Learning for Exemplar-based Image Translation

Neural Voxel Renderer: Learning an Accurate and Controllable Rendering Tool

Towards Lifelong Self-Supervision For Unpaired Image-to-Image Translation

Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color Distance

Enhanced Self-Perception in Mixed Reality: Egocentric Arm Segmentation and Database with Automatic Labelling

Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net

Colored Noise Injection for Training Adversarially Robust Neural Networks

3dDepthNet: Point Cloud Guided Depth Completion Network for Sparse Depth and Single Color Image

Estimation of Orofacial Kinematics in Parkinson's Disease: Comparison of 2D and 3D Markerless Systems for Motion Tracking

A model of figure ground organization incorporating local and global cues

Large-Scale Optimal Transport via Adversarial Training with Cycle-Consistency

Using an ensemble color space model to tackle adversarial examples

Texture Superpixel Clustering from Patch-based Nearest Neighbor Matching

I-ViSE: Interactive Video Surveillance as an Edge Service using Unsupervised Feature Queries

Dense Dilated Convolutions Merging Network for Land Cover Classification

Learning with minibatch Wasserstein : asymptotic and gradient properties

CLEVRER: CoLlision Events for Video REpresentation and Reasoning

Blind Universal Bayesian Image Denoising with Gaussian Noise Level Learning

Multi-task Deep Learning for Real-Time 3D Human Pose Estimation and Action Recognition

Matching Neuromorphic Events and Color Images via Adversarial Learning

Supervised Dimensionality Reduction and Visualization using Centroid-encoder

Comparing Different Deep Learning Architectures for Classification of Chest Radiographs

Domain Adaptive Adversarial Learning Based on Physics Model Feedback for Underwater Image Enhancement

Deep-HR: Fast Heart Rate Estimation from Face Video Under Realistic Conditions

3DPIFCM Novel Algorithm for Segmentation of Noisy Brain MRI Images

Attacking Optical Character Recognition (OCR) Systems with Adversarial Watermarks

Grape detection, segmentation and tracking using deep neural networks and three-dimensional association

Person Re-identification by Contour Sketch under Moderate Clothing Change

Simultaneous Enhancement and Super-Resolution of Underwater Imagery for Improved Visual Perception

Medicine Strip Identification using 2-D Cepstral Feature Extraction and Multiclass Classification Methods

ChromaGAN: Adversarial Picture Colorization with Semantic Class Distribution

Deformable Generator Network: Unsupervised Disentanglement of Appearance and Geometry

A Novel Inspection System For Variable Data Printing Using Deep Learning

Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces

Compositional Hierarchical Tensor Factorization: Representing Hierarchical Intrinsic and Extrinsic Causal Factors

Image retrieval approach based on local texture information derived from predefined patterns and spatial domain information

Robust Visual Tracking via Implicit Low-Rank Constraints and Structural Color Histograms

3D Face Reconstruction Using Color Photometric Stereo with Uncalibrated Near Point Lights

Tifinagh-IRCAM Handwritten character recognition using Deep learning

Fingerprint Spoof Detection: Temporal Analysis of Image Sequence

Hue-Net: Intensity-based Image-to-Image Translation with Differentiable Histogram Loss Functions

Identifying Recurring Patterns with Deep Neural Networks for Natural Image Denoising

Generating and Exploiting Probabilistic Monocular Depth Estimates

Learn to See by Events: Color Frame Synthesis from Event and RGB Cameras

Deep Learning-based Hybrid Graph-Coloring Algorithm for Register Allocation

A Novel Hybrid Scheme Using Genetic Algorithms and Deep Learning for the Reconstruction of Portuguese Tile Panels

Visual Illusions Also Deceive Convolutional Neural Networks: Analysis and Implications

Efficient Convolutional Neural Networks for Depth-Based Multi-Person Pose Estimation

FusionMapping: Learning Depth Prediction with Monocular Images and 2D Laser Scans

An End-to-end Framework for Unconstrained Monocular 3D Hand Pose Estimation

Real-Time 3D Model Tracking in Color and Depth on a Single CPU Core

CSPN++: Learning Context and Resource Aware Convolutional Spatial Propagation Networks for Depth Completion

Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer

DermGAN: Synthetic Generation of Clinical Skin Images with Pathology

Sibling Neural Estimators: Improving Iterative Image Decoding with Gradient Communication

Leveraging Multi-view Image Sets for Unsupervised Intrinsic Image Decomposition and Highlight Separation

Approximation Ratios of Graph Neural Networks for Combinatorial Problems

DeepBlindness: Fast Blindness Map Estimation and Blindness Type Classification for Outdoor Scene from Single Color Image

Visual Appearance Based Person Retrieval in Unconstrained Environment Videos

Conditional out-of-sample generation for unpaired data using trVAE

Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets

Low Shot Learning with Untrained Neural Networks for Imaging Inverse Problems

Cascaded Generation of High-quality Color Visible Face Images from Thermal Captures

Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection

Enhanced Human-Machine Interaction by Combining Proximity Sensing with Global Perception

Coloring the Black Box: Visualizing neural network behavior with a self-introspective model

RPM-Net: Robust Pixel-Level Matching Networks for Self-Supervised Video Object Segmentation

REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs

Defective samples simulation through Neural Style Transfer for automatic surface defect segment

Metric Pose Estimation for Human-Machine Interaction Using Monocular Vision

Colored Transparent Object Matting from a Single Image Using Deep Learning

IIITM Face: A Database for Facial Attribute Detection in Constrained and Simulated Unconstrained Environments

Diminishing the Effect of Adversarial Perturbations via Refining Feature Representation

Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis

Region-wise Generative Adversarial ImageInpainting for Large Missing Areas

Multi-scale Dynamic Feature Encoding Network for Image Demoireing

Adversarial Learning of General Transformations for Data Augmentation

Biometric Face Presentation Attack Detection with Multi-Channel Convolutional Neural Network

A Collaborative Approach using Ridge-Valley Minutiae for More Accurate Contactless Fingerprint Identification

Fast Fourier Color Constancy and Grayness Index for ISPA Illumination Estimation Challenge

MetalGAN: a Cluster-based Adaptive Training for Few-Shot Adversarial Colorization

Road Mapping In LiDAR Images Using A Joint-Task Dense Dilated Convolutions Merging Network

Faster and Accurate Classification for JPEG2000 Compressed Images in Networked Applications

Dense Dilated Convolutions Merging Network for Semantic Mapping of Remote Sensing Images

CorNet: Generic 3D Corners for 6D Pose Estimation of New Objects without Retraining

Unsupervised Domain-Adaptive Person Re-identification Based on Attributes

Object-Driven Multi-Layer Scene Decomposition From a Single Image

Appearance invariant Entry-Exit matching using visual soft biometric traits

EyeNet: A Multi-Task Network for Off-Axis Eye Gaze Estimation and User Understanding

U-CATCH: Using Color ATtribute of image patCHes in binary descriptors

A Comparative Study of Filtering Approaches Applied to Color Archival Document Images

Tag2Pix: Line Art Colorization Using Text Tag With SECat and Changing Loss

Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks

Difficulty Classification of Mountainbike Downhill Trails utilizing Deep Neural Networks

Fully Automatic Video Colorization with Self-Regularization and Diversity

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning

ShapeCaptioner: Generative Caption Network for 3D Shapes by Learning a Mapping from Parts Detected in Multiple Views to Sentences

LED2Net: Deep Illumination-aware Dehazing with Low-light and Detail Enhancement

Implicit Dual-domain Convolutional Network for Robust Color Image Compression Artifact Reduction

VARENN: Graphical representation of spatiotemporal data and application to climate studies

LYTNet: A Convolutional Neural Network for Real-Time Pedestrian Traffic Lights and Zebra Crossing Recognition for the Visually Impaired

Polyp Detection and Segmentation using Mask R-CNN: Does a Deeper Feature Extractor CNN Always Perform Better?

High Accuracy Classification of White Blood Cells using TSLDA Classifier and Covariance Features

Unsupervised Automatic Building Extraction Using Active Contour Model on Unregistered Optical Imagery and Airborne LiDAR Data

DeepIlluminance: Contextual Illuminance Estimation via Deep Neural Networks

Semi-supervised Feature-Level Attribute Manipulation for Fashion Image Retrieval

Material Based Object Tracking in Hyperspectral Videos: Benchmark and Algorithms

Single-Camera Basketball Tracker through Pose and Semantic Feature Fusion

Copula Representations and Error Surface Projections for the Exclusive Or Problem

Learning to Predict Robot Keypoints Using Artificially Generated Images

An Integrated Image Filter for Enhancing Change Detection Results

Nature Inspired Dimensional Reduction Technique for Fast and Invariant Visual Feature Extraction

CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark

Spatio-thermal depth correction of RGB-D sensors based on Gaussian Processes in real-time

Serif or Sans: Visual Font Analytics on Book Covers and Online Advertisements

Place recognition in gardens by learning visual representations: data set and benchmark analysis

Color Texture Classification Based on Proposed Impulse-Noise Resistant Color Local Binary Patterns and Significant Points Selection Algorithm

Artistic Enhancement and Style Transfer of Image Edges using Directional Pseudo-coloring

Object Sorting Using a Global Texture-Shape 3D Feature Descriptor

Learning to Reconstruct and Understand Indoor Scenes from Sparse Views

Floors are Flat: Leveraging Semantics for Real-Time Surface Normal Prediction

Fully Using Classifiers for Weakly Supervised Semantic Segmentation with Modified Cues

Image-to-Image Translation via Group-wise Deep Whitening-and-Coloring Transformation

Coloring With Limited Data: Few-Shot Colorization via Memory-Augmented Networks

A Preliminary Study on Data Augmentation of Deep Learning for Image Classification

3D Reconstruction of Whole Stomach from Endoscope Video Using Structure-from-Motion

Integration of Text-maps in Convolutional Neural Networks for Region Detection among Different Textual Categories

Plane-Based Optimization of Geometry and Texture for RGB-D Reconstruction of Indoor Scenes

A novel algorithm for segmentation of leukocytes in peripheral blood

Megapixel Photon-Counting Color Imaging using Quanta Image Sensor

Spatio-Temporal Road Scene Reconstruction using Superpixel Markov Random Field

Incorporating Luminance, Depth and Color Information by a Fusion-based Network for Semantic Segmentation

Bimodal Stereo: Joint Shape and Pose Estimation from Color-Depth Image Pair

Fluorescence Image Histology Pattern Transformation using Image Style Transfer

Vehicle Shape and Color Classification Using Convolutional Neural Network

Expression Conditional GAN for Facial Expression-to-Expression Translation

Object Recognition under Multifarious Conditions: A Reliability Analysis and A Feature Similarity-based Performance Estimation

Learning fashion compatibility across apparel categories for outfit recommendation

RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion

Unsupervised automatic classification of Scanning Electron Microscopy (SEM) images of CD4+ cells with varying extent of HIV virion infection

JPEG XT Image Compression with Hue Compensation for Two-Layer HDR Coding

MRF-Based Multispectral Image Fusion Using an Adaptive Approach Based on Edge-Guided Interpolation

End-to-End Denoising of Dark Burst Images Using Recurrent Fully Convolutional Networks

Painting on Placement: Forecasting Routing Congestion using Conditional Generative Adversarial Nets

Predicting Progression of Age-related Macular Degeneration from Fundus Images using Deep Learning

GIF2Video: Color Dequantization and Temporal Interpolation of GIF images

Multi-view Vector-valued Manifold Regularization for Multi-label Image Classification

Revealing Scenes by Inverting Structure from Motion Reconstructions

Comparative Analysis of Automatic Skin Lesion Segmentation with Two Different Implementations

Unsupervised Visual Feature Learning with Spike-timing-dependent Plasticity: How Far are we from Traditional Feature Learning Approaches?

Noise-Level Estimation from Single Color Image Using Correlations Between Textures in RGB Channels

Formulating Camera-Adaptive Color Constancy as a Few-shot Meta-Learning Problem

Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoning

Vehicle Re-identification in Aerial Imagery: Dataset and Approach

Prediction Model for Semitransparent Watercolor Pigment Mixtures Using Deep Learning with a Dataset of Transmittance and Reflectance

Iterative Joint Image Demosaicking and Denoising using a Residual Denoising Network

Ancient Painting to Natural Image: A New Solution for Painting Processing

DenseBody: Directly Regressing Dense 3D Human Pose and Shape From a Single Color Image

TextureNet: Consistent Local Parametrizations for Learning from High-Resolution Signals on Meshes

Mimicking the In-Camera Color Pipeline for Camera-Aware Object Compositing

Trace transform based method for color image domain identification

Underwater Single Image Color Restoration Using Haze-Lines and a New Quantitative Dataset

Diving Deep onto Discriminative Ensemble of Histological Hashing & Class-Specific Manifold Learning for Multi-class Breast Carcinoma Taxonomy

Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration

GFD-SSD: Gated Fusion Double SSD for Multispectral Pedestrian Detection

A smartphone application to detection and classification of coffee leaf miner and coffee leaf rust

Robust superpixels using color and contour features along linear path

Evaluation Framework of Superpixel Methods with a Global Regularity Measure

Deep Residual Autoencoder for quality independent JPEG restoration

Purifying Naturalistic Images through a Real-time Style Transfer Semantics Network

Simultaneous Coherent Structure Coloring facilitates interpretable clustering of scientific data by amplifying dissimilarity

Learning Attraction Field Representation for Robust Line Segment Detection

Tiling and Stitching Segmentation Output for Remote Sensing: Basic Challenges and Recommendations

Domain Transfer for 3D Pose Estimation from Color Images without Manual Annotations

Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer

Detecting Colorized Images via Convolutional Neural Networks: Toward High Accuracy and Good Generalization

Non-contact photoplethysmogram and instantaneous heart rate estimation from infrared face video

Self-adaptive Single and Multi-illuminant Estimation Framework based on Deep Learning

Handcrafted and Deep Trackers: Recent Visual Object Tracking Approaches and Trends

Color Image and Multispectral Image Denoising Using Block Diagonal Representation

Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard

Simultaneous x, y Pixel Estimation and Feature Extraction for Multiple Small Objects in a Scene: A Description of the ALIEN Network

End-to-end feature fusion siamese network for adaptive visual tracking

Long-term Correlation Tracking using Multi-layer Hybrid Features in Sparse and Dense Environments

Night Time Haze and Glow Removal using Deep Dilated Convolutional Network

ColorNet: Investigating the importance of color spaces for image classification

DeepSeeNet: A deep learning model for automated classification of patient-based age-related macular degeneration severity from color fundus photographs

Analyzing Covariate Influence on Gender and Race Prediction from Near-Infrared Ocular Images

Background subtraction on depth videos with convolutional neural networks

Assessment of central serous chorioretinopathy (CSC) depicted on color fundus photographs using deep Learning

PVSS: A Progressive Vehicle Search System for Video Surveillance Networks

Truncated nuclear norm regularization for low-rank tensor completion

Skeleton Transformer Networks: 3D Human Pose and Skinned Mesh from Single RGB Image

Can Image Enhancement be Beneficial to Find Smoke Images in Laparoscopic Surgery?

No-Reference Color Image Quality Assessment: From Entropy to Perceptual Quality

Learning to Recognize 3D Human Action from A New Skeleton-based Representation Using Deep Convolutional Neural Networks

The algorithm of the impulse noise filtration in images based on an algorithm of community detection in graphs

Color Image Enhancement Method Based on Weighted Image Guided Filtering

A Region-based Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking

Multi-channel Weighted Nuclear Norm Minimization for Real Color Image Denoising

Video Colorization using CNNs and Keyframes extraction: An application in saving bandwidth

Perturbation Analysis of Learning Algorithms: A Unifying Perspective on Generation of Adversarial Examples

Solar Cell Surface Defect Inspection Based on Multispectral Convolutional Neural Network

Exploring Hypergraph Representation on Face Anti-spoofing Beyond 2D Attacks

End to End Video Segmentation for Driving : Lane Detection For Autonomous Car

Robust Point Light Source Estimation Using Differentiable Rendering

Automatic Feature Weight Determination using Indexing and Pseudo-Relevance Feedback for Multi-feature Content-Based Image Retrieval

Decoupling Semantic Context and Color Correlation with multi-class cross branch regularization

Real-time Indoor Scene Reconstruction with RGBD and Inertia Input

Image Dehazing via Joint Estimation of Transmittance Map and Environmental Illumination

A multi-task deep learning model for the classification of Age-related Macular Degeneration

Automated segmentaiton and classification of arterioles and venules using Cascading Dilated Convolutional Neural Networks

Understanding Unequal Gender Classification Accuracy from Face Images

Playing Soccer without Colors in the SPL: A Convolutional Neural Network Approach

Automatic Image Stylization Using Deep Fully Convolutional Networks

Scene Categorization from Contours: Medial Axis Based Salience Measures

Image-to-Image Translation with Conditional Adversarial Networks

A^2Net: Adjacent Aggregation Networks for Image Raindrop Removal

CocoNet: A deep neural network for mapping pixel coordinates to color values

Quantifying Human Behavior on the Block Design Test Through Automated Multi-Level Analysis of Overhead Video

On Matching Faces with Alterations due to Plastic Surgery and Disguise

Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes

Perceptual Image Quality Assessment through Spectral Analysis of Error Representations

CSV: Image Quality Assessment Based on Color, Structure, and Visual System

CURE-OR: Challenging Unreal and Real Environments for Object Recognition

Multimodal Generative Models for Scalable Weakly-Supervised Learning

Multi-label Object Attribute Classification using a Convolutional Neural Network

Learned Neural Iterative Decoding for Lossy Image Compression Systems

DragonPaint: Rule based bootstrapping for small data with an application to cartoon coloring

ColorUNet: A convolutional classification approach to colorization

Instance Retrieval at Fine-grained Level Using Multi-Attribute Recognition

Performance assessment of the deep learning technologies in grading glaucoma severity

Quaternion Convolutional Neural Networks for Heterogeneous Image Processing

Object Tracking in Hyperspectral Videos with Convolutional Features and Kernelized Correlation Filter

Real-time Action Recognition with Dissimilarity-based Training of Specialized Module Networks

Consistency-aware Shading Orders Selective Fusion for Intrinsic Image Decomposition

Point-cloud-based place recognition using CNN feature extraction

An Efficient Bandit Algorithm for Realtime Multivariate Optimization

Dating Ancient Paintings of Mogao Grottoes Using Deeply Learnt Visual Codes

Fast and Robust Multiple ColorChecker Detection using Deep Convolutional Neural Networks

A Systematic Comparison of Deep Learning Architectures in an Autonomous Vehicle

Seeing Beyond Appearance - Mapping Real Images into Geometrical Domains for Unsupervised CAD-based Recognition

Marrying Tracking with ELM: A Metric Constraint Guided Multiple Feature Fusion Method

Resource Aware Person Re-identification across Multiple Resolutions

Automatic Skin Lesion Segmentation Using GrabCut in HSV Colour Space

Verisimilar Image Synthesis for Accurate Detection and Recognition of Texts in Scenes

Person Retrieval in Surveillance Video using Height, Color and Gender

Generalizing multistain immunohistochemistry tissue segmentation using one-shot color deconvolution deep neural networks

Pose Estimation for Non-Cooperative Spacecraft Rendezvous Using Convolutional Neural Networks

Radiative Transport Based Flame Volume Reconstruction from Videos

Seuillage par hystérésis pour le test de photo-consistance des voxels dans le cadre de la reconstruction 3D

Binocular Tone Mapping with Improved Overall Contrast and Local Details

Historic Emergence of Diversity in Painting: Heterogeneity in Chromatic Distance in Images and Characterization of Massive Painting Data Set

Towards Query Efficient Black-box Attacks: An Input-free Perspective

Structural Consistency and Controllability for Diverse Colorization

BinaryRelax: A Relaxation Approach For Training Deep Neural Networks With Quantized Weights

LUCSS: Language-based User-customized Colourization of Scene Sketches

Deeply Supervised Depth Map Super-Resolution as Novel View Synthesis

Convolutional Neural Networks for Aerial Vehicle Detection and Recognition

Segmentation of Bleeding Regions in Wireless Capsule Endoscopy for Detection of Informative Frames

Three Efficient, Low-Complexity Algorithms for Automatic Color Trapping

Automatic skin lesion segmentation on dermoscopic images by the means of superpixel merging

Fully Point-wise Convolutional Neural Network for Modeling Statistical Regularities in Natural Images

Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks

Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection

User-Guided Deep Anime Line Art Colorization with Conditional Adversarial Networks

DeepMag: Source Specific Motion Magnification Using Gradient Ascent

3D Shape Perception from Monocular Vision, Touch, and Shape Priors

HandSeg: An Automatically Labeled Dataset for Hand Segmentation from Depth Images

Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data

Deep Sketch-Photo Face Recognition Assisted by Facial Attributes

A Deep Learning based Joint Segmentation and Classification Framework for Glaucoma Assesment in Retinal Color Fundus Images

Making Deep Heatmaps Robust to Partial Occlusions for 3D Object Pose Estimation

Multi-Class Lesion Diagnosis with Pixel-wise Classification Network

StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction

Large Margin Structured Convolution Operator for Thermal Infrared Object Tracking

Skeletal Movement to Color Map: A Novel Representation for 3D Action Recognition with Inception Residual Networks

Photo-unrealistic Image Enhancement for Subject Placement in Outdoor Photography

Semantic-aware Grad-GAN for Virtual-to-Real Urban Scene Adaption

Single Bitmap Block Truncation Coding of Color Images Using Hill Climbing Algorithm

LiDAR and Camera Detection Fusion in a Real Time Industrial Multi-Sensor Collision Avoidance System

Underwater Image Haze Removal and Color Correction with an Underwater-ready Dark Channel Prior

Cross-spectral Iris Recognition for Mobile Applications using High-quality Color Images

XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings

Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera

It All Matters: Reporting Accuracy, Inference Time and Power Consumption for Face Emotion Recognition on Embedded Systems

Modularity Matters: Learning Invariant Relational Reasoning Tasks

A Systematic Evaluation of Recent Deep Learning Architectures for Fine-Grained Vehicle Classification

Supervised Saliency Map Driven Segmentation of the Lesions in Dermoscopic Images

Superpixel Based Segmentation and Classification of Polyps in Wireless Capsule Endoscopy

Superpixels Based Marker Tracking Vs. Hue Thresholding In Rodent Biomechanics Application

Low-Rank Tensor Completion by Truncated Nuclear Norm Regularization

PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

A Deep Structure of Person Re-Identification using Multi-Level Gaussian Models

Robust and Fast Decoding of High-Capacity Color QR Codes for Mobile Applications

An Automatic Patch-based Approach for HER-2 Scoring in Immunohistochemical Breast Cancer Images Using Color Features

Weakly Supervised Domain-Specific Color Naming Based on Attention

Learning to Estimate 3D Human Pose and Shape from a Single Color Image

Multichannel Distributed Local Pattern for Content Based Indexing and Retrieval

An Image dehazing approach based on the airlight field estimation

Bone marrow cells detection: A technique for the microscopic image analysis

TextureGAN: Controlling Deep Image Synthesis with Texture Patches

I-HAZE: a dehazing benchmark with real hazy and haze-free indoor images

Exploiting feature representations through similarity learning, post-ranking and ranking aggregation for person re-identification

Full Reference Objective Quality Assessment for Reconstructed Background Images

Attribute-Centered Loss for Soft-Biometrics Guided Face Sketch-Photo Recognition

Mix and match networks: encoder-decoder alignment for zero-pair image translation

CNN based Learning using Reflection and Retinex Models for Intrinsic Image Decomposition

Multimodal Registration of Retinal Images Using Domain-Specific Landmarks and Vessel Enhancement

Multilayer Complex Network Descriptors for Color-Texture Characterization

EarthMapper: A Tool Box for the Semantic Segmentation of Remote Sensing Imagery

Fast and Accurate Reconstruction of Compressed Color Light Field

Generative Adversarial Talking Head: Bringing Portraits to Life with a Weakly Supervised Neural Network

3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation

A New Target-specific Object Proposal Generation Method for Visual Tracking

Feature Mapping for Learning Fast and Accurate 3D Pose Inference from Synthetic Images

Binary Patterns Encoded Convolutional Neural Networks for Texture Recognition and Remote Sensing Scene Classification

Universal Denoising Networks : A Novel CNN Architecture for Image Denoising

Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking

Exploiting deep residual networks for human action recognition from skeletal data

A Learning-Based Visual Saliency Prediction Model for Stereoscopic 3D Video (LBVS-3D)

A Learning-Based Visual Saliency Fusion Model for High Dynamic Range Video (LBVS-HDR)

3D Human Pose Estimation in RGBD Images for Robotic Task Learning

Multimodal Recurrent Neural Networks with Information Transfer Layers for Indoor Scene Labeling

Sample-Relaxed Two-Dimensional Color Principal Component Analysis for Face Recognition and Image Reconstruction

BoxCars: Improving Fine-Grained Recognition of Vehicles using 3-D Bounding Boxes in Traffic Surveillance

A Deep Learning Algorithm for One-step Contour Aware Nuclei Segmentation of Histopathological Images

Multi-Channel Pyramid Person Matching Network for Person Re-Identification

Spectral reflectance estimation from one RGB image using self-interreflections in a concave object

Compressed Sensing, ASBSR-method of image sampling and reconstruction and the problem of digital image acquisition with the lowest possible sampling rate

Learning Graphs with Monotone Topology Properties and Multiple Connected Components

Superpixel based Class-Semantic Texton Occurrences for Natural Roadside Vegetation Segmentation

Adaptive specular reflection detection and inpainting in colonoscopy video frames

Segmentation of Bleeding Regions in Wireless Capsule Endoscopy Images an Approach for inside Capsule Video Summarization

A note on patch-based low-rank minimization for fast image denoising

Color-opponent mechanisms for local hue encoding in a hierarchical framework

An Image Processing based Object Counting Approach for Machine Vision Application

M4CD: A Robust Change Detection Method for Intelligent Visual Surveillance

Image Forgery Localization Based on Multi-Scale Convolutional Neural Networks

3D non-rigid registration using color: Color Coherent Point Drift

Netizen-Style Commenting on Fashion Photos: Dataset and Diversity Measures

Feature Based Framework to Detect Diseases, Tumor, and Bleeding in Wireless Capsule Endoscopy

Interactive Deep Colorization With Simultaneous Global and Local Inputs

DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep Learning

Cloud Detection From RGB Color Remote Sensing Images With Deep Pyramid Networks

Visualization of Hyperspectral Images Using Moving Least Squares

Simultaneous Tensor Completion and Denoising by Noise Inequality Constrained Convex Optimization

Joint convolutional neural pyramid for depth map super-resolution

Emerging from Water: Underwater Image Color Correction Based on Weakly Supervised Color Transfer

Context aware saliency map generation using semantic segmentation

A Novel Feature Descriptor for Image Retrieval by Combining Modified Color Histogram and Diagonally Symmetric Co-occurrence Texture Pattern

Exploring the significance of using perceptually relevant image decolorization method for scene classification

Aerial Spectral Super-Resolution using Conditional Adversarial Networks

Digital image splicing detection based on Markov features in QDCT and QWT domain

A smartphone application to measure the quality of pest control spraying machines via image analysis

Automated Image Analysis Framework for the High-Throughput Determination of Grapevine Berry Sizes Using Conditional Random Fields

Using a single RGB frame for real time 3D hand pose estimation in the wild

The Effectiveness of Data Augmentation for Detection of Gastrointestinal Diseases from Endoscopical Images

Deep Koalarization: Image Colorization using CNNs and Inception-ResNet-v2

MoFA: Model-based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction

Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks

Recognizing Gender from Human Facial Regions using Genetic Algorithm

DR-Net: Transmission Steered Single Image Dehazing Network with Weakly Supervised Refinement

An Adaptive Fuzzy-Based System to Simulate, Quantify and Compensate Color Blindness

Depth Map Completion by Jointly Exploiting Blurry Color Images and Sparse Depth Maps

Illuminant Spectra-based Source Separation Using Flash Photography

A Gamut-Mapping Framework for Color-Accurate Reproduction of HDR Images

Constrained Manifold Learning for Hyperspectral Imagery Visualization

The Emergence of Organizing Structure in Conceptual Representation

Color Face Recognition using High-Dimension Quaternion-based Adaptive Representation

A novel total variation model based on kernel functions and its application

Superpixels Based Segmentation and SVM Based Classification Method to Distinguish Five Diseases from Normal Regions in Wireless Capsule Endoscopy

Multi-Glimpse LSTM with Color-Depth Feature Fusion for Human Detection

Learning deep features for source color laser printer identification based on cascaded learning

VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition

Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusion

Improving Shadow Suppression for Illumination Robust Face Recognition

Gender and Ethnicity Classification of Iris Images using Deep Class-Encoder

Strengths and Weaknesses of Deep Learning Models for Face Recognition Against Image Degradations

First Steps Toward Camera Model Identification with Convolutional Neural Networks

Camera-Aware Multi-Resolution Analysis (CAMRA) for Raw Sensor Data Compression

A Generic Regression Framework for Pose Recognition on Color and Depth Images

Predicting Cardiovascular Risk Factors from Retinal Fundus Photographs using Deep Learning

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging

A Computational Model of Afterimages based on Simultaneous and Successive Contrasts

Improving Heterogeneous Face Recognition with Conditional Adversarial Networks

A General Framework for Flexible Multi-Cue Photometric Point Cloud Registration

Towards high-throughput 3D insect capture for species discovery and diagnostics

DSLR-Quality Photos on Mobile Devices with Deep Convolutional Networks

A Survey of Efficient Regression of General-Activity Human Poses from Depth Images

Stereo Matching With Color-Weighted Correlation, Hierarchical Belief Propagation And Occlusion Handling

Can We See Photosynthesis? Magnifying the Tiny Color Changes of Plant Green Leaves Using Eulerian Video Magnification

Color and Gradient Features for Text Segmentation from Video Frames

Reflectance Intensity Assisted Automatic and Accurate Extrinsic Calibration of 3D LiDAR and Panoramic Camera Using a Printed Chessboard

Context-based Normalization of Histological Stains using Deep Convolutional Features

What your Facebook Profile Picture Reveals about your Personality

Learning to Synthesize a 4D RGBD Light Field from a Single Image

A Solution for Crime Scene Reconstruction using Time-of-Flight Cameras

ORGB: Offset Correction in RGB Color Space for Illumination-Robust Image Processing

Learning to Generate Chairs, Tables and Cars with Convolutional Networks

Monocular Depth Estimation with Hierarchical Fusion of Dilated CNNs and Soft-Weighted-Sum Inference

Analysis and Optimization of Convolutional Neural Network Architectures

Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization

Automatic Classification of Bright Retinal Lesions via Deep Network Features

Text Recognition in Scene Image and Video Frame using Color Channel Selection

Naturally Combined Shape-Color Moment Invariants under Affine Transformations

Coarse-to-Fine Volumetric Prediction for Single-Image 3D Human Pose

Modelling the Scene Dependent Imaging in Cameras with a Deep Neural Network

Conditional generation of multi-modal data using constrained embedding space mapping

Automatic breast cancer grading in lymph nodes using a deep neural network

SAR Image Colorization: Converting Single-Polarization to Fully Polarimetric Using Deep Neural Networks

Wavelet-based Reflection Symmetry Detection via Textural and Color Histograms

Domain-adversarial neural networks to address the appearance variability of histopathology images

Modified Alpha-Rooting Color Image Enhancement Method On The Two-Side 2-D Quaternion Discrete Fourier Transform And The 2-D Discrete Fourier Transform

Optimizing Codes for Source Separation in Color Image Demosaicing and Compressive Video Recovery

Impulsive noise removal from color images with morphological filtering

Text Extraction From Texture Images Using Masked Signal Decomposition

Non-Local Color Image Denoising with Convolutional Neural Networks

Learning Efficient Image Representation for Person Re-Identification

Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study

Large-scale Datasets: Faces with Partial Occlusions and Pose Variations in the Wild

Shape-Color Differential Moment Invariants under Affine Transformations

Hierarchical Gaussian Descriptors with Application to Person Re-Identification

Saliency detection by aggregating complementary background template with optimization framework

Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural Networks

Bayer Demosaicking Using Optimized Mean Curvature over RGB channels

Back to RGB: 3D tracking of hands and hand-object interactions based on short-baseline stereo

Real-Time User-Guided Image Colorization with Learned Deep Priors

Marine Animal Classification with Correntropy Loss Based Multi-view Learning

Investigation of Different Skeleton Features for CNN-based 3D Action Recognition

Spotting the Difference: Context Retrieval and Analysis for Improved Forgery Detection and Localization

Blind Facial Image Quality Enhancement using Non-Rigid Semantic Patches

Multi-view Supervision for Single-view Reconstruction via Differentiable Ray Consistency

Network Dissection: Quantifying Interpretability of Deep Visual Representations

Mean Deviation Similarity Index: Efficient and Reliable Full-Reference Image Quality Evaluator

Visual Recognition of Paper Analytical Device Images for Detection of Falsified Pharmaceuticals

Can fully convolutional networks perform well for general image restoration problems?

Connecting Look and Feel: Associating the visual and tactile properties of physical materials

Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer

A New Pseudo-color Technique Based on Intensity Information Protection for Passive Sensor Imagery

Could you guess an interesting movie from the posters?: An evaluation of vision-based features on movie poster database

On the Relation between Color Image Denoising and Classification

Classification of Diabetic Retinopathy Images Using Multi-Class Multiple-Instance Learning Based on Color Correlogram Features

Dense Multi-view 3D-reconstruction Without Dense Correspondences

A Visual Measure of Changes to Weighted Self-Organizing Map Patterns

Scene Flow to Action Map: A New Representation for RGB-D based Action Recognition with Convolutional Neural Networks

Clustering for Different Scales of Measurement - the Gap-Ratio Weighted K-means Algorithm

Color Orchestra: Ordering Color Palettes for Interpolation and Prediction

Automatic Skin Lesion Analysis using Large-scale Dermoscopy Images and Deep Residual Networks

Illuminant Estimation using Ensembles of Multivariate Regression Trees

Skin lesion segmentation based on preprocessing, thresholding and neural networks

Classification in biological networks with hypergraphlet kernels

Automatic Skin Lesion Segmentation using Semi-supervised Learning Technique

Data-Driven Color Augmentation Techniques for Deep Skin Image Analysis

FALCON: Feature Driven Selective Classification for Energy-Efficient Image Recognition

Deep Learning for Automated Quality Assessment of Color Fundus Images in Diabetic Retinopathy Screening

Removal of Salt and Pepper noise from Gray-Scale and Color Images: An Adaptive Approach

Deep Matching Prior Network: Toward Tighter Multi-oriented Text Detection

Texture and Color-based Image Retrieval Using the Local Extrema Features and Riemannian Distance

An Extensive Technique to Detect and Analyze Melanoma: A Challenge at the International Symposium on Biomedical Imaging (ISBI) 2017

Enhanced Facial Recognition Framework based on Skin Tone and False Alarm Rejection

The Effect of Color Space Selection on Detectability and Discriminability of Colored Objects

Attribute-controlled face photo synthesis from simple line drawing

View Independent Vehicle Make, Model and Color Recognition Using Convolutional Neural Network

Computational Techniques in Multispectral Image Processing: Application to the Syriac Galen Palimpsest

Fast and robust pushbroom hyperspectral imaging via DMD-based scanning

Detection of Face using Viola Jones and Recognition using Back Propagation Neural Network

High Performance Novel Skin Segmentation Algorithm for Images With Complex Background

T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objects

Systematic study of color spaces and components for the segmentation of sky/cloud images

Single Image Restoration for Participating Media Based on Prior Fusion

A statistical model of tristimulus measurements within and between OLED displays

Automated Linear-Time Detection and Quality Assessment of Superpixels in Uncalibrated True- or False-Color RGB Images

Free-Space Detection with Self-Supervised and Online Trained Fully Convolutional Networks

Action Recognition Based on Joint Trajectory Maps with Convolutional Neural Networks

The Mehler-Fock Transform and some Applications in Texture Analysis and Color Processing

A Nonlocal Denoising Algorithm for Manifold-Valued Images Using Second Order Statistics

Scribbler: Controlling Deep Image Synthesis with Sketch and Color

Cancerous Nuclei Detection and Scoring in Breast Cancer Histopathological Images

Comparative study of histogram distance measures for re-identification

Probabilistic Duality for Parallel Gibbs Sampling without Graph Coloring

Generative One-Class Models for Text-based Person Retrieval in Forensic Applications

Improving Color Constancy by Discounting the Variation of Camera Spectral Sensitivity

Robust Gait Recognition by Integrating Inertial and RGBD Sensors

Mask-off: Synthesizing Face Images in the Presence of Head-mounted Displays

Automatic View-Point Selection for Inter-Operative Endoscopic Surveillance

Content-Based Image Retrieval Using Multiresolution Analysis Of Shape-Based Classified Images

Sparsity-based Color Image Super Resolution via Exploiting Cross Channel Constraints

On the Empirical Effect of Gaussian Noise in Under-sampled MRI Reconstruction

Linear Support Tensor Machine: Pedestrian Detection in Thermal Infrared Images

Perceptual uniform descriptor and Ranking on manifold: A bridge between image representation and ranking for image retrieval

Adaptive Decontamination of the Training Set: A Unified Formulation for Discriminative Visual Tracking

Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models

Color: A Crucial Factor for Aesthetic Quality Assessment in a Subjective Dataset of Paintings

Perceptual Quality Prediction on Authentically Distorted Images Using a Bag of Features Approach

Single-image RGB Photometric Stereo With Spatially-varying Albedo

Segmentation and Classification of Skin Lesions for Disease Diagnosis

Simultaneous independent image display technique on multiple 3D objects

Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions

Vanishing point attracts gaze in free-viewing and visual search tasks

Robust video object tracking via Bayesian model averaging based feature fusion

Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking

Approaching the Computational Color Constancy as a Classification Problem through Deep Learning

Multiple objects tracking in surveillance video using color and Hu moments

Who Leads the Clothing Fashion: Style, Color, or Texture? A Computational Study

Deep Structured-Output Regression Learning for Computational Color Constancy

FPGA system for real-time computational extended depth of field imaging using phase aperture coding

Interactive Removal and Ground Truth for Difficult Shadow Scenes

DAVE: A Unified Framework for Fast Vehicle Detection and Annotation

Automatic Detection of Solar Photovoltaic Arrays in High Resolution Aerial Imagery

Person Re-identification with Hyperspectral Multi-Camera Systems --- A Pilot Study

Photo Stylistic Brush: Robust Style Transfer via Superpixel-Based Bipartite Graph

Adaptive Gray World-Based Color Normalization of Thin Blood Film Images

Concatenated image completion via tensor augmentation and completion

Salient Region Detection and Segmentation in Images using Dynamic Mode Decomposition

Convolutional Neural Networks for Attribute-based Active Authentication on Mobile Devices

Deep Depth Super-Resolution : Learning Depth Super-Resolution using Deep Convolutional Neural Network

Articulated Clinician Detection Using 3D Pictorial Structures on RGB-D Data

Multipartite Ranking-Selection of Low-Dimensional Instances by Supervised Projection to High-Dimensional Space

Visualizing textual models with in-text and word-as-pixel highlighting

A Survey of Pansharpening Methods with A New Band-Decoupled Variational Model

MARLow: A Joint Multiplanar Autoregressive and Low-Rank Approach for Image Completion

FOMTrace: Interactive Video Segmentation By Image Graphs and Fuzzy Object Models

Predicting Personal Traits from Facial Images using Convolutional Neural Networks Augmented with Facial Landmark Information

A Channelized Binning Method for Extraction of Dominant Color Pixel Value

A Mid-level Video Representation based on Binary Descriptors: A Case Study for Pornography Detection

Item Popularity Prediction in E-commerce Using Image Quality Feature Vectors

A propagation matting method based on the Local Sampling and KNN Classification with adaptive feature space

An Enhanced Deep Feature Representation for Person Re-identification

Depth Image Inpainting: Improving Low Rank Matrix Completion with Low Gradient Regularization

DENSER Cities: A System for Dense Efficient Reconstructions of Cities

Multi-modal Fusion for Diabetes Mellitus and Impaired Glucose Regulation Detection

Machine Learning for Visual Navigation of Unmanned Ground Vehicles

Reading Between the Pixels: Photographic Steganography for Camera Display Messaging

Deep Manifold Traversal: Changing Labels with Convolutional Features

Ensemble of Deep Convolutional Neural Networks for Learning to Detect Retinal Vessels in Fundus Images

Effective Computer Model For Recognizing Nationality From Frontal Image

Automatic Discrimination of Color Retinal Images using the Bag of Words Approach

Adaptive Visualisation System for Construction Building Information Models Using Saliency

Underwater Fish Tracking for Moving Cameras based on Deformable Multiple Kernels

Saliency Detection combining Multi-layer Integration algorithm with background prior and energy function

Real-Time Hand Tracking Using a Sum of Anisotropic Gaussians Model

God(s) Know(s): Developmental and Cross-Cultural Patterns in Children Drawings

Nonlinearities and Adaptation of Color Vision from Sequential Principal Curves Analysis

Discovering Picturesque Highlights from Egocentric Vacation Videos

A dense subgraph based algorithm for compact salient image region detection

Numerical Demultiplexing of Color Image Sensor Measurements via Non-linear Random Forest Modeling

Single and Multiple Illuminant Estimation Using Convolutional Neural Networks

Color Constancy by Learning to Predict Chromaticity from Luminance

Sparse Coral Classification Using Deep Convolutional Neural Networks

Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric

Identification and Counting White Blood Cells and Red Blood Cells using Image Processing Case Study of Leukemia

Standard methods for inexpensive pollen loads authentication by means of computer vision and machine learning

A new humanlike facial attractiveness predictor with cascaded fine-tuning deep learning model

Image classification based on support vector machine and the fusion of complementary features

Sparse + Low Rank Decomposition of Annihilating Filter-based Hankel Matrix for Impulse Noise Removal

Learning a Discriminative Model for the Perception of Realism in Composite Images

Fast Non-local Stereo Matching based on Hierarchical Disparity Prediction

Robust video object tracking using particle filter with likelihood based feature fusion and adaptive template updating

High-for-Low and Low-for-High: Efficient Boundary Detection from Deep Object Features and its Applications to High-Level Vision

Color-Stripe Structured Light Robust to Surface Color and Discontinuity

Color-Phase Analysis for Sinusoidal Structured Light in Rapid Range Imaging

On Binary Classification with Single-Layer Convolutional Neural Networks

Exploring Online Ad Images Using a Deep Convolutional Neural Network Approach

A Comparative Analysis of Retrieval Techniques In Content Based Image Retrieval

BREN: Body Reflection Essence-Neuter Model for Separation of Reflection Components

High-Contrast Color-Stripe Pattern for Rapid Structured-Light Range Imaging

Feature Learning for Interaction Activity Recognition in RGBD Videos

Collaborative Total Variation: A General Framework for Vectorial TV Models

Evaluating color texture descriptors under large variations of controlled lighting conditions

Aging display's effect on interpretation of digital pathology slides

DeepStereo: Learning to Predict New Views from the World's Imagery

BoWFire: Detection of Fire in Still Images by Integrating Pixel Color and Texture Analysis

License Plate Recognition System Based on Color Coding Of License Plates

Image Retrieval System Base on EMD Similarity Measure and S-Tree

A Three-stage Approach for Segmenting Degraded Color Images: Smoothing, Lifting and Thresholding (SLaT)

The color of smiling: computational synaesthesia of facial expressions

Data Fusion of Objects Using Techniques Such as Laser Scanning, Structured Light and Photogrammetry for Cultural Heritage Applications

Text Localization in Video Using Multiscale Weber's Local Descriptor

An Analysis of Unsupervised Pre-training in Light of Recent Advances

Unsupervised Neural Architecture for Saliency Detection: Extended Version

Tensor machines for learning target-specific polynomial features

DistancePPG: Robust non-contact vital signs monitoring using a camera

Sign Language Fingerspelling Classification from Depth and Color Images using a Deep Belief Network

An approach to improving edge detection for facial and remotely sensed images using vector order statistics

Edge Detection: A Collection of Pixel based Approach for Colored Images

Content-Based Bird Retrieval using Shape context, Color moments and Bag of Features

Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices

Color Image Classification via Quaternion Principal Component Analysis Network

Discrete Wavelet Transform and Gradient Difference based approach for text localization in videos

Multi-valued Color Representation Based on Frank t-norm Properties

Color Image Enhancement Using the lrgb Coordinates in the Context of Support Fuzzification

Gradient Difference based approach for Text Localization in Compressed domain

Skeleton Matching based approach for Text Localization in Scene Images

A Survey on Hough Transform, Theory, Techniques and Applications

Pixel-wise Orthogonal Decomposition for Color Illumination Invariant and Shadow-free Image

An Offline Technique for Localization of License Plates for Indian Commercial Vehicles

Leader Follower Formation Control of Ground Vehicles Using Camshift Based Guidance

Face recognition using color local binary pattern from mutually independent color channels

Learning of Proto-object Representations via Fixations on Low Resolution

Facial Expressions recognition Based on Principal Component Analysis (PCA)

Fusing Color and Texture Cues to Categorize the Fruit Diseases from Images

Road Detection by One-Class Color Classification: Dataset and Experiments

Color image quality assessment measure using multivariate generalized Gaussian distribution

On color image quality assessment using natural image statistics

A statistical reduced-reference method for color image quality assessment

Person Re-identification Based on Color Histogram and Spatial Configuration of Dominant Color Regions

Image color transfer to evoke different emotions based on color combinations

Novel methods for multilinear data completion and de-noising based on tensor-SVD

Efficient MRF Energy Propagation for Video Segmentation via Bilateral Filters

Shape and Color Object Tracking for Real-Time Robotic Navigation

An Aerial Image Recognition Framework using Discrimination and Redundancy Quality Measure

MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation

A New Framework for Retinex based Color Image Enhancement using Particle Swarm Optimization

A Model of Plant Identification System Using GLCM, Lacunarity And Shen Features

Robust Statistical Approach for Extraction of Moving Human Silhouettes from Videos

An Improved Approach for Contrast Enhancement of Spinal Cord Images based on Multiscale Retinex Algorithm

Novel and Tuneable Method for Skin Detection Based on Hybrid Color Space and Color Statistical Features

Performance evaluation of wavelet scattering network in image texture classification in various color spaces

A robust and adaptable method for face detection based on Color Probabilistic Estimation Technique

Optimized Method for Iranian Road Signs Detection and recognition system

Natural Color Image Enhancement based on Modified Multiscale Retinex Algorithm and Performance Evaluation usingWavelet Energy

Identification of Orchid Species Using Content-Based Flower Image Retrieval

The Shortlist Method for Fast Computation of the Earth Mover's Distance and Finding Optimal Solutions to Transportation Problems

An FPGA-based Parallel Architecture for Face Detection using Mixed Color Models

VSCAN: An Enhanced Video Summarization using Density-based Spatial Clustering

Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes

Packing and Padding: Coupled Multi-index for Accurate Image Retrieval

Modeling Radiometric Uncertainty for Vision with Tone-mapped Color Images

Automatic Image Registration in Infrared-Visible Videos using Polygon Vertices

Designing an FPGA Synthesizable Computer Vision Algorithm to Detect the Greening of Potatoes

Improving Streaming Video Segmentation with Early and Mid-Level Visual Processing

A Fast Two Pass Multi-Value Segmentation Algorithm based on Connected Component Analysis

Multiclass Data Segmentation using Diffuse Interface Methods on Graphs

IVSS Integration of Color Feature Extraction Techniques for Intelligent Video Search Systems

Face Detection from still and Video Images using Unsupervised Cellular Automata with K means clustering algorithm

ARIANNA: pAth Recognition for Indoor Assisted NavigatioN with Augmented perception

Color and Shape Content Based Image Classification using RBF Network and PSO Technique: A Survey

Experiments of Distance Measurements in a Foliage Plant Retrieval System

Structure-preserving color transformations using Laplacian commutativity

Advances in Hyperspectral Image Classification: Earth monitoring with statistical learning methods

Using the Random Sprays Retinex Algorithm for Global Illumination Estimation

CSIFT Based Locality-constrained Linear Coding for Image Classification

Robust Periocular Recognition By Fusing Sparse Representations of Color and Geometry Information

Suspicious Object Recognition Method in Video Stream Based on Visual Attention

An Adaptive GMM Approach to Background Subtraction for Application in Real Time Surveillance

Saliency-Guided Perceptual Grouping Using Motion Cues in Region-Based Artificial Visual Attention

Content Based Image Retrieval System using Feature Classification with Modified KNN Algorithm

Processing stationary noise: model and parameter selection in variational methods

Demosaicing and Superresolution for Color Filter Array via Residual Image Reconstruction and Sparse Representation

A maximal-information color to gray conversion method for document images: Toward an optimal grayscale representation for document image binarization

A Novel Block-DCT and PCA Based Image Perceptual Hashing Algorithm

Cluster coloring of the Self-Organizing Map: An information visualization perspective

Detection of Outer Rotations on 3D-Vector Fields with Iterative Geometric Correlation and its Efficiency

Revisiting the Nystrom Method for Improved Large-Scale Machine Learning

Video Human Segmentation using Fuzzy Object Models and its Application to Body Pose Estimation of Toddlers for Behavior Studies

Color image denoising by chromatic edges based vector valued diffusion

A Bag of Words Approach for Semantic Segmentation of Monitored Scenes

An Adaptive Descriptor Design for Object Recognition in the Wild

A Self-Organizing Neural Scheme for Door Detection in Different Environments

Visual Objects Classification with Sliding Spatial Pyramid Matching

Applying Dynamic Model for Multiple Manoeuvring Target Tracking Using Particle Filtering

Color Constancy based on Image Similarity via Bilayer Sparse Coding

Different Operating Systems Compatible for Image Prepress Process in Color Management: Analysis and Performance Testing

Developing ICC Profile Using Gray Level Control In Offset Printing Process

Unsupervised Detection and Tracking of Arbitrary Objects with Dependent Dirichlet Process Mixtures

A fast compression-based similarity measure with applications to content-based image retrieval

Reproduction of Images by Gamut Mapping and Creation of New Test Charts in Prepress Process

An Implementation of Computer Graphics as Prepress Image Enhancement Process

An Efficient Color Face Verification Based on 2-Directional 2-Dimensional Feature Extraction

Acceleration of the shiftable O(1) algorithm for bilateral filtering and non-local means

ROI Segmentation for Feature Extraction from Human Facial Images

A Novel Approach Coloured Object Tracker with Adaptive Model and Bandwidth using Mean Shift Algorithm

Spatial And Spectral Quality Evaluation Based On Edges Regions Of Satellite Image Fusion

An Innovative Skin Detection Approach Using Color Based Image Retrieval Technique

Investigation of Color Constancy for Ubiquitous Wireless LAN/Camera Positioning: An Initial Outcome

Scaling Up Coordinate Descent Algorithms for Large $\ell_1$ Regularization Problems

M-FISH Karyotyping - A New Approach Based on Watershed Transform

Clustering and Bayesian network for image of faces classification

Kernel Density Feature Points Estimator for Content-Based Image Retrieval

Unsupervised Threshold for Automatic Extraction of Dolphin Dorsal Fin Outlines from Digital Photographs in DARWIN (Digital Analysis and Recognition of Whale Images on a Network)

A New Color Feature Extraction Method Based on Dynamic Color Distribution Entropy of Neighborhoods

Improvement of BM3D Algorithm and Employment to Satellite and CFA Images Denoising

A multi-feature tracking algorithm enabling adaptation to context variations

The Object Projection Feature Estimation Problem in Unsupervised Markerless 3D Motion Tracking

A robust, low-cost approach to Face Detection and Face Recognition

How to Evaluate Dimensionality Reduction? - Improving the Co-ranking Matrix

Foliage Plant Retrieval using Polar Fourier Transform, Color Moments and Vein Features

Color Texture Classification Approach Based on Combination of Primitive Pattern Units and Statistical Features

Arithmetic and Frequency Filtering Methods of Pixel-Based Image Fusion Techniques

Robust Mobile Object Tracking Based on Multiple Feature Similarity and Trajectory Filtering

Face Recognition using 3D Facial Shape and Color Map Information: Comparison and Combination

Hue Histograms to Spatiotemporal Local Features for Action Recognition

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development

Property-aware Adaptive Relation Networks for Molecular Property Prediction

Calibrated Uncertainty for Molecular Property Prediction using Ensembles of Message Passing Neural Networks

DeepCEL0 for 2D Single Molecule Localization in Fluorescence Microscopy

Improving black-box optimization in VAE latent space using decoder uncertainty

On Graph Neural Network Ensembles for Large-Scale Molecular Property Prediction

GraphPiece: Efficiently Generating High-Quality Molecular Graph with Substructures

DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science

Adversarial Graph Augmentation to Improve Graph Contrastive Learning

High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning

Modern Hopfield Networks for Few- and Zero-Shot Reaction Template Prediction

Flexible dual-branched message passing neural network for quantum mechanical property prediction with molecular conformation

Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation

Equivariant message passing for the prediction of tensorial properties and molecular spectra

High-Throughput Virtual Screening of Small Molecule Inhibitors for SARS-CoV-2 Protein Targets with Deep Fusion Models

Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge

Semi-supervised learning of images with strong rotational disorder: assembling nanoparticle libraries

HamNet: Conformation-Guided Molecular Representation with Hamiltonian Neural Networks

SafeDrug: Dual Molecular Graph Encoders for Safe Drug Recommendations

Genetic Constrained Graph Variational Autoencoder for COVID-19 Drug Discovery

Learning Neural Generative Dynamics for Molecular Conformation Generation

Differentiable sampling of molecular geometries with uncertainty-based adversarial attacks

Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics

Set Prediction without Imposing Structure as Conditional Density Estimation

A reproducibility study of "Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space"

Artificial Intelligence based Autonomous Molecular Design for Medical Therapeutic: A Perspective

Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19

BridgeDPI: A Novel Graph Neural Network for Predicting Drug-Protein Interactions

Automatic design of novel potential 3CL$^{\text{pro}}$ and PL$^{\text{pro}}$ inhibitors

Lossless Compression of Structured Convolutional Models via Lifting

Barking up the right tree: an approach to search over molecule synthesis DAGs

Learn molecular representations from large-scale unlabeled molecules for drug discovery

Deep Molecular Dreaming: Inverse machine learning for de-novo molecular design and interpretability with surjective representations

Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules

RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design

Lipophilicity Prediction with Multitask Learning and Molecular Substructures Representation

Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties

On the equivalence of molecular graph convolution and molecular wave function with poor basis set

Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures

Optimizing Molecules using Efficient Queries from Property Evaluations

Graph Neural Network for Metal Organic Framework Potential Energy Approximation

Learning Latent Space Energy-Based Prior Model for Molecule Generation

Deep learning method to remove chemical, kinetic and electric artifacts on ISEs

SoRC -- Evaluation of Computational Molecular Co-Localization Analysis in Mass Spectrometry Images

Conditional Constrained Graph Variational Autoencoders for Molecule Design

Graph Neural Network Architecture Search for Molecular Property Prediction

A Systematic Assessment of Deep Learning Models for Molecule Generation

Augmenting Molecular Images with Vector Representations as a Featurization Technique for Drug Classification

ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction

Multi-Objective Molecule Generation using Interpretable Substructures

CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models

Geometric Graph Representations and Geometric Graph Convolutions for Deep Learning on Three-Dimensional (3D) Graphs

Structure-Property Maps with Kernel Principal Covariates Regression

Hierarchical Generation of Molecular Graphs using Structural Motifs

Continuous Representation of Molecules Using Graph Variational Autoencoder

Knowledge Elicitation using Deep Metric Learning and Psychometric Testing

Predicting drug properties with parameter-free machine learning: Pareto-Optimal Embedded Modeling (POEM)

Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular string representation

ChemGrapher: Optical Graph Recognition of Chemical Compounds by Deep Learning

Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks

Molecule Property Prediction and Classification with Graph Hypernetworks

Re-balancing Variational Autoencoder Loss for Molecule Sequence Generation

Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules

Fast and robust multiplane single molecule localization microscopy using deep neural network

Molecular geometry prediction using a deep generative graph neural network

libmolgrid: GPU Accelerated Molecular Gridding for Deep Learning Applications

Gated Graph Recursive Neural Networks for Molecular Property Prediction

CORE: Automatic Molecule Optimization Using Copy & Refine Strategy

Analyzing Learned Molecular Representations for Property Prediction

N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules

Discrete Object Generation with Reversible Inductive Construction

Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods

ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations

Learning to Make Generalizable and Diverse Predictions for Retrosynthesis

Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction

Deep Generative Model for Sparse Graphs using Text-Based Learning with Augmentation in Generative Examination Networks

GEN: Highly Efficient SMILES Explorer Using Autodidactic Generative Examination Networks

Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures

PADME: A Deep Learning-based Framework for Drug-Target Interaction Prediction

Hyper-Molecules: on the Representation and Recovery of Dynamical Structures, with Application to Flexible Macro-Molecular Structures in Cryo-EM

Capabilities and Limitations of Time-lagged Autoencoders for Slow Mode Discovery in Dynamical Systems

Graph Warp Module: an Auxiliary Module for Boosting the Power of Graph Neural Networks in Molecular Graph Analysis

Using Attribution to Decode Dataset Bias in Neural Network Models for Chemistry

Molecular Hypergraph Grammar with its Application to Molecular Optimization

Three-Dimensionally Embedded Graph Convolutional Network (3DGCN) for Molecule Interpretation

Adversarial Autoencoders with Constant-Curvature Latent Manifolds

Learning formation energy of inorganic compounds using matrix variate deep Gaussian process

Junction Tree Variational Autoencoder for Molecular Graph Generation

Step Change Improvement in ADMET Prediction with PotentialNet Deep Featurization

Tiered Latent Representations and Latent Spaces for Molecular Graphs

High-dimensional Metric Combining for Non-coherent Molecular Signal Detection

Prediction of Atomization Energy Using Graph Kernel and Active Learning

Learning Multimodal Graph-to-Graph Translation for Molecular Optimization

Interpretable deep learning for guided structure-property explorations in photovoltaics

Synergy Effect between Convolutional Neural Networks and the Multiplicity of SMILES for Improvement of Molecular Prediction

CheMixNet: Mixed DNN Architectures for Predicting Chemical Properties using Multiple Molecular Representations

DEFactor: Differentiable Edge Factorization-based Probabilistic Graph Generation

Efficient nonmyopic active search with applications in drug and materials discovery

High Quality Prediction of Protein Q8 Secondary Structure by Diverse Neural Network Architectures

Supervised Classification Methods for Flash X-ray single particle diffraction Imaging

Domain-Adversarial Multi-Task Framework for Novel Therapeutic Property Prediction of Compounds

Improving Chemical Autoencoder Latent Space and Molecular De novo Generation Diversity with Heteroencoders

Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images

Molecular generative model based on conditional variational autoencoder for de novo molecular design

An image representation based convolutional network for DNA classification

ToxicBlend: Virtual Screening of Toxic Compounds with Ensemble Predictors

Weighted Tanimoto Coefficient for 3D Molecule Structure Similarity Measurement

Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials

Edge Attention-based Multi-Relational Graph Convolutional Networks

Accelerating Prototype-Based Drug Discovery using Conditional Diversity Networks

Molecular Structure Extraction From Documents Using Deep Learning

GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders

In silico generation of novel, drug-like chemical matter using the LSTM neural network

Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network

Automatic chemical design using a data-driven continuous representation of molecules

Semi-supervised learning of hierarchical representations of molecules using neural message passing

Application of generative autoencoder in de novo molecular design

Hierarchical modeling of molecular energies using a deep neural network

Learning Deep Architectures for Interaction Prediction in Structure-based Virtual Screening

Robust Spatial Filtering with Graph Convolutional Neural Networks

Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models

Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space

SMILES Enumeration as Data Augmentation for Neural Network Modeling of Molecules

Graphical Models: An Extension to Random Graphs, Trees, and Other Objects

Continuously heterogeneous hyper-objects in cryo-EM and 3-D movies of many temporal dimensions

Atomic Convolutional Networks for Predicting Protein-Ligand Binding Affinity

Localized Coulomb Descriptors for the Gaussian Approximation Potential

Space-Filling Curves as a Novel Crystal Structure Representation for Machine Learning Models

A Representation Theory Perspective on Simultaneous Alignment and Classification

Predicting Drug Interactions and Mutagenicity with Ensemble Classifiers on Subgraphs of Molecules

Properties of the Sample Mean in Graph Spaces and the Majorize-Minimize-Mean Algorithm

AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery

Building Proteins in a Day: Efficient 3D Molecular Reconstruction

Covariance estimation using conjugate gradient for 3D classification in Cryo-EM

Microscopic Advances with Large-Scale Learning: Stochastic Optimization for Cryo-EM

A Ray-based Approach for Boundary Estimation of Fiber Bundles Derived from Diffusion Tensor Imaging

Statistical Denoising for single molecule fluorescence microscopic images

Towards a Mathematical Foundation of Immunology and Amino Acid Chains

A Semi-Automatic Graph-Based Approach for Determining the Boundary of Eloquent Fiber Bundles in the Human Brain

Backdoor Attacks on Federated Learning with Lottery Ticket Hypothesis

Exploring the Connection between Knowledge Distillation and Logits Matching

Novel Compressible Adaptive Spectral Mixture Kernels for Gaussian Processes with Sparse Time and Phase Delay Structures

Full-Cycle Energy Consumption Benchmark for Low-Carbon Computer Vision

Weight Squeezing: Reparameterization for Knowledge Transfer and Model Compression

Preventing Catastrophic Forgetting and Distribution Mismatch in Knowledge Distillation via Synthetic Data

WeClick: Weakly-Supervised Video Semantic Segmentation with Click Annotations

QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning

Towards Efficient Tensor Decomposition-Based DNN Model Compression with Optimization Framework

Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?

Model compression as constrained optimization, with application to neural nets. Part V: combining compressions

Image Classification with CondenseNeXt for ARM-Based Computing Platforms

PQK: Model Compression via Pruning, Quantization, and Knowledge Distillation

Knowledge Distillation and Student-Teacher Learning for Visual Intelligence: A Review and New Outlooks

A Winning Hand: Compressing Deep Networks Can Improve Out-Of-Distribution Robustness

MixMix: All You Need for Data-Free Compression Are Feature and Data Mixing

Rate-Distortion Theoretic Model Compression: Successive Refinement for Pruning

Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization

FedNL: Making Newton-Type Methods Applicable to Federated Learning

Feature Flow Regularization: Improving Structured Sparsity in Deep Neural Networks

Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators

Multi-level Knowledge Distillation via Knowledge Alignment and Correlation

Energy-Efficient Model Compression and Splitting for Collaborative Inference Over Time-Varying Channels

Towards Efficient Full 8-bit Integer DNN Online Training on Resource-limited Devices without Batch Normalization

Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning

3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low BitwidthQuantization, and Ultra-Low Latency Acceleration

Modulating Regularization Frequency for Efficient Compression-Aware Model Training

Spirit Distillation: A Model Compression Method with Multi-domain Knowledge Transfer

Spatio-Temporal Pruning and Quantization for Low-latency Spiking Neural Networks

Dual Discriminator Adversarial Distillation for Data-free Model Compression

Tight Compression: Compressing CNN Through Fine-Grained Pruning and Weight Permutation for Efficient Implementation

Compacting Deep Neural Networks for Internet of Things: Methods and Applications

Formalizing Generalization and Robustness of Neural Networks to Weight Perturbations

Preserved central model for faster bidirectional compression in distributed settings

Robustness and Diversity Seeking Data-Free Knowledge Distillation

It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation

AACP: Model Compression by Accurate and Automatic Channel Pruning

Differential Privacy Meets Federated Learning under Communication Constraints

AdaSpring: Context-adaptive and Runtime-evolutionary Deep Model Compression for Mobile Applications

Deep Compression of Neural Networks for Fault Detection on Tennessee Eastman Chemical Processes

Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks

RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices

Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination

Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks

Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework

Pea-KD: Parameter-efficient and Accurate Knowledge Distillation on BERT

Progressive Network Grafting for Few-Shot Knowledge Distillation

DE-RRD: A Knowledge Distillation Framework for Recommender System

A Tunable Robust Pruning Framework Through Dynamic Network Rewiring of DNNs

Empirical Evaluation of Deep Learning Model Compression Techniques on the WaveNet Vocoder

Position-based Scaled Gradient for Model Quantization and Pruning

CompRess: Self-Supervised Learning by Compressing Representations

MSP: An FPGA-Specific Mixed-Scheme, Multi-Precision Deep Neural Network Quantization Framework

Communication-Computation Trade-Off in Resource-Constrained Edge Inference

Compression-aware Continual Learning using Singular Value Decomposition

Layer-specific Optimization for Mixed Data Flow with Mixed Precision in FPGA Design for CNN-based Object Detectors

Data-Independent Structured Pruning of Neural Networks via Coresets

Differentiable Feature Aggregation Search for Knowledge Distillation

ALF: Autoencoder-based Low-rank Filter-sharing for Efficient Convolutional Neural Networks

Paraphrasing Complex Network: Network Compression via Factor Transfer

Standing on the Shoulders of Giants: Hardware and Neural Architecture Co-Search with Hot Start

Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error

Soft Labeling Affects Out-of-Distribution Detection of Deep Neural Networks

PFGDF: Pruning Filter via Gaussian Distribution Feature for Deep Neural Networks Acceleration

Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization

PCNN: Pattern-based Fine-Grained Regular Pruning towards Optimizing CNN Accelerators

A Survey of Model Compression and Acceleration for Deep Neural Networks

AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles

A flexible, extensible software framework for model compression based on the LC algorithm

Compressing Recurrent Neural Networks Using Hierarchical Tucker Tensor Decomposition

Pruning Algorithms to Accelerate Convolutional Neural Networks for Edge Applications: A Survey

Data-Free Network Quantization With Adversarial Knowledge Distillation

SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation

Gradual Channel Pruning while Training using Feature Relevance Scores for Convolutional Neural Networks

PERMDNN: Efficient Compressed DNN Architecture with Permuted Diagonal Matrices

Robust Membership Encoding: Inference Attacks and Copyright Protection for Deep Learning

Pacemaker: Intermediate Teacher Knowledge Distillation For On-The-Fly Convolutional Neural Network

Structured Compression by Weight Encryption for Unstructured Pruning and Quantization

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-time Execution on Mobile Devices

An Efficient Method of Training Small Models for Regression Problems with Knowledge Distillation

Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs

Scalable Model Compression by Entropy Penalized Reparameterization

SS-Auto: A Single-Shot, Automatic Structured Weight Pruning Framework of DNNs with Ultra-High Efficiency

PatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning

Non-Structured DNN Weight Pruning -- Is It Beneficial in Any Platform?

Model Compression with Adversarial Robustness: A Unified Optimization Framework

Neural Epitome Search for Architecture-Agnostic Network Compression

Towards Building a Real Time Mobile Device Bird Counting System Through Synthetic Data Training and Model Compression

DeGAN : Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier

MicroExpNet: An Extremely Small and Fast Model For Expression Recognition From Face Images

Pruning at a Glance: Global Neural Pruning for Model Compression

Communication-Efficient Distributed Online Learning with Kernels

Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks

DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks

LPRNet: Lightweight Deep Network by Low-rank Pointwise Residual Convolution

Compacting, Picking and Growing for Unforgetting Continual Learning

Locality-Sensitive Hashing for f-Divergences: Mutual Information Loss and Beyond

Global Sparse Momentum SGD for Pruning Very Deep Neural Networks

Balancing Specialization, Generalization, and Compression for Detection and Tracking

Joint Regularization on Activations and Weights for Efficient Neural Network Pruning

MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors

Memory- and Communication-Aware Model Compression for Distributed Deep Learning Inference on IoT

3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation

Weight Normalization based Quantization for Deep Neural Network Compression

COP: Customized Deep Model Compression via Regularized Correlation-Based Filter-Level Pruning

Network Implosion: Effective Model Compression for ResNets via Static Layer Pruning and Retraining

Deep Face Recognition Model Compression via Knowledge Transfer and Distillation

Bayesian Tensorized Neural Networks with Automatic Rank Selection

Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems

Three Dimensional Convolutional Neural Network Pruning with Regularization-Based Method

Dream Distillation: A Data-Independent Model Compression Framework

Play and Prune: Adaptive Filter Pruning for Deep Model Compression

Creating Lightweight Object Detectors with Model Compression for Deployment on Edge Devices

Toward Extremely Low Bit and Lossless Accuracy in DNNs with Progressive ADMM

26ms Inference Time for ResNet-50: Towards Real-Time Execution of all DNNs on Smartphone

Matrix and tensor decompositions for training binary neural networks

Shakeout: A New Approach to Regularized Deep Neural Network Training

Exploiting Kernel Sparsity and Entropy for Interpretable CNN Compression

Recurrent Convolution for Compact and Cost-Adjustable Neural Networks: An Empirical Study

MICIK: MIning Cross-Layer Inherent Similarity Knowledge for Deep Model Compression

Information-Theoretic Understanding of Population Risk Improvement with Model Compression

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

Tensorial Neural Networks: Generalization of Neural Networks and Application to Model Compression

FLOPs as a Direct Optimization Objective for Learning Sparse Neural Networks

Graph-Adaptive Pruning for Efficient Inference of Convolutional Neural Networks

DeepTwist: Learning Model Compression via Occasional Weight Distortion

A Miniaturized Semantic Segmentation Method for Remote Sensing Image

LIT: Block-wise Intermediate Representation Training for Model Compression

SlimNets: An Exploration of Deep Model Compression and Acceleration

Optimize Deep Convolutional Neural Network with Ternarized Weights and High Accuracy

SCSP: Spectral Clustering Filter Pruning with Soft Self-adaption Manners

Dynamically Hierarchy Revolution: DirNet for Compressing Recurrent Neural Network on Mobile Devices

MPDCompress - Matrix Permutation Decomposition Algorithm for Deep Neural Network Compression

Retraining-Based Iterative Weight Quantization for Deep Neural Networks

Hybrid Binary Networks: Optimizing for Accuracy, Efficiency and Memory

Security Analysis and Enhancement of Model Compressed Deep Learning Systems under Adversarial Attacks

Interpreting Deep Classifier by Visual Distillation of Dark Knowledge

Learning Intrinsic Sparse Structures within Long Short-Term Memory

DeepRebirth: Accelerating Deep Neural Network Execution on Mobile Devices

To prune, or not to prune: exploring the efficacy of pruning for model compression

Weightless: Lossy Weight Encoding For Deep Neural Network Compression

Model Distillation with Knowledge Transfer from Face Classification to Alignment and Verification

Compressing Low Precision Deep Neural Networks Using Sparsity-Induced Regularization in Ternary Networks

A Deep Cascade Network for Unaligned Face Attribute Classification

Model compression as constrained optimization, with application to neural nets. Part II: quantization

Model compression as constrained optimization, with application to neural nets. Part I: general framework

A Compact DNN: Approaching GoogLeNet-Level Accuracy of Classification and Domain Adaptation

Parameter Compression of Recurrent Neural Networks and Degradation of Short-term Memory

Compression of Deep Neural Networks for Image Instance Retrieval

QuickNet: Maximizing Efficiency and Efficacy in Deep Architectures

Two-Bit Networks for Deep Learning on Resource-Constrained Embedded Devices

SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

Deep Model Compression: Distilling Knowledge from Noisy Teachers

To Know Where We Are: Vision-Based Positioning in Outdoor Environments

A Scale Mixture Perspective of Multiplicative Noise in Neural Networks

Efficient classification using parallel and scalable compressed model and Its application on intrusion detection

Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation

Boosting Light-Weight Depth Estimation Via Knowledge Distillation

From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation

A Novel Unified Stereo Stimuli based Binocular Eye-Tracking System for Accurate 3D Gaze Estimation

HoHoNet: 360 Indoor Holistic Understanding with Latent Horizontal Features

LiDARTouch: Monocular metric depth estimation with a few-beam LiDAR

Pano3D: A Holistic Benchmark and a Solid Baseline for $360^o$ Depth Estimation

NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo

SeasonDepth: Cross-Season Monocular Depth Prediction Dataset and Benchmark under Multiple Environments

Improving Semi-Supervised and Domain-Adaptive Semantic Segmentation with Self-Supervised Depth Estimation

Multi-task learning from fixed-wing UAV images for 2D/3D city modeling

Lightweight Monocular Depth with a Novel Neural Architecture Search Method

Boosting Monocular Depth Estimation with Lightweight 3D Point Fusion

Bridging Unsupervised and Supervised Depth from Focus via All-in-Focus Supervision

Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation

Real-Time Monocular Human Depth Estimation and Segmentation on Embedded Systems

$S^3$: Learnable Sparse Signal Superdensity for Guided Depth Estimation

Consensus-based Optimization for 3D Human Pose Estimation in Camera Coordinates

Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth Estimation

StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimation

Geometric Unsupervised Domain Adaptation for Semantic Segmentation

Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task Learning

R4Dyn: Exploring Radar for Self-Supervised Monocular Depth Estimation of Dynamic Scenes

MFuseNet: Robust Depth Estimation with Learned Multiscopic Fusion

Bootstrapped Self-Supervised Training with Monocular Video for Semantic Segmentation and Depth Estimation

Pix2Point: Learning Outdoor 3D Using Sparse Point Clouds and Optimal Transport

MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesis

Unsupervised Monocular Depth Estimation in Highly Complex Environments

MonoIndoor: Towards Good Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments

CodeMapping: Real-Time Dense Mapping for Sparse SLAM using Compact Scene Representations

The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth

Domain Generalization with Pseudo-Domain Label for Face Anti-Spoofing

Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce Model

Edge-aware Bidirectional Diffusion for Dense Depth Estimation from Light Fields

Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation

WoodScape: A multi-task, multi-camera fisheye dataset for autonomous driving

Differentiable Diffusion for Dense Depth Estimation from Multi-view Images

Virtual Normal: Enforcing Geometric Constraints for Accurate and Robust Depth Prediction

Self-Supervised Monocular Depth Estimation of Untextured Indoor Rotated Scenes

Achieving Domain Robustness in Stereo Matching Networks by Removing Shortcut Learning

Predicting Depth from Semantic Segmentation using Game Engine Dataset

Instance-Level Task Parameters: A Robust Multi-task Weighting Framework

Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging

Self-Guided Instance-Aware Network for Depth Completion and Enhancement

UniFuse: Unidirectional Fusion for 360$^{\circ}$ Panorama Depth Estimation

Polka Lines: Learning Structured Illumination and Reconstruction for Active Stereo

Real-time Monocular Depth Estimation with Sparse Supervision on Mobile

M4Depth: A motion-based approach for monocular depth estimation on video sequences

Stacked Deep Multi-Scale Hierarchical Network for Fast Bokeh Effect Rendering from a Single Image

Revisiting Light Field Rendering with Deep Anti-Aliasing Neural Network

Mesh Reconstruction from Aerial Images for Outdoor Terrain Mapping Using Joint 2D-3D Learning

Domain Adaptive Monocular Depth Estimation With Semantic Information

Improving Online Performance Prediction for Semantic Segmentation

Instantaneous Stereo Depth Estimation of Real-World Stimuli with a Neuromorphic Stereo-Vision Setup

Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo

Three Ways to Improve Semantic Segmentation with Self-Supervised Depth Estimation

RGB-D Local Implicit Function for Depth Completion of Transparent Objects

On the Synergies between Machine Learning and Binocular Stereo for Depth Estimation from Images: a Survey

Unpaired Single-Image Depth Synthesis with cycle-consistent Wasserstein GANs

Does it work outside this benchmark? Introducing the Rigid Depth Constructor tool, depth validation dataset construction in rigid scenes for the masses

Volumetric Propagation Network: Stereo-LiDAR Fusion for Long-Range Depth Estimation

Monocular Depth Estimation through Virtual-world Supervision and Real-world SfM Self-Supervision

Joint Hand-object 3D Reconstruction from a Single Image with Cross-branch Feature Fusion

Generic Perceptual Loss for Modeling Structured Output Dependencies

Dilated Fully Convolutional Neural Network for Depth Estimation from a Single Image

PLADE-Net: Towards Pixel-Level Accuracy for Self-Supervised Single-View Depth Estimation with Neural Positional Encoding and Distilled Matting Loss

Learning a Domain-Agnostic Visual Representation for Autonomous Driving via Contrastive Loss

Learning to compose 6-DoF omnidirectional videos using multi-sphere images

Implicit Integration of Superpixel Segmentation into Fully Convolutional Networks

Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation

Scene Completeness-Aware Lidar Depth Completion for Driving Scenario

Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction

Learning Depth via Leveraging Semantics: Self-supervised Monocular Depth Estimation with Both Implicit and Explicit Semantic Guidance

Towards General Purpose Geometry-Preserving Single-View Depth Estimation

Stereo Correspondence and Reconstruction of Endoscopic Data Challenge

SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular images

Black-box Adversarial Attacks on Monocular Depth Estimation Using Evolutionary Multi-objective Optimization

SAFENet: Self-Supervised Monocular Depth Estimation with Semantic-Aware Feature Extraction

On Deep Learning Techniques to Boost Monocular Depth Estimation for Autonomous Navigation

HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation

Competitive Simplicity for Multi-Task Learning for Real-Time Foggy Scene Understanding via Domain Adaptation

ViP-DeepLab: Learning Visual Perception with Depth-aware Video Panoptic Segmentation

Dehazing Cost Volume for Deep Multi-view Stereo in Scattering Media with Airlight and Scattering Coefficient Estimation

Dual Pixel Exploration: Simultaneous Depth Estimation and Image Restoration

Distortion-aware Monocular Depth Estimation for Omnidirectional Images

Variational Monocular Depth Estimation for Reliability Prediction

SLAM in the Field: An Evaluation of Monocular Mapping and Localization on Challenging Dynamic Agricultural Environment

Real-Time Uncertainty Estimation in Computer Vision via Uncertainty-Aware Distribution Distillation

The Aleatoric Uncertainty Estimation Using a Separate Formulation with Virtual Residuals

Inferring Point Clouds from Single Monocular Images by Depth Intermediation

A New Distributional Ranking Loss With Uncertainty: Illustrated in Relative Depth Estimation

Nighttime Stereo Depth Estimation using Joint Translation-Stereo Learning: Light Effects and Uninformative Regions

Adversarial Patch Attacks on Monocular Depth Estimation Networks

UnRectDepthNet: Self-Supervised Monocular Depth Estimation using a Generic Framework for Handling Common Camera Distortion Models

Parallax Motion Effect Generation Through Instance Segmentation And Depth Estimation

Joint Pruning & Quantization for Extremely Sparse Neural Networks

Forget About the LiDAR: Self-Supervised Depth Estimators with MED Probability Volumes

Monocular Depth Estimation Using Multi Scale Neural Network And Feature Fusion

Toward Hierarchical Self-Supervised Monocular Absolute Depth Estimation for Autonomous Driving Applications

DESC: Domain Adaptation for Depth Estimation via Semantic Consistency

EPI-based Oriented Relation Networks for Light Field Depth Estimation

DELTAS: Depth Estimation by Learning Triangulation And densification of Sparse points

Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer

Reversing the cycle: self-supervised deep stereo through enhanced monocular distillation

Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motion

Balanced Depth Completion between Dense Depth Inference and Sparse Range Measurements via KISS-GP

HMOR: Hierarchical Multi-Person Ordinal Relations for Monocular Multi-Person 3D Pose Estimation

PLG-IN: Pluggable Geometric Consistency Loss with Wasserstein Distance in Monocular Depth Estimation

$S^3$Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data

Adaptive LiDAR Sampling and Depth Completion using Ensemble Variance

Self-Supervised Monocular 3D Face Reconstruction by Occlusion-Aware Multi-view Geometry Consistency

Pixel-Pair Occlusion Relationship Map(P2ORM): Formulation, Inference & Application

SelfVIO: Self-Supervised Deep Monocular Visual-Inertial Odometry and Depth Estimation

Multi-person 3D Pose Estimation in Crowded Scenes Based on Multi-View Geometry

Pyramid Multi-view Stereo Net with Self-adaptive View Aggregation

Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic Guidance

Feature-metric Loss for Self-supervised Learning of Depth and Egomotion

P$^{2}$Net: Patch-match and Plane-regularization for Unsupervised Indoor Depth Estimation

P2D: a self-supervised method for depth estimation from polarimetry

Partially Supervised Multi-Task Network for Single-View Dietary Assessment

360$^\circ$ Depth Estimation from Multiple Fisheye Images with Origami Crown Representation of Icosahedron

AI Playground: Unreal Engine-based Data Ablation Tool for Deep Learning

On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach

FP-Stereo: Hardware-Efficient Stereo Vision for Embedded Applications

MTStereo 2.0: improved accuracy of stereo depth estimation withMax-trees

Why Having 10,000 Parameters in Your Camera Model is Better Than Twelve

Depth by Poking: Learning to Estimate Depth from Self-Supervised Grasping

Real-time single image depth perception in the wild with handheld devices

SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation

Unsupervised Depth Learning in Challenging Indoor Video: Weak Rectification to Rescue

A Survey on Deep Learning Techniques for Stereo-based Depth Estimation

Depth-aware Blending of Smoothed Images for Bokeh Effect Generation

Focus on defocus: bridging the synthetic to real domain gap for depth estimation

On the uncertainty of self-supervised monocular depth estimation

Predicting Sharp and Accurate Occlusion Boundaries in Monocular Depth Estimation Using Displacement Fields

DeepV2D: Video to Depth with Differentiable Structure from Motion

Improved Noise and Attack Robustness for Semantic Segmentation by Using Multi-Task Training with Self-Supervised Depth Estimation

DepthNet Nano: A Highly Compact Self-Normalizing Neural Network for Monocular Depth Estimation

Monocular Depth Estimation with Self-supervised Instance Adaptation

Novel View Synthesis of Dynamic Scenes with Globally Coherent Depths from a Monocular Camera

Du$^2$Net: Learning Depth Estimation from Dual-Cameras and Dual-Pixels

Fast-MVSNet: Sparse-to-Dense Multi-View Stereo With Learned Propagation and Gauss-Newton Refinement

360SD-Net: 360° Stereo Depth Estimation with Learnable Cost Volume

OmniSLAM: Omnidirectional Localization and Dense Mapping for Wide-baseline Multi-camera Systems

Scalable Uncertainty for Computer Vision with Functional Variational Inference

Learning Light Field Angular Super-Resolution via a Geometry-Aware Network

Pano Popups: Indoor 3D Reconstruction with a Plane-Aware Network

Active Perception with A Monocular Camera for Multiscopic Vision

A Neural Network for Detailed Human Depth Estimation from a Single Image

Edge-Guided Occlusion Fading Reduction for a Light-Weighted Self-Supervised Monocular Depth Estimation

Analysis of Deep Networks for Monocular Depth Estimation Through Adversarial Attacks with Proposal of a Defense Method

Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances

Dense Depth Estimation in Monocular Endoscopy with Self-supervised Learning Methods

Sparse-to-Continuous: Enhancing Monocular Depth Estimation using Occupancy Maps

ClearGrasp: 3D Shape Estimation of Transparent Objects for Manipulation

Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video

Efficient Surface-Aware Semi-Global Matching with Multi-View Plane-Sweep Sampling

Conf-Net: Toward High-Confidence Dense 3D Point-Cloud with Error-Map Prediction

Learning to Think Outside the Box: Wide-Baseline Light Field Depth Estimation with EPI-Shift

Spherical View Synthesis for Self-Supervised 360 Depth Estimation

Progressive Fusion for Unsupervised Binocular Depth Estimation using Cycled Networks

Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance

Improving Self-Supervised Single View Depth Estimation by Masking Occlusion

n-MeRCI: A new Metric to Evaluate the Correlation Between Predictive Uncertainty and True Error

OmniMVS: End-to-End Learning for Omnidirectional Stereo Matching

To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation

DFineNet: Ego-Motion Estimation and Depth Refinement from Sparse, Noisy Depth Input with RGB Guidance

Enhancing self-supervised monocular depth estimation with traditional visual odometry

Exploiting temporal consistency for real-time video depth estimation

GroundNet: Monocular Ground Plane Normal Estimation with Geometric Consistency

Adversarial View-Consistent Learning for Monocular Depth Estimation

RRNet: Repetition-Reduction Network for Energy Efficient Decoder of Depth Estimation

MultiDepth: Single-Image Depth Estimation via Multi-Task Regression and Classification

Veritatem Dies Aperit- Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach

NeurAll: Towards a Unified Model for Visual Perception in Automated Driving

Structure-Aware Residual Pyramid Network for Monocular Depth Estimation

Monocular Depth Estimation with Augmented Ordinal Depth Relationships

DeepPerimeter: Indoor Boundary Estimation from Posed Monocular Sequences

Wireless Software Synchronization of Multiple Distributed Cameras

Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding

Region Deformer Networks for Unsupervised Depth Estimation from Unconstrained Monocular Videos

Depth Estimation on Underwater Omni-directional Images Using a Deep Neural Network

Semi-Supervised Monocular Depth Estimation with Left-Right Consistency Using Deep Neural Network

Lightweight Monocular Depth Estimation Model by Joint End-to-End Filter pruning

Monocular Depth Estimation with Directional Consistency by Deep Networks

Multi-task human analysis in still images: 2D/3D pose, depth map, and multi-part segmentation

Learn Stereo, Infer Mono: Siamese Networks for Self-Supervised, Monocular, Depth Estimation

Learning Single-Image Depth from Videos using Quality Assessment Networks

A Large RGB-D Dataset for Semi-supervised Monocular Depth Estimation

Student Becoming the Master: Knowledge Amalgamation for Joint Scene Parsing, Depth Estimation, and More

Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation

Non-Lambertian Surface Shape and Reflectance Reconstruction Using Concentric Multi-Spectral Light Field

Online Adaptation through Meta-Learning for Stereo Depth Estimation

Recurrent Neural Network for (Un-)supervised Learning of Monocular VideoVisual Odometry and Depth

Unstructured Multi-View Depth Estimation Using Mask-Based Multiplane Representation

Learning monocular depth estimation infusing traditional stereo knowledge

Visualization of Convolutional Neural Networks for Monocular Depth Estimation

Double Refinement Network for Efficient Indoor Monocular Depth Estimation

CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depth

Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation

Defogging Kinect: Simultaneous Estimation of Object Region and Depth in Foggy Scenes

Synthesizing a 4D Spatio-Angular Consistent Light Field from a Single Image

Fast Deep Stereo with 2D Convolutional Processing of Cost Signatures

Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations

GEN-SLAM: Generative Modeling for Monocular Simultaneous Localization and Mapping

AuxNet: Auxiliary tasks enhanced Semantic Segmentation for Automated Driving

A Deeper Insight into the UnDEMoN: Unsupervised Deep Network for Depth and Ego-Motion Estimation

UnDEMoN 2.0: Improved Depth and Ego Motion Estimation through Deep Image Sampling

Event-Based Structured Light for Depth Reconstruction using Frequency Tagged Light Patterns

Learning Deeply Supervised Good Features to Match for Dense Monocular Reconstruction

SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation

Deep Learning with Cinematic Rendering: Fine-Tuning Deep Neural Networks Using Photorealistic Medical Images

Monocular Fisheye Camera Depth Estimation Using Sparse LiDAR Supervision

Revisiting Single Image Depth Estimation: Toward Higher Resolution Maps with Accurate Object Boundaries

Real Time Dense Depth Estimation by Fusing Stereo with Sparse Depth Measurements

Monocular Depth Estimation by Learning from Heterogeneous Datasets

Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks?

Learning Monocular Depth by Distilling Cross-domain Stereo Networks

Learning monocular depth estimation with unsupervised trinocular assumptions

T2Net: Synthetic-to-Realistic Translation for Solving Single-Image Depth Estimation Tasks

Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network

Towards real-time unsupervised monocular depth estimation on CPU

Unsupervised Adversarial Depth Estimation using Cycled Generative Networks

Self-supervised Learning for Dense Depth Estimation in Monocular Endoscopy

OmniDepth: Dense Depth Estimation for Indoors Spherical Panoramas

Generalizable Data-free Objective for Crafting Universal Adversarial Perturbations

Joint Blind Motion Deblurring and Depth Estimation of Light Field

AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation

Recurrent Neural Network for Learning DenseDepth and Ego-Motion from Video

PAD-Net: Multi-Tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing

Depth from Monocular Images using a Semi-Parallel Deep Neural Network (SPDNN) Hybrid Architecture

PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image

EPINET: A Fully-Convolutional Neural Network Using Epipolar Geometry for Depth from Light Field Images

Self-Supervised Relative Depth Learning for Urban Scene Understanding

Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation

Learning Depth from Single Images with Deep Neural Network Embedding Focal Length

Fusion of stereo and still monocular depth estimates in a self-supervised learning context

Self-Supervised Monocular Image Depth Learning and Confidence Estimation

Approximating Continuous Functions by ReLU Nets of Minimal Width

Monocular Depth Estimation using Multi-Scale Continuous CRFs as Sequential Deep Networks

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks

Joint Voxel and Coordinate Regression for Accurate 3D Facial Landmark Localization

Size-to-depth: A New Perspective for Single Image Depth Estimation

Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations

J-MOD$^{2}$: Joint Monocular Obstacle Detection and Depth Estimation

Recurrent Scene Parsing with Perspective Understanding in the Loop

Automatic Discovery and Geotagging of Objects from Street View Imagery

Deep Learning and Conditional Random Fields-based Depth Estimation and Topographical Reconstruction from Conventional Endoscopy

Depth Assisted Full Resolution Network for Single Image-based View Synthesis

An Adaptive Framework for Missing Depth Inference Using Joint Bilateral Filter

Depth estimation using structured light flow -- analysis of projected pattern flow on an object's surface --

Exact Blur Measure Outperforms Conventional Learned Features for Depth Finding

Estimating Depth from Monocular Images as Classification Using Deep Fully Convolutional Residual Networks

Accurate Light Field Depth Estimation with Superpixel Regularization over Partially Occluded Regions

Hybrid Light Field Imaging for Improved Spatial Resolution and Depth Range

DepthCut: Improved Depth Edge Estimation Using Multiple Unreliable Channels

Self-Supervised Siamese Learning on Stereo Image Pairs for Depth Estimation in Robotic Surgery

Out-of-focus: Learning Depth from Image Bokeh for Robotic Perception

Single image depth estimation by dilated deep residual convolutional neural network and soft-weight-sum inference

OCRAPOSE II: An OCR-based indoor positioning system using mobile phone images

Unsupervised Monocular Depth Estimation with Left-Right Consistency

Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation

Analyzing Modular CNN Architectures for Joint Depth Prediction and Semantic Segmentation

Computing Egomotion with Local Loop Closures for Egocentric Videos

Parse Geometry from a Line: Monocular Depth Estimation with Partial Laser Observation

Two-stage Convolutional Part Heatmap Regression for the 1st 3D Face Alignment in the Wild (3DFAW) Challenge

Joint Semantic Segmentation and Depth Estimation with Deep Convolutional Networks

Deeper Depth Prediction with Fully Convolutional Residual Networks

Depth Estimation Through a Generative Model of Light Field Synthesis

Occlusion-Model Guided Anti-Occlusion Depth Estimation in Light Field

Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue

3DFS: Deformable Dense Depth Fusion and Segmentation for Object Reconstruction from a Handheld Camera

Unified Depth Prediction and Intrinsic Image Decomposition from a Single Image via Joint Convolutional Neural Fields

Image and Depth from a Single Defocused Image Using Coded Aperture Photography

Discriminative Training of Deep Fully-connected Continuous CRF with Task-specific Loss

Automated Management of Pothole related Disasters Using Image Processing and Geotagging

Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields

Structured Depth Prediction in Challenging Monocular Video Sequences

Depth Extraction from Videos Using Geometric Context and Occlusion Boundaries

Depth Reconstruction from Sparse Samples: Representation, Algorithm, and Sampling

Analog Signal Processing Approach for Coarse and Fine Depth Estimation

Deep Convolutional Neural Fields for Depth Estimation from a Single Image

Formulation Of A N-Degree Polynomial For Depth Estimation using a Single Image

GSIP: Green Semantic Segmentation of Large-Scale Indoor Point Clouds

Scan-based Semantic Segmentation of LiDAR Point Clouds: An Experimental Study

Quantifying point cloud realism through adversarially learned latent representations

Fast Point Voxel Convolution Neural Network with Selective Feature Fusion for Point Cloud Semantic Segmentation

Semantic Segmentation-assisted Scene Completion for LiDAR Point Clouds

Multi-resolution deep learning pipeline for dense large scale point clouds

OneFlow: One-class flow for anomaly detection based on a minimal volume region

LoGG3D-Net: Locally Guided Global Descriptor Learning for 3D Place Recognition

3D Point Cloud Completion with Geometric-Aware Adversarial Augmentation

Superquadric Object Representation for Optimization-based Semantic SLAM

PC2-PU: Patch Correlation and Position Correction for Effective Point Cloud Upsampling

Minimal Adversarial Examples for Deep Learning on 3D Point Clouds

A Point-Cloud Deep Learning Framework for Prediction of Fluid Flow Fields on Irregular Geometries

A Divide-and-Merge Point Cloud Clustering Algorithm for LiDAR Panoptic Segmentation

Lifting 2D Object Locations to 3D by Discounting LiDAR Outliers across Objects and Views

PointManifoldCut: Point-wise Augmentation in the Manifold for Point Clouds

Tesla-Rapture: A Lightweight Gesture Recognition System from mmWave Radar Point Clouds

Sparse PointPillars: Maintaining and Exploiting Input Sparsity to Improve Runtime on Embedded Systems

MonteFloor: Extending MCTS for Reconstructing Accurate Large-Scale Floor Plans

Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-based Perception

A Self-Supervised Deep Framework for Reference Bony Shape Estimation in Orthognathic Surgical Planning

Residual 3D Scene Flow Learning with Context-Aware Feature Extraction

Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking

Multi-Features Guidance Network for partial-to-partial point cloud registration

Neural-IMLS: Learning Implicit Moving Least-Squares for Surface Reconstruction from Unoriented Point clouds

Superpoint-guided Semi-supervised Semantic Segmentation of 3D Point Clouds

Certifiable Outlier-Robust Geometric Perception: Exact Semidefinite Relaxations and Scalable Global Optimization

Spatio-temporal-spectral-angular observation model that integrates observations from UAV and mobile mapping vehicle for better urban mapping

CORSAIR: Convolutional Object Retrieval and Symmetry-AIded Registration

TearingNet: Point Cloud Autoencoder to Learn Topology-Friendly Representations

Graph Signal Processing for Geometric Data and Beyond: Theory and Applications

Dense Supervision Propagation for Weakly Supervised Semantic Segmentation on 3D Point Clouds

CAP-Net: Correspondence-Aware Point-view Fusion Network for 3D Shape Analysis

3D Shape Generation and Completion through Point-Voxel Diffusion

From noisy point clouds to complete ear shapes: unsupervised pipeline

PSE-Match: A Viewpoint-free Place Recognition Method with Parallel Semantic Embedding

SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks

ICM-3D: Instantiated Category Modeling for 3D Instance Segmentation

Cascaded Refinement Network for Point Cloud Completion with Self-supervision

Investigate Indistinguishable Points in Semantic Segmentation of 3D Point Cloud

CSG-Stump: A Learning Friendly CSG-Like Representation for Interpretable Shape Parsing

H2O: Two Hands Manipulating Objects for First Person Interaction Recognition

Occlusion-robust Visual Markerless Bone Tracking for Computer-Assisted Orthopaedic Surgery

Unsupervised Depth Completion with Calibrated Backprojection Layers

Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases

Generative Zero-Shot Learning for Semantic Segmentation of 3D Point Cloud

Voxel-based Network for Shape Completion by Leveraging Edge Generation

PR-GCN: A Deep Graph Convolutional Network with Point Refinement for 6D Pose Estimation

A Dynamic 3D Spontaneous Micro-expression Database: Establishment and Evaluation

A Technical Survey and Evaluation of Traditional Point Cloud Clustering Methods for LiDAR Panoptic Segmentation

Vis2Mesh: Efficient Mesh Reconstruction from Unstructured Point Clouds of Large Scenes with Learned Virtual View Visibility

Quality assessment of image matchers for DSM generation -- a comparative study based on UAV images

LIGA-Stereo: Learning LiDAR Geometry Aware Representations for Stereo-based 3D Detector

Perception-Aware Multi-Sensor Fusion for 3D LiDAR Semantic Segmentation

Visual Enhanced 3D Point Cloud Reconstruction from A Single Image

Bridging the Reality Gap for Pose Estimation Networks using Sensor-Based Domain Randomization

Out-of-Core Surface Reconstruction via Global $TGV$ Minimization

Towards Efficient Point Cloud Graph Neural Networks Through Architectural Simplification

AdaFit: Rethinking Learning-based Normal Estimation on Point Clouds

3D-SiamRPN: An End-to-End Learning Method for Real-Time 3D Single Object Tracking Using Raw Point Cloud

HandFoldingNet: A 3D Hand Pose Estimation Network Using Multiscale-Feature Guided Folding of a 2D Hand Skeleton

Box-Aware Feature Enhancement for Single Object Tracking on Point Clouds

Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation

(Just) A Spoonful of Refinements Helps the Registration Error Go Down

ASFM-Net: Asymmetrical Siamese Feature Matching Network for Point Completion

A Registration-aided Domain Adaptation Network for 3D Point Cloud Based Place Recognition

SSPU-Net: Self-Supervised Point Cloud Upsampling via Differentiable Rendering

Wood-leaf classification of tree point cloud based on intensity and geometrical information

The decomposition of the higher-order homology embedding constructed from the $k$-Laplacian

Helmholtzian Eigenmap: Topological feature discovery & edge flow learning from point cloud data

RGL-NET: A Recurrent Graph Learning framework for Progressive Part Assembly

Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis

P2-Net: Joint Description and Detection of Local Features for Pixel and Point Matching

Unsupervised Segmentation for Terracotta Warrior with Seed-Region-Growing CNN(SRG-Net)

Multi Point-Voxel Convolution (MPVConv) for Deep Learning on Point Clouds

HRegNet: A Hierarchical Network for Large-scale Outdoor LiDAR Point Cloud Registration

Pre-Clustering Point Clouds of Crop Fields Using Scalable Methods

Correspondence-Free Point Cloud Registration with SO(3)-Equivariant Implicit Shape Representations

Registration of 3D Point Sets Using Correntropy Similarity Matrix

Pose Normalization of Indoor Mapping Datasets Partially Compliant to the Manhattan World Assumption

Scalable Surface Reconstruction with Delaunay-Graph Neural Networks

HDMapNet: An Online HD Map Construction and Evaluation Framework

Intraoperative Liver Surface Completion with Graph Convolutional VAE

Learning 3D Dense Correspondence via Canonical Point Autoencoder

HIDA: Towards Holistic Indoor Understanding for the Visually Impaired via Semantic Instance Segmentation with a Wearable Solid-State LiDAR Sensor

Learning Semantic Segmentation of Large-Scale Point Clouds with Random Sampling

PillarSegNet: Pillar-based Semantic Grid Map Estimation using Sparse LiDAR Data

Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts

The Neurally-Guided Shape Parser: A Monte Carlo Method for Hierarchical Labeling of Over-segmented 3D Shapes

PALMAR: Towards Adaptive Multi-inhabitant Activity Recognition in Point-Cloud Technology

SeqNetVLAD vs PointNetVLAD: Image Sequence vs 3D Point Clouds for Day-Night Place Recognition

Deep Evaluation Metric: Learning to Evaluate Simulated Radar Point Clouds for Virtual Testing of Autonomous Driving

FloorPP-Net: Reconstructing Floor Plans using Point Pillars for Scan-to-BIM

Improved Generalization Bounds of Group Invariant / Equivariant Deep Networks via Quotient Feature Spaces

Neural Network Modeling of Probabilities for Coding the Octree Representation of Point Clouds

Go with the Flows: Mixtures of Normalizing Flows for Point Cloud Generation and Reconstruction

SE-MD: A Single-encoder multiple-decoder deep network for point cloud generation from 2D images

Synthesizing Long-Term 3D Human Motion and Interaction in 3D Scenes

Shape-Preserving Dimensionality Reduction : An Algorithm and Measures of Topological Equivalence

PMP-Net: Point Cloud Completion by Learning Multi-step Point Moving Paths

Spatially Invariant Unsupervised 3D Object Segmentation with Graph Neural Networks

Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline

Sign-Agnostic Implicit Learning of Surface Self-Similarities for Shape Modeling and Reconstruction from Raw Point Clouds

Image2Point: 3D Point-Cloud Understanding with Pretrained 2D ConvNets

Point Cloud Failure Criterion for Composites using k-Nearest Neighbor Classification

PC-DAN: Point Cloud based Deep Affinity Network for 3D Multi-Object Tracking (Accepted as an extended abstract in JRDB-ACT Workshop at CVPR21)

Spline Positional Encoding for Learning 3D Implicit Signed Distance Fields

Refining the bounding volumes for lossless compression of voxelized point clouds geometry

SN-Graph: a Minimalist 3D Object Representation for Classification

Know Your Surroundings: Panoramic Multi-Object Tracking by Multimodality Collaboration

Xihe: A 3D Vision-based Lighting Estimation Framework for Mobile Augmented Reality

2nd Place Solution for IJCAI-PRICAI 2020 3D AI Challenge: 3D Object Reconstruction from A Single Image

Revisiting 2D Convolutional Neural Networks for Graph-based Applications

Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces

Omni-supervised Point Cloud Segmentation via Gradual Receptive Field Component Reasoning

Towards Automatic Sizing for PPE with a Point Cloud Based Variational Autoencoder

GPR-based Model Reconstruction System for Underground Utilities Using GPRNet

StrobeNet: Category-Level Multiview Reconstruction of Articulated Objects

AWCD: An Efficient Point Cloud Processing Approach via Wasserstein Curvature

Poisoning MorphNet for Clean-Label Backdoor Attack to Point Clouds

ACORN: Adaptive Coordinate Networks for Neural Scene Representation

Deep Weighted Consensus: Dense correspondence confidence maps for 3D shape registration

Pairwise Point Cloud Registration using Graph Matching and Rotation-invariant Features

Weakly Supervised Pseudo-Label assisted Learning for ALS Point Cloud Semantic Segmentation

Pedestrian Detection in 3D Point Clouds using Deep Neural Networks

PointLIE: Locally Invertible Embedding for Point Cloud Sampling and Recovery

D-OccNet: Detailed 3D Reconstruction Using Cross-Domain Learning

3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic Segmentation

Reconstruction of Convex Polytope Compositions from 3D Point-clouds

PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds

LiDARNet: A Boundary-Aware Domain Adaptation Model for Point Cloud Semantic Segmentation

LCCNet: LiDAR and Camera Self-Calibration using Cost Volume Network

JRDB: A Dataset and Benchmark of Egocentric Robot Visual Perception of Humans in Built Environments

RANSIC: Fast and Highly Robust Estimation for Rotation Search and Point Cloud Registration using Invariant Compatibility

Geometric Deep Learning on Anatomical Meshes for the Prediction of Alzheimer's Disease

A metric for evaluating 3D reconstruction and mapping performance with no ground truthing

A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups

An Improved Discriminative Optimization for 3D Rigid Point Cloud Registration

One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation

SCALE: Modeling Clothed Humans with a Surface Codec of Articulated Local Elements

A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation

MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition

SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation

Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion

Semantic Scene Completion using Local Deep Implicit Functions on LiDAR Data

Towards Efficient Graph Convolutional Networks for Point Cloud Handling

MOPS-Net: A Matrix Optimization-driven Network forTask-Oriented 3D Point Cloud Downsampling

CAPRI-Net: Learning Compact CAD Shapes with Adaptive Primitive Assembly

Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach

OpenGF: An Ultra-Large-Scale Ground Filtering Dataset Built Upon Open ALS Point Clouds Around the World

Approach for modeling single branches of meadow orchard trees with 3D point clouds

SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds with 1000x Fewer Labels

Occlusion Guided Self-supervised Scene Flow Estimation on 3D Point Clouds

Iso-Points: Optimizing Neural Implicit Surfaces with Hybrid Representations

CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Clouds

Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification

On Adversarial Robustness of 3D Point Cloud Classification under Adaptive Attacks

Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges

SALA: Soft Assignment Local Aggregation for Parameter Efficient 3D Semantic Segmentation

Potential Convolution: Embedding Point Clouds into Potential Fields

A Semantic Segmentation Network for Urban-Scale Building Footprint Extraction Using RGB Satellite Imagery

DeepDT: Learning Geometry From Delaunay Triangulation for Surface Reconstruction

Verifiability and Predictability: Interpreting Utilities of Network Architectures for Point Cloud Processing

iCurb: Imitation Learning-based Detection of Road Curbs using Aerial Images for Autonomous Driving

3D AffordanceNet: A Benchmark for Visual Object Affordance Understanding

Few-Data Guided Learning Upon End-to-End Point Cloud Network for 3D Face Recognition

Online Learning of a Probabilistic and Adaptive Scene Representation

Fast and Accurate Normal Estimation for Point Cloud via Patch Stitching

Complete & Label: A Domain Adaptation Approach to Semantic Segmentation of LiDAR Point Clouds

Sparse Auxiliary Networks for Unified Monocular Depth Prediction and Completion

Robust Detection of Non-overlapping Ellipses from Points with Applications to Circular Target Extraction in Images and Cylinder Detection in Point Clouds

Towards Automatic Digital Documentation and Progress Reporting of Mechanical Construction Pipes using Smartphones

Point Cloud Instance Segmentation using Probabilistic Embeddings

Free-form Description Guided 3D Visual Graph Network for Object Grounding in Point Cloud

PU-GCN: Point Cloud Upsampling using Graph Convolutional Networks

Cloud2Curve: Generation and Vectorization of Parametric Sketches

MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization

Exploiting Local Geometry for Feature and Graph Construction for Better 3D Point Cloud Processing with Graph Neural Networks

SegGroup: Seg-Level Supervision for 3D Instance and Semantic Segmentation

Panoptic-PolarNet: Proposal-free LiDAR Point Cloud Panoptic Segmentation

3D Point Cloud Registration with Multi-Scale Architecture and Self-supervised Fine-tuning

VDM-DA: Virtual Domain Modeling for Source Data-free Domain Adaptation

Bidirectional Projection Network for Cross Dimension Scene Understanding

RPVNet: A Deep and Efficient Range-Point-Voxel Fusion Network for LiDAR Point Cloud Segmentation

StablePose: Learning 6D Object Poses from Geometrically Stable Patches

IF-Defense: 3D Adversarial Point Cloud Defense via Implicit Function based Restoration

LRGNet: Learnable Region Growing for Class-Agnostic Point Cloud Segmentation

Lite-HDSeg: LiDAR Semantic Segmentation Using Lite Harmonic Dense Convolutions

Juggling With Representations: On the Information Transfer Between Imagery, Point Clouds, and Meshes for Multi-Modal Semantics

Unsupervised 3D Learning for Shape Analysis via Multiresolution Instance Discrimination

An Efficient Hypergraph Approach to Robust Point Cloud Resampling

Instance Segmentation GNNs for One-Shot Conformal Tracking at the LHC

Regularization Strategy for Point Cloud via Rigidly Mixed Sample

How Privacy-Preserving are Line Clouds? Recovering Scene Details from 3D Lines

CRLF: Automatic Calibration and Refinement based on Line Feature for LiDAR and Camera in Road Scenes

EllipsoidNet: Ellipsoid Representation for Point Cloud Classification and Segmentation

Self-Supervised Learning of Part Mobility from Point Cloud Sequence

Deep learning based geometric registration for medical images: How accurate can we get without visual features?

FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud Segmentation

SKD: Keypoint Detection for Point Clouds using Saliency Estimation

Point Cloud Upsampling and Normal Estimation using Deep Learning for Robust Surface Reconstruction

LPMNet: Latent Part Modification and Generation for 3D Point Clouds

PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features

UnsupervisedR&R: Unsupervised Point Cloud Registration via Differentiable Rendering

ePointDA: An End-to-End Simulation-to-Real Domain Adaptation Framework for LiDAR Point Cloud Segmentation

Three dimensional unique identifier based automated georeferencing and coregistration of point clouds in underground environment

NPTC-net: Narrow-Band Parallel Transport Convolutional Neural Network on Point Clouds

Curiosity-driven 3D Scene Structure from Single-image Self-supervision

Panoster: End-to-end Panoptic Segmentation of LiDAR Point Clouds

An underwater binocular stereo matching algorithm based on the best search domain

A procedure for automated tree pruning suggestion using LiDAR scans of fruit trees

PatchNets: Patch-Based Generalizable Deep Implicit 3D Shape Representations

From a Point Cloud to a Simulation Model: Bayesian Segmentation and Entropy based Uncertainty Estimation for 3D Modelling

Graph-based methods for analyzing orchard tree structure using noisy point cloud data

A Fast Point Cloud Ground Segmentation Approach Based on Coarse-To-Fine Markov Random Field

The Devils in the Point Clouds: Studying the Robustness of Point Cloud Convolutions

Pseudoinverse Graph Convolutional Networks: Fast Filters Tailored for Large Eigengaps of Dense Graphs and Hypergraphs

Virtual laser scanning with HELIOS++: A novel take on ray tracing-based simulation of topographic 3D laser scanning

Cross-modal Learning for Domain Adaptation in 3D Semantic Segmentation

A Smooth Representation of Belief over SO(3) for Deep Rotation Learning with Uncertainty

Semantic Implicit Neural Scene Representations With Semi-Supervised Training

Leveraging Planar Regularities for Point Line Visual-Inertial Odometry

Robust Kernel-based Feature Representation for 3D Point Cloud Analysis via Circular Graph Convolutional Network

DeepCLR: Correspondence-Less Architecture for Deep End-to-End Point Cloud Registration

PvDeConv: Point-Voxel Deconvolution for Autoencoding CAD Construction in 3D

Joint Scene and Object Tracking for Cost-Effective Augmented Reality Assisted Patient Positioning in Radiation Therapy

Efficient 3D Point Cloud Feature Learning for Large-Scale Place Recognition

Cycle Registration in Persistent Homology with Applications in Topological Bootstrap

Learning Rotation-Invariant Representations of Point Clouds Using Aligned Edge Convolutional Neural Networks

Compositional Prototype Network with Multi-view Comparision for Few-Shot Point Cloud Semantic Segmentation

Semantic Segmentation on Swiss3DCities: A Benchmark Study on Aerial Photogrammetric 3D Pointcloud Dataset

Segmentation of structural parts of rosebush plants with 3D point-based deep learning methods

Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose Estimation

PanoNet3D: Combining Semantic and Geometric Understanding for LiDARPoint Cloud Detection

S3CNet: A Sparse Semantic Scene Completion Network for LiDAR Point Clouds

NeuralQAAD: An Efficient Differentiable Framework for High Resolution Point Cloud Compression

Learning Category-level Shape Saliency via Deep Implicit Surface Networks

DUDE: Deep Unsigned Distance Embeddings for Hi-Fidelity Representation of Complex 3D Surfaces

Uncertainty Estimation in Deep Neural Networks for Point Cloud Segmentation in Factory Planning

ODFNet: Using orientation distribution functions to characterize 3D point clouds

Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion

Automatic sampling and training method for wood-leaf classification based on tree terrestrial point cloud

CIA-SSD: Confident IoU-Aware Single-Stage Object Detector From Point Cloud

Sparse Convolutions on Continuous Domains for Point Cloud and Event Stream Networks

MEVA: A Large-Scale Multiview, Multimodal Video Dataset for Activity Detection

Cross-modal registration using point clouds and graph-matching in the context of correlative microscopies

SRG-Net: Unsupervised Segmentation for Terracotta Warrior Point Cloud with 3D Pointwise CNN methods

Exploring Deep 3D Spatial Encodings for Large-Scale 3D Scene Understanding

Robust building footprint extraction from big multi-sensor data using deep competition network

Spherical Interpolated Convolutional Network with Distance-Feature Density for 3D Semantic Segmentation of Point Clouds

Grasping Field: Learning Implicit Representations for Human Grasps

AdaCoSeg: Adaptive Shape Co-Segmentation with Group Consistency Loss

SAMA-VTOL: A new unmanned aircraft system for remotely sensed data collection

Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation

Deep Positional and Relational Feature Learning for Rotation-Invariant Point Cloud Analysis

ACSC: Automatic Calibration for Non-repetitive Scanning Solid-State LiDAR and Camera Systems

CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations

Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting

Multi Projection Fusion for Real-time Semantic Segmentation of 3D LiDAR Point Clouds

Instant recovery of shape from spectrum via latent space connections

PBP-Net: Point Projection and Back-Projection Network for 3D Point Cloud Segmentation

Do not trust the neighbors! Adversarial Metric Learning for Self-Supervised Scene Flow Estimation

LG-GAN: Label Guided Adversarial Network for Flexible Targeted Attack of Point Cloud-based Deep Networks

A Simple and Efficient Registration of 3D Point Cloud and Image Data for Indoor Mobile Mapping System

Reconfigurable Voxels: A New Representation for LiDAR-Based Point Clouds

Empowering Knowledge Distillation via Open Set Recognition for Robust 3D Point Cloud Classification

PLOP: Probabilistic poLynomial Objects trajectory Planning for autonomous driving

F-Siamese Tracker: A Frustum-based Double Siamese Network for 3D Single Object Tracking

Learning Occupancy Function from Point Clouds for Surface Reconstruction

UAV LiDAR Point Cloud Segmentation of A Stack Interchange with Deep Neural Networks

Tracking from Patterns: Learning Corresponding Patterns in Point Clouds for 3D Object Tracking

SelfVoxeLO: Self-supervised LiDAR Odometry with Voxel-based Deep Neural Networks

MaskNet: A Fully-Convolutional Network to Estimate Inlier Points

Self-supervised Learning of Point Clouds via Orientation Estimation

PointManifold: Using Manifold Learning for Point Cloud Classification

Skeleton-bridged Point Completion: From Global Inference to Local Adjustment

Torch-Points3D: A Modular Multi-Task Frameworkfor Reproducible Deep Learning on 3D Point Clouds

Refinement of Predicted Missing Parts Enhance Point Cloud Completion

Representing Point Clouds with Generative Conditional Invertible Flow Networks

Meshing Point Clouds with Predicted Intrinsic-Extrinsic Ratio Guidance

ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds

Improving Semantic Analysis on Point Clouds via Auxiliary Supervision of Local Geometric Priors

RGB2LIDAR: Towards Solving Large-Scale Cross-Modal Visual Localization

Probabilistic Semantic Mapping for Urban Autonomous Driving Applications

Stem-leaf segmentation and phenotypic trait extraction of maize shoots from three-dimensional point cloud

TRANSPR: Transparency Ray-Accumulating Neural 3D Scene Point Renderer

Unsupervised Feedforward Feature (UFF) Learning for Point Cloud Classification and Segmentation

PillarFlow: End-to-end Birds-eye-view Flow Estimation for Autonomous Driving

How semantic and geometric information mutually reinforce each other in ToF object localization

PASS3D: Precise and Accelerated Semantic Segmentation for 3D Point Cloud

TORNADO-Net: mulTiview tOtal vaRiatioN semAntic segmentation with Diamond inceptiOn module

LC-NAS: Latency Constrained Neural Architecture Search for Point Cloud Networks

Generating synthetic photogrammetric data for training deep learning based 3D point cloud segmentation models

Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded Platform

Pix2Surf: Learning Parametric 3D Surface Models of Objects from Images

SoftPoolNet: Shape Descriptor for Point Cloud Completion and Classification

Mesorasi: Architecture Support for Point Cloud Analytics via Delayed-Aggregation

Augmented Semantic Signatures of Airborne LiDAR Point Clouds for Comparison

Iterative Distance-Aware Similarity Matrix Convolution with Mutual-Supervised Point Elimination for Efficient Point Cloud Registration

Cylinder3D: An Effective 3D Framework for Driving-scene LiDAR Semantic Segmentation

Monocular Camera Localization in Prior LiDAR Maps with 2D-3D Line Correspondences

PointPWC-Net: A Coarse-to-Fine Network for Supervised and Self-Supervised Scene Flow Estimation on 3D Point Clouds

Cascaded Non-local Neural Network for Point Cloud Semantic Segmentation

mmFall: Fall Detection using 4D MmWave Radar and a Hybrid Variational RNN AutoEncoder

Recovery of Superquadrics from Range Images using Deep Learning: A Preliminary Study

Real-Time Point Cloud Fusion of Multi-LiDAR Infrastructure Sensor Setups with Unknown Spatial Location and Orientation

Self-Prediction for Joint Instance and Semantic Segmentation of Point Clouds

MRGAN: Multi-Rooted 3D Shape Generation with Unsupervised Part Disentanglement

Through the Looking Glass: Neural 3D Reconstruction of Transparent Shapes

Combining Implicit Function Learning and Parametric Models for 3D Human Reconstruction

JRMOT: A Real-Time 3D Multi-Object Tracker and a New Large-Scale Dataset

Dense Hybrid Recurrent Multi-view Stereo Net with Dynamic Consistency Checking

Points2Surf: Learning Implicit Surfaces from Point Cloud Patches

Discrete Point Flow Networks for Efficient Point Cloud Generation

GRNet: Gridding Residual Network for Dense Point Cloud Completion

Blended Convolution and Synthesis for Efficient Discrimination of 3D Shapes

PointAR: Efficient Lighting Estimation for Mobile Augmented Reality

AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds

PT2PC: Learning to Generate 3D Point Cloud Shapes from Part Tree Conditions

Pose2RGBD. Generating Depth and RGB images from absolute positions

DRWR: A Differentiable Renderer without Rendering for Unsupervised 3D Structure Learning from Silhouette Images

SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving

Camera-Lidar Integration: Probabilistic sensor fusion for semantic mapping

PointMask: Towards Interpretable and Bias-Resilient Point Cloud Processing

Learning Graph-Convolutional Representations for Point Cloud Denoising

Detail Preserved Point Cloud Completion via Separated Feature Aggregation

Evaluating Uncertainty Estimation Methods on 3D Semantic Segmentation of Point Clouds

Segment as Points for Efficient Online Multi-Object Tracking and Segmentation

PointTrack++ for Effective Online Multi-Object Tracking and Segmentation

Motion Guided LIDAR-camera Self-calibration and Accelerated Depth Upsampling for Autonomous Vehicles

A Closer Look at Local Aggregation Operators in Point Cloud Analysis

Leveraging Temporal Information for 3D Detection and Domain Adaptation

Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation

RPM-Net: Recurrent Prediction of Motion and Parts from Point Cloud

Discontinuous and Smooth Depth Completion with Binary Anisotropic Diffusion Tensor

SASO: Joint 3D Semantic-Instance Segmentation via Multi-scale Semantic Association and Salient Point Clustering Optimization

AdvectiveNet: An Eulerian-Lagrangian Fluidic reservoir for Point Cloud Processing

3DMotion-Net: Learning Continuous Flow Function for 3D Motion Prediction

Coresets for Estimating Means and Mean Square Error with Limited Greedy Samples

A Nearest Neighbor Network to Extract Digital Terrain Models from 3D Point Clouds

A block coordinate descent optimizer for classification problems exploiting convexity

LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World

RasterNet: Modeling Free-Flow Speed using LiDAR and Overhead Imagery

Cityscapes 3D: Dataset and Benchmark for 9 DoF Vehicle Detection

Local-Area-Learning Network: Meaningful Local Areas for Efficient Point Cloud Analysis

PFCNN: Convolutional Neural Networks on 3D Surfaces Using Parallel Frames

Minimum Potential Energy of Point Cloud for Robust Global Registration

Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection

Tree Annotations in LiDAR Data Using Point Densities and Convolutional Neural Networks

Fast Synthetic LiDAR Rendering via Spherical UV Unwrapping of Equirectangular Z-Buffer Images

GFPNet: A Deep Network for Learning Shape Completion in Generic Fitted Primitives

3D Lidar Mapping Relative Accuracy Automatic Evaluation Algorithm

Unconstrained Matching of 2D and 3D Descriptors for 6-DOF Pose Estimation

P2B: Point-to-Box Network for 3D Object Tracking in Point Clouds

False Positive Removal for 3D Vehicle Detection with Penetrated Point Classifier

AutoSweep: Recovering 3D Editable Objectsfrom a Single Photograph

Dilated Point Convolutions: On the Receptive Field Size of Point Convolutions on 3D Point Clouds

PointHop++: A Lightweight Learning Model on Point Sets for 3D Classification

Adaptive Hierarchical Down-Sampling for Point Cloud Classification

Learning Structural Graph Layouts and 3D Shapes for Long Span Bridges 3D Reconstruction

Holistic Parameteric Reconstruction of Building Models from Point Clouds

Weakly Supervised Semantic Segmentation in 3D Graph-Structured Point Clouds of Wild Scenes

Automatic clustering of Celtic coins based on 3D point cloud pattern analysis

Fast Geometric Surface based Segmentation of Point Cloud from Lidar Data

PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling

From Image Collections to Point Clouds with Self-supervised Shape and Pose Networks

Feature-metric Registration: A Fast Semi-supervised Approach for Robust Point Cloud Registration without Correspondences

LRF-Net: Learning Local Reference Frames for 3D Local Shape Description and Matching

RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds

From Planes to Corners: Multi-Purpose Primitive Detection in Unorganized 3D Point Clouds

Local intrinsic dimensionality estimators based on concentration of measure

Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways

Flex-Convolution (Million-Scale Point-Cloud Learning Beyond Grid-Worlds)

DALES: A Large-scale Aerial LiDAR Data Set for Semantic Segmentation

Self-supervised Feature Learning by Cross-modality and Cross-view Correspondences

Learning 3D Semantic Scene Graphs from 3D Indoor Reconstructions

3D Dynamic Point Cloud Denoising via Spatial-Temporal Graph Learning

Real-Time Fruit Recognition and Grasping Estimation for Autonomous Apple Harvesting

Intrinsic Point Cloud Interpolation via Dual Latent Space Navigation

PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation

Knowledge as Priors: Cross-Modal Knowledge Generalization for Datasets without Superior Knowledge

SK-Net: Deep Learning on Point Cloud via End-to-end Discovery of Spatial Keypoints

xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation

Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimation

G2L-Net: Global to Local Network for Real-time 6D Pose Estimation with Embedding Vector Features

Adversarial Generation of Continuous Implicit Shape Representations

Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds

DeepFit: 3D Surface Fitting via Neural Network Weighted Least Squares

Curved Buildings Reconstruction from Airborne LiDAR Data by Matching and Deforming Geometric Primitives

LRC-Net: Learning Discriminative Features on Point Clouds by Encoding Local Region Contexts

Efficient and Robust Shape Correspondence via Sparsity-Enforced Quadratic Assignment

A new geodesic-based feature for characterization of 3D shapes: application to soft tissue organ temporal deformations

Fast and Accurate 3D Hand Pose Estimation via Recurrent Neural Network for Capturing Hand Articulations

Scan2Plan: Efficient Floorplan Generation from 3D Scans of Indoor Scenes

Learning-Based Human Segmentation and Velocity Estimation Using Automatic Labeled LiDAR Sequence for Training

Global visual localization in LiDAR-maps through shared 2D-3D embedding space

DirectShape: Direct Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation

SOIC: Semantic Online Initialization and Calibration for LiDAR and Camera

DeepPCO: End-to-End Point Cloud Odometry through Deep Parallel Neural Network

A Benchmark for LiDAR-based Panoptic Segmentation based on KITTI

Automated classification of stems and leaves of potted plants based on point cloud data

A Practical Maximum Clique Algorithm for Matching with Pairwise Constraints

Defense-PointNet: Protecting PointNet Against Adversarial Attacks

Fault Diagnosis in Microelectronics Attachment via Deep Learning Analysis of 3D Laser Scans

Unpaired Point Cloud Completion on Real Scans using Adversarial Training

MREC: a fast and versatile framework for aligning and matching point clouds with applications to single cell molecular data

Shallow Water Bathymetry Mapping from UAV Imagery based on Machine Learning

SegVoxelNet: Exploring Semantic Context and Depth-aware Features for 3D Vehicle Detection from Point Cloud

Tranquil Clouds: Neural Networks for Learning Temporally Coherent Features in Point Clouds

SceneEncoder: Scene-Aware Semantic Segmentation of Point Clouds with A Learnable Scene Descriptor

A novel tree-structured point cloud dataset for skeletonization algorithm evaluation

Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation

DAR-Net: Dynamic Aggregation Network for Semantic Scene Segmentation

Point2Node: Correlation Learning of Dynamic-Node for Point Cloud Feature Modeling

Learning to Generate Dense Point Clouds with Textures on Multiple Categories

P$^2$GNet: Pose-Guided Point Cloud Generating Networks for 6-DoF Object Pose Estimation

Exploring Spatial Context for 3D Semantic Segmentation of Point Clouds

Deep-learning-based classification and retrieval of components of a process plant from segmented point clouds

Line-based Camera Pose Estimation in Point Cloud of Structured Environments

Parallel Total Variation Distance Estimation with Neural Networks for Merging Over-Clusterings

Large-scale 6D Object Pose Estimation Dataset for Industrial Bin-Picking

Pointwise Rotation-Invariant Network with Adaptive Sampling and 3D Spherical Voxel Convolution

The Perfect Match: 3D Point Cloud Matching with Smoothed Densities

Shape Reconstruction by Learning Differentiable Surface Representations

PointRNN: Point Recurrent Neural Network for Moving Point Cloud Processing

Tigris: Architecture and Algorithms for 3D Perception in Point Clouds

Multi-Resolution Multi-Modal Sensor Fusion For Remote Sensing Data With Label Uncertainty

GraphX-Convolution for Point Cloud Deformation in 2D-to-3D Conversion

Boosting Object Recognition in Point Clouds by Saliency Detection

A GMM based algorithm to generate point-cloud and its application to neuroimaging

Technical Report: Co-learning of geometry and semantics for online 3D mapping

3D tissue reconstruction with Kinect to evaluate neck lymphedema

PRNet: Self-Supervised Learning for Partial-to-Partial Registration

A Topological "Reading" Lesson: Classification of MNIST using TDA

Density-Aware Convolutional Networks with Context Encoding for Airborne LiDAR Point Cloud Classification

An Automatic Digital Terrain Generation Technique for Terrestrial Sensing and Virtual Reality Applications

AlignNet-3D: Fast Point Cloud Registration of Partially Observed Objects

Improving Map Re-localization with Deep 'Movable' Objects Segmentation on 3D LiDAR Point Clouds

Automated 3D recovery from very high resolution multi-view satellite images

IPC-Net: 3D point-cloud segmentation using deep inter-point convolutional layers

Rethinking Task and Metrics of Instance Segmentation on 3D Point Clouds

A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification

Hierarchical Point-Edge Interaction Network for Point Cloud Semantic Segmentation

Go Wider: An Efficient Neural Network for Point Cloud Analysis via Group Convolutions

Render4Completion: Synthesizing Multi-View Depth Maps for 3D Shape Completion

PointNLM: Point Nonlocal-Means for vegetation segmentation based on middle echo point clouds

SalsaNet: Fast Road and Vehicle Segmentation in LiDAR Point Clouds for Autonomous Driving

A machine vision meta-algorithm for automated recognition of underwater objects using sidescan sonar imagery

DeepICP: An End-to-End Deep Neural Network for 3D Point Cloud Registration

PointAtrousGraph: Deep Hierarchical Encoder-Decoder with Point Atrous Convolution for Unorganized 3D Points

Joint Learning of Graph Representation and Node Features in Graph Convolutional Neural Networks

Effective Rotation-invariant Point CNN with Spherical Harmonics kernels

DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing

Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds

Performance comparison of 3D correspondence grouping algorithm for 3D plant point clouds

Combining Deep Learning and Model-Based Methods for Robust Real-Time Semantic Landmark Detection

PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows

LU-Net: An Efficient Network for 3D LiDAR Point Cloud Semantic Segmentation Based on End-to-End-Learned 3D Features and U-Net

Point2SpatialCapsule: Aggregating Features and Spatial Relationships of Local Regions on Point Clouds using Spatial-aware Capsules

GarNet: A Two-Stream Network for Fast and Accurate 3D Cloth Draping

Probabilistic Reconstruction Networks for 3D Shape Inference from a Single Image

BoxNet: A Deep Learning Method for 2D Bounding Box Estimation from Bird's-Eye View Point Cloud

Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data

Directionally Constrained Fully Convolutional Neural Network For Airborne Lidar Point Cloud Classification

SeqLPD: Sequence Matching Enhanced Loop-Closure Detection Based on Large-Scale Point Cloud Description for Self-Driving Vehicles

LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis

Rotation Invariant Convolutions for 3D Point Clouds Deep Learning

ShellNet: Efficient Point Cloud Convolutional Neural Networks using Concentric Shells Statistics

6-DOF GraspNet: Variational Grasp Generation for Object Manipulation

SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences

PS^2-Net: A Locally and Globally Aware Network for Point-Based Semantic Segmentation

Justlookup: One Millisecond Deep Feature Extraction for Point Clouds By Lookup Tables

Interpolated Convolutional Networks for 3D Point Cloud Understanding

An overlapping-free leaf segmentation method for plant point clouds

Sim-to-Real Learning for Casualty Detection from Ground Projected Point Cloud Data

Grasp Type Estimation for Myoelectric Prostheses using Point Cloud Feature Learning

An Unsupervised, Iterative N-Dimensional Point-Set Registration Algorithm

Part Segmentation for Highly Accurate Deformable Tracking in Occlusions via Fully Convolutional Neural Networks

Enforcing geometric constraints of virtual normal for depth prediction

A Fast Free-viewpoint Video Synthesis Algorithm for Sports Scenes

Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds from Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction

Outlier-Robust Spatial Perception: Hardness, General-Purpose Algorithms, and Guarantees

Incremental Visual-Inertial 3D Mesh Generation with Structural Regularities

DUP-Net: Denoiser and Upsampler Network for 3D Adversarial Point Clouds Defense

EnforceNet: Monocular Camera Localization in Large Scale Indoor Sparse LiDAR Point Cloud

Mitigating the Hubness Problem for Zero-Shot Learning of 3D Objects

A Performance Evaluation of Correspondence Grouping Methods for 3D Rigid Data Matching

Analyzing the Cross-Sensor Portability of Neural Network Architectures for LiDAR-based Semantic Labeling

Evaluating Local Geometric Feature Representations for 3D Rigid Data Matching

A Convolutional Decoder for Point Clouds using Adaptive Instance Normalization

Supervized Segmentation with Graph-Structured Deep Metric Learning

LSANet: Feature Learning on Point Sets by Local Spatial Aware Layer

Weather Influence and Classification with Automotive Lidar Sensors

Direct Image to Point Cloud Descriptors Matching for 6-DOF Camera Localization in Dense 3D Point Cloud

HPLFlowNet: Hierarchical Permutohedral Lattice FlowNet for Scene Flow Estimation on Large-scale Point Clouds

Solving Large-Scale 0-1 Knapsack Problems and its Application to Point Cloud Resampling

Fast Hierarchical Neural Network for Feature Learning on Point Cloud

A survey of Object Classification and Detection based on 2D/3D data

Relation-Shape Convolutional Neural Network for Point Cloud Analysis

Robust Point Cloud Based Reconstruction of Large-Scale Outdoor Scenes

Learning Convolutional Transforms for Lossy Point Cloud Geometry Compression

SAWNet: A Spatially Aware Deep Neural Network for 3D Point Cloud Processing

Analysis of critical parameters of satellite stereo image for 3D reconstruction and mapping

LiDAR Sensor modeling and Data augmentation with GANs for Autonomous driving

Visibility Constrained Generative Model for Depth-based 3D Facial Pose Tracking

Oriented Point Sampling for Plane Detection in Unorganized Point Clouds

3D BAT: A Semi-Automatic, Web-based 3D Annotation Toolbox for Full-Surround, Multi-Modal Data Streams

Occupancy Networks: Learning 3D Reconstruction in Function Space

3D Point Cloud Denoising using Graph Laplacian Regularization of a Low Dimensional Manifold Model

LBS Autoencoder: Self-supervised Fitting of Articulated Meshes to Point Clouds

2D3D-MatchNet: Learning to Match Keypoints Across 2D Image and 3D Point Cloud

LATTE: Accelerating LiDAR Point Cloud Annotation via Sensor Fusion, One-Click Annotation, and Tracking

Deep AutoEncoder-based Lossy Geometry Compression for Point Clouds

Point cloud registration: matching a maximal common subset on pointclouds with noise (with 2D implementation)

SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences

A Skeleton-bridged Deep Learning Approach for Generating Meshes of Complex Topologies from Single RGB Images

Weighted Point Cloud Augmentation for Neural Network Training Data Class-Imbalance

DeepMapping: Unsupervised Map Estimation From Multiple Point Clouds

3D Point Cloud Denoising via Deep Neural Network based Local Surface Estimation

Robust Building-based Registration of Airborne LiDAR Data and Optical Imagery on Urban Scenes

Embodied Question Answering in Photorealistic Environments with Point Cloud Perception

Deep RBFNet: Point Cloud Feature Learning using Radial Basis Functions

Local Regularization of Noisy Point Clouds: Improved Global Geometric Estimates and Data Analysis

JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds with Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields

PointNetLK: Robust & Efficient Point Cloud Registration using PointNet

Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning

Performance Evalution of 3D Keypoint Detectors and Descriptors for Plants Health Classification

DeepCloud. The Application of a Data-driven, Generative Model in Design

MortonNet: Self-Supervised Learning of Local Features in 3D Point Clouds

USIP: Unsupervised Stable Interest Point Detection from 3D Point Clouds

PartNet: A Recursive Part Decomposition Network for Fine-grained and Hierarchical Shape Segmentation

DeepPoint3D: Learning Discriminative Local Descriptors using Deep Metric Learning on 3D Point Clouds

3D-LMNet: Latent Embedding Matching for Accurate and Diverse 3D Point Cloud Reconstruction from a Single Image

Quantitative Depth Quality Assessment of RGBD Cameras At Close Range Using 3D Printed Fixtures

Directional PointNet: 3D Environmental Classification for Wearable Robotics

Three-dimensional Segmentation of Trees Through a Flexible Multi-Class Graph Cut Algorithm (MCGC)

Shape2Motion: Joint Analysis of Motion Parts and Attributes from 3D Shapes

Fast Registration for cross-source point clouds by using weak regional affinity and pixel-wise refinement

Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Data

Associatively Segmenting Instances and Semantics in Point Clouds

PointIT: A Fast Tracking Framework Based on 3D Instance Segmentation

Sparse and noisy LiDAR completion with RGB guidance and uncertainty

Automatic Labeled LiDAR Data Generation based on Precise Human Model

MASC: Multi-scale Affinity with Sparse Convolution for 3D Instance Segmentation

Global Collaboration through Local Interaction in Competitive Learning

Challenges in Partially-Automated Roadway Feature Mapping Using Mobile Laser Scanning and Vehicle Trajectory Data

Dense 3D Point Cloud Reconstruction Using a Deep Pyramid Network

Fitting 3D Shapes from Partial and Noisy Point Clouds with Evolutionary Computing

Estimating the effective dimension of large biological datasets using Fisher separability analysis

DeepSpline: Data-Driven Reconstruction of Parametric Curves and Surfaces

Convolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation

PointFlowNet: Learning Representations for Rigid Motion Estimation from Point Clouds

Multi-scale Geometric Summaries for Similarity-based Sensor Fusion

Generic Primitive Detection in Point Clouds Using Novel Minimal Quadric Fits

Multi-view Point Cloud Registration with Adaptive Convergence Threshold and its Application on 3D Model Retrieval

Dual Principal Component Pursuit: Probability Analysis and Efficient Algorithms

Three Dimensional Reconstruction of Botanical Trees with Simulatable Geometry

Know What Your Neighbors Do: 3D Semantic Segmentation of Point Clouds

GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud

Point-to-Pose Voting based Hand Pose Estimation using Residual Permutation Equivariant Layer

3DContextNet: K-d Tree Guided Hierarchical Learning of Point Clouds Using Local and Global Contextual Cues

Nesti-Net: Normal Estimation for Unstructured 3D Point Clouds using Convolutional Neural Networks

Occlusion Resistant Object Rotation Regression from Point Cloud Segments

Structured Point Cloud Data Analysis via Regularized Tensor Regression for Process Modeling and Optimization

Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving

CAPNet: Continuous Approximation Projection For 3D Point Cloud Reconstruction Using 2D Supervision

Deep Functional Dictionaries: Learning Consistent Semantic Structures on 3D Models from Functions

Object Tracking by Reconstruction with View-Specific Discriminative Correlation Filters

PointSIFT: A SIFT-like Network Module for 3D Point Cloud Semantic Segmentation

MVPNet: Multi-View Point Regression Networks for 3D Object Reconstruction from A Single Image

Conceptualization of Object Compositions Using Persistent Homology

cilantro: A Lean, Versatile, and Efficient Library for Point Cloud Data Processing

Neural Generative Models for 3D Faces with Application in 3D Texture Free Face Recognition

3DCapsule: Extending the Capsule Architecture to Classify 3D Point Clouds

Fully automatic structure from motion with a spline-based environment representation

Benchmark data and method for real-time people counting in cluttered scenes using depth sensors

URSA: A Neural Network for Unordered Point Clouds Using Constellations

Primitive Fitting Using Deep Boundary Aware Geometric Segmentation

3D-PSRNet: Part Segmented 3D Point Cloud Reconstruction From a Single Image

High Fidelity Semantic Shape Completion for Point Clouds using Latent Optimization

Edge and Corner Detection for Unorganized 3D Point Clouds with Application to Robotic Welding

SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud

LIDAR-Camera Fusion for Road Detection Using Fully Convolutional Neural Networks

Multi-Kernel Diffusion CNNs for Graph-Based Learning on Point Clouds

Canonical and Compact Point Cloud Representation for Shape Classification

SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters

Reconstruction and Registration of Large-Scale Medical Scene Using Point Clouds Data from Different Modalities

Landslide Monitoring based on Terrestrial Laser Scanning: A Novel Semi-automatic Workflow

Sparse and Dense Data with CNNs: Depth Completion and Semantic Segmentation

Deconvolutional Networks for Point-Cloud Vehicle Detection and Tracking in Driving Scenarios

Machine Learning for Spatiotemporal Sequence Forecasting: A Survey

Performance Analysis and Robustification of Single-query 6-DoF Camera Pose Estimation

Iterative Global Similarity Points : A robust coarse-to-fine integration solution for pairwise 3D point cloud registration

EOE: Expected Overlap Estimation over Unstructured Point Cloud Data

Purely Geometric Scene Association and Retrieval - A Case for Macro Scale 3D Geometry

Semantic Classification of 3D Point Clouds with Multiscale Spherical Neighborhoods

Learning to See Forces: Surgical Force Prediction with RGB-Point Cloud Temporal Convolutional Networks

FARM: Functional Automatic Registration Method for 3D Human Bodies

Change Detection between Multimodal Remote Sensing Data Using Siamese CNN

AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation

Learning and Matching Multi-View Descriptors for Registration of Point Clouds

Towards Head Motion Compensation Using Multi-Scale Convolutional Neural Networks

Fast and Accurate Point Cloud Registration using Trees of Gaussian Mixtures

Combining SLAM with muti-spectral photometric stereo for real-time dense 3D reconstruction

Fast Cylinder and Plane Extraction from Depth Cameras for Visual Odometry

An Iterative Closest Points Approach to Neural Generative Models

Sparse 3D Point-cloud Map Upsampling and Noise Removal as a vSLAM Post-processing Step: Experimental Evaluation

Point cloud segmentation using hierarchical tree for architectural models

Robust And Scalable Learning Of Complex Dataset Topologies Via Elpigraph

Deep Multi-Structural Shape Analysis: Application to Neuroanatomy

Multi-View Semantic Labeling of 3D Point Clouds for Automated Plant Phenotyping

Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds

PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition

DeLS-3D: Deep Localization and Segmentation with a 3D Semantic Map

Boosting LiDAR-based Semantic Labeling by Cross-Modal Training Data Generation

Accurate 3-D Reconstruction with RGB-D Cameras using Depth Map Fusion and Pose Refinement

Spatiotemporal Learning of Dynamic Gestures from 3D Point Cloud Data

Constructing Locally Dense Point Clouds Using OpenSfM and ORB-SLAM2

LiDAR and Camera Calibration using Motion Estimated by Sensor Fusion Odometry

Paris-Lille-3D: a large and high-quality ground truth urban point cloud dataset for automatic segmentation and classification

Classification of Point Cloud Scenes with Multiscale Voxel Deep Network

Noise-resistant Deep Learning for Object Classification in 3D Point Clouds Using a Point Pair Descriptor

Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling

Visual Object Categorization Based on Hierarchical Shape Motifs Learned From Noisy Point Cloud Decompositions

A LiDAR Point Cloud Generator: from a Virtual World to Autonomous Driving

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

Prioritized Multi-View Stereo Depth Map Generation Using Confidence Prediction

A Minimalist Approach to Type-Agnostic Detection of Quadrics in Point Clouds

PPFNet: Global Context Aware Local Features for Robust 3D Point Matching

Deep learning for conifer/deciduous classification of airborne LiDAR 3D point clouds representing individual trees

Stable Distribution Alignment Using the Dual of the Adversarial Distance

Recovery of Point Clouds on Surfaces: Application to Image Reconstruction

Image2Mesh: A Learning Framework for Single Image 3D Reconstruction

3D Semantic Segmentation with Submanifold Sparse Convolutional Networks

Guaranteed Outlier Removal for Point Cloud Registration with Correspondences

Persistent homology machine learning for fingerprint classification

3D Point Cloud Classification and Segmentation using 3D Modified Fisher Vector Representation for Convolutional Neural Networks

End-to-end 3D shape inverse rendering of different classes of objects from a single input image

An optimal hierarchical clustering approach to segmentation of mobile LiDAR point clouds

Escape from Cells: Deep Kd-Networks for the Recognition of 3D Point Cloud Models

SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud

Combining LiDAR Space Clustering and Convolutional Neural Networks for Pedestrian Detection

Traffic Sign Timely Visual Recognizability Evaluation Based on 3D Measurable Point Clouds

A Fully Convolutional Network for Semantic Labeling of 3D Point Clouds

3D Shape Reconstruction from Sketches via Multi-view Convolutional Networks

Joint Calibration of Panoramic Camera and Lidar Based on Supervised Learning

Rotational Subgroup Voting and Pose Clustering for Robust 3D Object Recognition

Complete End-To-End Low Cost Solution To a 3D Scanning System with Integrated Turntable

Learning a 3D descriptor for cross-source point cloud registration from synthetic data

Robust Registration and Geometry Estimation from Unstructured Facial Scans

DeformNet: Free-Form Deformation Network for 3D Shape Reconstruction from a Single Image

Three-dimensional planar model estimation using multi-constraint knowledge based on k-means and RANSAC

Forest understory trees can be segmented accurately within sufficiently dense airborne laser scanning point clouds

Robust Rigid Point Registration based on Convolution of Adaptive Gaussian Mixture Models

Associating Grasp Configurations with Hierarchical Features in Convolutional Neural Networks

Vertical stratification of forest canopy for segmentation of under-story trees within small-footprint airborne LiDAR point clouds

A Fast Method For Computing Principal Curvatures From Range Images

Discriminative Optimization: Theory and Applications to Computer Vision Problems

The Surfacing of Multiview 3D Drawings via Lofting and Occlusion Reasoning

An Expectation-Maximization Algorithm for the Fractal Inverse Problem

A region-growing approach for automatic outcrop fracture extraction from a three-dimensional point cloud

Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

An Effective Approach for Point Clouds Registration Based on the Hard and Soft Assignments

Scalable Surface Reconstruction from Point Clouds with Extreme Scale and Density Diversity

Detecting Drivable Area for Self-driving Cars: An Unsupervised Approach

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Massive Data Clustering in Moderate Dimensions from the Dual Spaces of Observation and Attribute Data Clouds

LIDAR-based Driving Path Generation Using Fully Convolutional Neural Networks

Fast LIDAR-based Road Detection Using Fully Convolutional Neural Networks

Extrinsic Calibration of 3D Range Finder and Camera without Auxiliary Object or Human Intervention

Augmented Reality for Depth Cues in Monocular Minimally Invasive Surgery

PetroSurf3D - A Dataset for high-resolution 3D Surface Segmentation

3D Reconstruction of Temples in the Special Region of Yogyakarta By Using Close-Range Photogrammetry

A graph cut approach to 3D tree delineation, using integrated airborne LiDAR and hyperspectral imagery

Guaranteed Parameter Estimation for Discrete Energy Minimization

A Learning-based Variable Size Part Extraction Architecture for 6D Object Pose Recovery in Depth

Iterative Hough Forest with Histogram of Control Points for 6 DoF Object Registration from Depth Images

A robust approach for tree segmentation in deciduous forests using small-footprint airborne LiDAR data

Efficient Global Point Cloud Alignment using Bayesian Nonparametric Mixtures

A coarse-to-fine algorithm for registration in 3D street-view cross-source point clouds

Reliable Attribute-Based Object Recognition Using High Predictive Value Classifiers

Efficient Volumetric Fusion of Airborne and Street-Side Data for Urban Reconstruction

A Systematic Approach for Cross-source Point Cloud Registration by Preserving Macro and Micro Structures

Multi-view 3D Models from Single Images with a Convolutional Network

Video Registration in Egocentric Vision under Day and Night Illumination Changes

3-D Hand Pose Estimation from Kinect's Point Cloud Using Appearance Matching

LiDAR Ground Filtering Algorithm for Urban Areas Using Scan Line Based Segmentation

Geometric-Algebra LMS Adaptive Filter and its Application to Rotation Estimation

Efficient moving point handling for incremental 3D manifold reconstruction

Robust Performance-driven 3D Face Tracking in Long Range Depth Scenes

Computer-assisted polyp matching between optical colonoscopy and CT colonography: a phantom study

Global registration of multiple point clouds using semidefinite programming

Find my mug: Efficient object search with a mobile robot using semantic segmentation

Convex Relaxations of SE(2) and SE(3) for Visual Pose Estimation

A Low-Dimensional Representation for Robust Partial Isometric Correspondences Computation

A Synergistic Approach for Recovering Occlusion-Free Textured 3D Maps of Urban Facades from Heterogeneous Cartographic Data

Difference of Normals as a Multi-Scale Operator in Unorganized Point Clouds

A Self-Supervised Terrain Roughness Estimator for Off-Road Autonomous Driving

Probabilistic Recovery of Multiple Subspaces in Point Clouds by Geometric lp Minimization

Real-time Image-based 6-DOF Localization in Large-Scale Environments

3D Terrestrial lidar data classification of complex natural scenes using a multi-scale dimensionality criterion: applications in geomorphology

KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D

DAReN: A Collaborative Approach Towards Reasoning And Disentangling

Model reduction for the material point method via learning the deformation map and its spatial-temporal gradients

Impact of GPU uncertainty on the training of predictive deep neural networks

Decentralized Learning of Tree-Structured Gaussian Graphical Models from Noisy Data

ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators

Effective Fusion of Deep Multitasking Representations for Robust Visual Tracking

Accurate, Interpretable, and Fast Animation: An Iterative, Sparse, and Nonconvex Approach

Evaluating Continual Learning Algorithms by Generating 3D Virtual Environments

Infinite Nature: Perpetual View Generation of Natural Scenes from a Single Image

Relaxed Marginal Consistency for Differentially Private Query Answering

Border-SegGCN: Improving Semantic Segmentation by Refining the Border Outline using Graph Convolutional Network

HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields

LSD-StructureNet: Modeling Levels of Structural Detail in 3D Part Hierarchies

Estimating the probabilities of causation via deep monotonic twin networks

SLIDE: Single Image 3D Photography with Soft Layering and Depth-aware Inpainting

Scene Synthesis via Uncertainty-Driven Attribute Synchronization

Automatic digital twin data model generation of building energy systems from piping and instrumentation diagrams

Convolutional versus Dense Neural Networks: Comparing the Two Neural Networks Performance in Predicting Building Operational Energy Use Based on the Building Shape

Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-based Approach

Unsupervised Dense Deformation Embedding Network for Template-Free Shape Correspondence

The Word is Mightier than the Label: Learning without Pointillistic Labels using Data Programming

Benchpress: a scalable and platform-independent workflow for benchmarking structure learning algorithms for graphical models

Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Video

Recurrent Video Deblurring with Blur-Invariant Motion Estimation and Pixel Volumes

Detecting and Segmenting Adversarial Graphics Patterns from Images

Spatiotemporal Texture Reconstruction for Dynamic Objects Using a Single RGB-D Camera

Augmenting Implicit Neural Shape Representations with Explicit Deformation Fields

NTU-X: An Enhanced Large-scale Dataset for Improving Pose-based Recognition of Subtle Human Actions

Worldsheet: Wrapping the World in a 3D Sheet for View Synthesis from a Single Image

Learning Generative Models of Textured 3D Meshes from Real-World Images

Spatially Conditioned Graphs for Detecting Human-Object Interactions

Incorporating Causal Graphical Prior Knowledge into Predictive Modeling via Simple Data Augmentation

Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields

iButter: Neural Interactive Bullet Time Generator for Human Free-viewpoint Rendering

MotionInput v2.0 supporting DirectX: A modular library of open-source gesture-based machine learning and computer vision methods for interacting and controlling existing software with a webcam

Semi-supervised classification of radiology images with NoTeacher: A Teacher that is not Mean

A Weak Supervision Approach to Detecting Visual Anomalies for Automated Testing of Graphics Units

A Generalized Framework for Edge-preserving and Structure-preserving Image Smoothing

Neural Free-Viewpoint Performance Rendering under Complex Human-object Interactions

BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models

Structured Context Enhancement Network for Mouse Pose Estimation

Topological Information Retrieval with Dilation-Invariant Bottleneck Comparative Measures

Adding Visibility to Visibility Graphs: Weighting Visibility Analysis with Attenuation Coefficients

Perceptually Validated Precise Local Editing for Facial Action Units with StyleGAN

Probing neural networks with t-SNE, class-specific projections and a guided tour

Active Learning in Incomplete Label Multiple Instance Multiple Label Learning

NeLF: Neural Light-transport Field for Portrait View Synthesis and Relighting

Linear Polytree Structural Equation Models: Structural Learning and Inverse Correlation Estimation

Efficient Neural Causal Discovery without Acyclicity Constraints

Discovering Latent Causal Variables via Mechanism Sparsity: A New Principle for Nonlinear ICA

Investigating the performance of multi-objective optimization when learning Bayesian Networks

Deep Learning based Food Instance Segmentation using Synthetic Data

'CADSketchNet' -- An Annotated Sketch dataset for 3D CAD Model Retrieval with Deep Neural Networks

Making transport more robust and interpretable by moving data through a small number of anchor points

Potential UAV Landing Sites Detection through Digital Elevation Models Analysis

Few-shot Neural Human Performance Rendering from Sparse RGBD Videos

Robust Pose Transfer with Dynamic Details using Neural Video Rendering

A Convolutional Neural Network Approach to the Classification of Engineering Models

A Projector-Camera System Using Hybrid Pixels with Projection and Capturing Capabilities

Non-linear Visual Knowledge Discovery with Elliptic Paired Coordinates

Adiabatic Quantum Graph Matching with Permutation Matrix Constraints

GPNAS: A Neural Network Architecture Search Framework Based on Graphical Predictor

Partial 3D Object Retrieval using Local Binary QUICCI Descriptors and Dissimilarity Tree Indexing

Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization

A convolutional neural network for teeth margin detection on 3-dimensional dental meshes

Generalization Error Analysis of Neural networks with Gradient Based Regularization

Deep Mesh Prior: Unsupervised Mesh Restoration using Graph Convolutional Networks

Reconsidering Dependency Networks from an Information Geometry Perspective

Learning Mesh Representations via Binary Space Partitioning Tree Networks

Famous Companies Use More Letters in Logo:A Large-Scale Analysis of Text Area in Logo

Dense Graph Convolutional Neural Networks on 3D Meshes for 3D Object Segmentation and Classification

Parameter Priors for Directed Acyclic Graphical Models and the Characterization of Several Probability Distributions

Diversifying Semantic Image Synthesis and Editing via Class- and Layer-wise VAEs

Syntactically Guided Generative Embeddings for Zero-Shot Skeleton Action Recognition

Fast Training of Neural Lumigraph Representations using Meta Learning

Hyperspectral Remote Sensing Image Classification Based on Multi-scale Cross Graphic Convolution

DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks

Sparse Needlets for Lighting Estimation with Spherical Transport Loss

Image-to-Image Translation of Synthetic Samples for Rare Classes

RGB2Hands: Real-Time Tracking of 3D Hand Interactions from Monocular RGB Video

Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge

Normalized Avatar Synthesis Using StyleGAN and Perceptual Refinement

SHREC 2021: Track on Skeleton-based Hand Gesture Recognition in the Wild

NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction

Learning and Meshing from Deep Implicit Surface Networks Using an Efficient Implementation of Analytic Marching

Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields

Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical Models

Silhouettes and quasi residual plots for neural nets and tree-based classifiers

Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models

Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages

Online Optimization in Games via Control Theory: Connecting Regret, Passivity and Poincaré Recurrence

Real-time Pose and Shape Reconstruction of Two Interacting Hands With a Single Depth Camera

ReS2tAC -- UAV-Borne Real-Time SGM Stereo Optimized for Embedded ARM and CUDA Devices

Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics

HUMAP: Hierarchical Uniform Manifold Approximation and Projection

GANs N' Roses: Stable, Controllable, Diverse Image to Image Translation (works for videos too!)

Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks

Multimodal Semantic Scene Graphs for Holistic Modeling of Surgical Procedures

Automatic 2D-3D Registration without Contrast Agent during Neurovascular Interventions

Artificial Intelligence in Minimally Invasive Interventional Treatment

An End-to-End Breast Tumour Classification Model Using Context-Based Patch Modelling- A BiLSTM Approach for Image Classification

Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering

A Procedural World Generation Framework for Systematic Evaluation of Continual Learning

Neural Actor: Neural Free-view Synthesis of Human Actors with Pose Control

NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illumination

Barbershop: GAN-based Image Compositing using Segmentation Masks

Learning an Animatable Detailed 3D Face Model from In-The-Wild Images

FastRIFE: Optimization of Real-Time Intermediate Flow Estimation for Video Frame Interpolation

Neural Splines: Fitting 3D Surfaces with Infinitely-Wide Neural Networks

Multi-view 3D Reconstruction of a Texture-less Smooth Surface of Unknown Generic Reflectance

PBNS: Physically Based Neural Simulator for Unsupervised Garment Pose Space Deformation

Document Domain Randomization for Deep Learning Document Layout Extraction

Learning high-dimensional probability distributions using tree tensor networks

Addendum on the scoring of Gaussian directed acyclic graphical models

Fusion 360 Gallery: A Dataset and Environment for Programmatic CAD Construction from Human Design Sequences

FloorPlanCAD: A Large-Scale CAD Drawing Dataset for Panoptic Symbol Spotting

Predicting Surface Reflectance Properties of Outdoor Scenes Under Unknown Natural Illumination

A Fast Deep Learning Network for Automatic Image Auto-Straightening

ROSEFusion: Random Optimization for Online Dense Reconstruction under Fast Camera Motion

Deep Graphics Encoder for Real-Time Video Makeup Synthesis from Example

On the reproducibility of fully convolutional neural networks for modeling time-space evolving physical systems

Contour Integration using Graph-Cut and Non-Classical Receptive Field

Current Status and Performance Analysis of Table Recognition in Document Images with Deep Neural Networks

Inverting Generative Adversarial Renderer for Face Reconstruction

Use of High Dimensional Modeling for automatic variables selection: the best path algorithm

TrackMPNN: A Message Passing Graph Neural Architecture for Multi-Object Tracking

Function4D: Real-time Human Volumetric Capture from Very Sparse Consumer RGBD Sensors

DiffAqua: A Differentiable Computational Design Pipeline for Soft Underwater Swimmers with Shape Interpolation

A Neural Lip-Sync Framework for Synthesizing Photorealistic Virtual News Anchors

Neural Monocular 3D Human Motion Capture with Physical Awareness

EQ-Net: A Unified Deep Learning Framework for Log-Likelihood Ratio Estimation and Quantization

Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables

Efficient semidefinite-programming-based inference for binary and multi-class MRFs

Editable Free-viewpoint Video Using a Layered Neural Representation

Learning monocular 3D reconstruction of articulated categories from motion

Node Embedding using Mutual Information and Self-Supervision based Bi-level Aggregation

PMCE: efficient inference of expressive models of cancer evolution with high prognostic power

Cross-Domain and Disentangled Face Manipulation with 3D Guidance

KeypointDeformer: Unsupervised 3D Keypoint Discovery for Shape Control

On Buggy Resizing Libraries and Surprising Subtleties in FID Calculation

Improvement of Normal Estimation for PointClouds via Simplifying Surface Fitting

Learning on Hardware: A Tutorial on Neural Network Accelerators and Co-Processors

When deep learning models on GPU can be accelerated by taking advantage of unstructured sparsity

Fast Private Parameter Learning and Evaluation for Sum-Product Networks

Thresholded Graphical Lasso Adjusts for Latent Variables: Application to Functional Neural Connectivity

Kernel Operations on the GPU, with Autodiff, without Memory Overflows

Reconstructing Recognizable 3D Face Shapes based on 3D Morphable Models

Which Neural Network to Choose for Post-Fault Localization, Dynamic State Estimation and Optimal Measurement Placement in Power Systems?

DeePSD: Automatic Deep Skinning And Pose Space Deformation For 3D Garment Animation

NullaNet Tiny: Ultra-low-latency DNN Inference Through Fixed-function Combinational Logic

Deep Implicit Moving Least-Squares Functions for 3D Reconstruction

Generating Furry Cars: Disentangling Object Shape & Appearance across Multiple Domains

Learning Mobile CNN Feature Extraction Toward Fast Computation of Visual Object Tracking

A Quotient Space Formulation for Generative Statistical Analysis of Graphical Data

PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting

Neural Video Portrait Relighting in Real-time via Consistency Modeling

Batteries, camera, action! Learning a semantic control space for expressive robot cinematography

PX-NET: Simple and Efficient Pixel-Wise Training of Photometric Stereo Networks

Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes

Head2HeadFS: Video-based Head Reenactment with Few-shot Learning

Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery

Two-Stage Monte Carlo Denoising with Adaptive Sampling and Kernel Pool

Intrinsic Autoencoders for Joint Neural Rendering and Intrinsic Image Decomposition

DeepMetaHandles: Learning Deformation Meta-Handles of 3D Meshes with Biharmonic Coordinates

VisEvol: Visual Analytics to Support Hyperparameter Search through Evolutionary Optimization

CGPart: A Part Segmentation Dataset Based on 3D Computer Graphics Models

ScanGAN360: A Generative Model of Realistic Scanpaths for 360$^{\circ}$ Images

Generative Grading: Near Human-level Accuracy for Automated Feedback on Richly Structured Problems

Consistency-Aware Graph Network for Human Interaction Understanding

Self-Guided Belief Propagation -- A Homotopy Continuation Method

Deep Tiling: Texture Tile Synthesis Using a Deep Learning Approach

Knowledge- and Data-driven Services for Energy Systems using Graph Neural Networks

In the light of feature distributions: moment matching for Neural Style Transfer

Diverse Semantic Image Synthesis via Probability Distribution Modeling

Hyperbolic Graph Embedding with Enhanced Semi-Implicit Variational Inference

Landmark Detection and 3D Face Reconstruction for Caricature using a Nonlinear Parametric Model

Improved Image Matting via Real-time User Clicks and Uncertainty Estimation

Deep Shape-from-Template: Wide-Baseline, Dense and Fast Registration and Deformable Reconstruction from a Single Image

Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables

A Local Method for Identifying Causal Relations under Markov Equivalence

A System for 3D Reconstruction Of Comminuted Tibial Plafond Bone Fractures

GMLight: Lighting Estimation via Geometric Distribution Approximation

High-order Differentiable Autoencoder for Nonlinear Model Reduction

Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm

StatEcoNet: Statistical Ecology Neural Networks for Species Distribution Modeling

Estimate Three-Phase Distribution Line Parameters With Physics-Informed Graphical Learning Method

Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models

Adversarial Linear Contextual Bandits with Graph-Structured Side Observations

Learning from Synthetic Shadows for Shadow Detection and Removal

Do-calculus enables causal reasoning with latent variable models

A-NeRF: Surface-free Human 3D Pose Refinement via Neural Rendering

Classification of Handwritten Names of Cities and Handwritten Text Recognition using Various Deep Learning Models

Subjective and Objective Visual Quality Assessment of Textured 3D Meshes

Scalable Inference of Sparsely-changing Markov Random Fields with Strong Statistical Guarantees

The joint role of geometry and illumination on material recognition

Graph Coding for Model Selection and Anomaly Detection in Gaussian Graphical Models

Monocular Human Pose and Shape Reconstruction using Part Differentiable Rendering

Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes

DeProCams: Simultaneous Relighting, Compensation and Shape Reconstruction for Projector-Camera Systems

SGA: A Robust Algorithm for Partial Recovery of Tree-Structured Graphical Models with Noisy Samples

Superiorities of Deep Extreme Learning Machines against Convolutional Neural Networks

Gaussian Mixture Graphical Lasso with Application to Edge Detection in Brain Networks

A Large Multi-Target Dataset of Common Bengali Handwritten Graphemes

Towards Energy Efficient Federated Learning over 5G+ Mobile Devices

VIS30K: A Collection of Figures and Tables from IEEE Visualization Conference Publications

On the Role of Sparsity and DAG Constraints for Learning Linear DAGs

Learning non-Gaussian graphical models via Hessian scores and triangular transport

SketchZooms: Deep multi-view descriptors for matching line drawings

Graph-based non-linear least squares optimization for visual place recognition in changing environments

Faster and Accurate Compressed Video Action Recognition Straight from the Frequency Domain

Interpolating Points on a Non-Uniform Grid using a Mixture of Gaussians

Vid2Actor: Free-viewpoint Animatable Person Synthesis from Video in the Wild

Deep Dose Plugin Towards Real-time Monte Carlo Dose Calculation Through a Deep Learning based Denoising Algorithm

STaR: Self-supervised Tracking and Reconstruction of Rigid Objects in Motion with Neural Rendering

EMLight: Lighting Estimation via Spherical Distribution Approximation

FuDGE: Functional Differential Graph Estimation with fully and discretely observed curves

No Shadow Left Behind: Removing Objects and their Shadows using Approximate Lighting and Geometry

Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs

CT Film Recovery via Disentangling Geometric Deformation and Illumination Variation: Simulated Datasets and Deep Models

A Fast Algorithm for Heart Disease Prediction using Bayesian Network Model

End-to-end Generative Floor-plan and Layout with Attributes and Relation Graph

Normalized Label Distribution: Towards Learning Calibrated, Adaptable and Efficient Activation Maps

The Inverse G-Wishart Distribution and Variational Message Passing

Deep traffic light detection by overlaying synthetic context on arbitrary natural images

Topology-Adaptive Mesh Deformation for Surface Evolution, Morphing, and Multi-View Reconstruction

Unsupervised Geometric Disentanglement for Surfaces via CFAN-VAE

PhysCap: Physically Plausible Monocular 3D Motion Capture in Real Time

BSP-Net: Generating Compact Meshes via Binary Space Partitioning

NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis

MoGlow: Probabilistic and controllable motion synthesis using normalising flows

Shape From Tracing: Towards Reconstructing 3D Object Geometry and SVBRDF Material from Images via Differentiable Path Tracing

MyFood: A Food Segmentation and Classification System to Aid Nutritional Monitoring

A Survey on Deep Learning with Noisy Labels: How to train your model when you cannot trust on the annotations?

Neural Deformation Graphs for Globally-consistent Non-rigid Reconstruction

A Photogrammetry-based Framework to Facilitate Image-based Modeling and Automatic Camera Tracking

StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics

t-viSNE: Interactive Assessment and Interpretation of t-SNE Projections

DeepCloth: Neural Garment Representation for Shape and Style Editing

MonoClothCap: Towards Temporally Coherent Clothing Capture from Monocular RGB Video

A non-autonomous equation discovery method for time signal classification

End-to-End Differentiable 6DoF Object Pose Estimation with Local and Global Constraints

Iterative Text-based Editing of Talking-heads Using Neural Retargeting

Learning Gaussian Graphical Models with Ordered Weighted L1 Regularization

Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs

Towards human performance on automatic motion tracking of infant spontaneous movements

PoseNet3D: Learning Temporally Consistent 3D Human Pose via Knowledge Distillation

A polynomial-time algorithm for learning nonparametric causal graphs

COALESCE: Component Assembly by Learning to Synthesize Connections

Similarity-Based Clustering for Enhancing Image Classification Architectures

A Score-and-Search Approach to Learning Bayesian Networks with Noisy-OR Relations

Topology-Based Feature Design and Tracking for Multi-Center Cyclones

Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance

Accelerating Metropolis-Hastings with Lightweight Inference Compilation

Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models

Probabilistic Circuits for Variational Inference in Discrete Graphical Models

Multiple Pedestrians and Vehicles Tracking in Aerial Imagery: A Comprehensive Study

Learning Exponential Family Graphical Models with Latent Variables using Regularized Conditional Likelihood

Exploiting Context for Robustness to Label Noise in Active Learning

Addressing Variance Shrinkage in Variational Autoencoders using Quantile Regression

Learning Restricted Boltzmann Machines with Sparse Latent Variables

Coupling Explicit and Implicit Surface Representations for Generative 3D Modeling

Training Data Generating Networks: Linking 3D Shapes and Few-Shot Classification

QReLU and m-QReLU: Two novel quantum activation functions to aid medical diagnostics

Bayesian Spatio-Temporal Graph Convolutional Network for Traffic Forecasting

GPU-Accelerated Primal Learning for Extremely Fast Large-Scale Classification

Photovoltaic module segmentation and thermal analysis tool from thermal images

Learning Linear Non-Gaussian Graphical Models with Multidirected Edges

Tensor Fields for Data Extraction from Chart Images: Bar Charts and Scatter Plots

Learning Complete 3D Morphable Face Models from Images and Videos

Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective

X-Fields: Implicit Neural View-, Light- and Time-Image Interpolation

Spectral neighbor joining for reconstruction of latent tree models

DeepVir -- Graphical Deep Matrix Factorization for "In Silico" Antiviral Repositioning: Application to COVID-19

StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows

Deep intrinsic decomposition trained on surreal scenes yet with realistic light effects

Fully Convolutional Graph Neural Networks for Parametric Virtual Try-On

Concise and Effective Network for 3D Human Modeling from Orthogonal Silhouettes

CNNPruner: Pruning Convolutional Neural Networks with Visual Analytics

Interactive Visual Study of Multiple Attributes Learning Model of X-Ray Scattering Images

LIMP: Learning Latent Shape Representations with Metric Preservation Priors

Strudel: Learning Structured-Decomposable Probabilistic Circuits

Visualization of Tradeoff in Evaluation: from Precision-Recall & PN to LIFT, ROC & BIRD

Relationship-aware Multivariate Sampling Strategy for Scientific Simulation Data

SymmetryNet: Learning to Predict Reflectional and Rotational Symmetries of 3D Shapes from Single-View RGB-D Images

Multi-task deep CNN model for no-reference image quality assessment on smartphone camera photos

Vehicle Trajectory Prediction in Crowded Highway Scenarios Using Bird Eye View Representations and CNNs

The Hessian Penalty: A Weak Prior for Unsupervised Disentanglement

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

Fast Bi-layer Neural Synthesis of One-Shot Realistic Head Avatars

Counterfactual Evaluation of Slate Recommendations with Sequential Reward Interactions

DronePose: Photorealistic UAV-Assistant Dataset Synthesis for 3D Pose Estimation via a Smooth Silhouette Loss

Object Properties Inferring from and Transfer for Human Interaction Motions

UnrealText: Synthesizing Realistic Scene Text Images from the Unreal World

Fiedler Regularization: Learning Neural Networks with Graph Sparsity

RocNet: Recursive Octree Network for Efficient 3D Deep Representation

Causal Structure Discovery from Distributions Arising from Mixtures of DAGs

SimPatch: A Nearest Neighbor Similarity Match between Image Patches

KeypointNet: A Large-scale 3D Keypoint Dataset Aggregated from Numerous Human Annotations

An Indexing Scheme and Descriptor for 3D Object Retrieval Based on Local Shape Querying

Unravelling the Architecture of Membrane Proteins with Conditional Random Fields

LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction

LANCE: Efficient Low-Precision Quantized Winograd Convolution for Neural Networks Based on Graphics Processing Units

se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains

Fragments-Expert: A Graphical User Interface MATLAB Toolbox for Classification of File Fragments

Simulating Content Consistent Vehicle Datasets with Attribute Descent

Inverting the Feature Visualization Process for Feedforward Neural Networks

Deep Reflectance Volumes: Relightable Reconstructions from Multi-View Photometric Images

JNR: Joint-based Neural Rig Representation for Compact 3D Face Modeling

Latent Instrumental Variables as Priors in Causal Inference based on Independence of Cause and Mechanism

Neural Design Network: Graphic Layout Generation with Constraints

Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision

Weakly Supervised Person Re-ID: Differentiable Graphical Learning and A New Benchmark

Transposer: Universal Texture Synthesis Using Feature Maps as Transposed Convolution Filter

algcomparison: Comparing the Performance of Graphical Structure Learning Algorithms with TETRAD

Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models

The Phong Surface: Efficient 3D Model Fitting using Lifted Optimization

Single Storage Semi-Global Matching for Real Time Depth Processing

Radial Intersection Count Image: a Clutter Resistant 3D Shape Descriptor

TilinGNN: Learning to Tile with Self-Supervised Graph Neural Network

Deep 3D Capture: Geometry and Reflectance from Sparse Multi-View Images

Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs

The Many-to-Many Mapping Between the Concordance Correlation Coefficient and the Mean Square Error

Predictive and Generative Neural Networks for Object Functionality

AerialMPTNet: Multi-Pedestrian Tracking in Aerial Imagery Using Temporal and Graphical Features

High Resolution Zero-Shot Domain Adaptation of Synthetically Rendered Face Images

Does the $\ell_1$-norm Learn a Sparse Graph under Laplacian Constrained Graphical Models?

The huge Package for High-dimensional Undirected Graph Estimation in R

A Baseline Approach for AutoImplant: the MICCAI 2020 Cranial Implant Design Challenge

Differential Privacy for Multi-armed Bandits: What Is It and What Is Its Cost?

A Complete Characterization of Projectivity for Statistical Relational Models

MotioNet: 3D Human Motion Reconstruction from Monocular Video with Skeleton Consistency

Perspective Texture Synthesis Based on Improved Energy Optimization

Efficient Statistics for Sparse Graphical Models from Truncated Samples

Probabilistic Optimal Transport based on Collective Graphical Models

A study of the effect of the illumination model on the generation of synthetic training datasets

Alternating ConvLSTM: Learning Force Propagation with Alternate State Updates

LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose Estimation

DIST: Rendering Deep Implicit Signed Distance Function with Differentiable Sphere Tracing

Deep Octree-based CNNs with Output-Guided Skip Connections for 3D Shape and Scene Completion

OPAL-Net: A Generative Model for Part-based Object Layout Generation

4D Visualization of Dynamic Events from Unconstrained Multi-View Videos

Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting

A Relation-Augmented Fully Convolutional Network for Semantic Segmentation in Aerial Scenes

Deep Lighting Environment Map Estimation from Spherical Panoramas

Representations, Metrics and Statistics For Shape Analysis of Elastic Graphs

Lighthouse: Predicting Lighting Volumes for Spatially-Coherent Illumination

Exact Asymptotics for Learning Tree-Structured Graphical Models with Side Information: Noiseless and Noisy Samples

The scalable Birth-Death MCMC Algorithm for Mixed Graphical Model Learning with Application to Genomic Data Integration

Fast Automatic Visibility Optimization for Thermal Synthetic Aperture Visualization

Training and Classification using a Restricted Boltzmann Machine on the D-Wave 2000Q

Design and Development of a Web-based Tool for Inpainting of Dissected Aortae in Angiography Images

XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera

FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation

Joint Inference of States, Robot Knowledge, and Human (False-)Beliefs

Learning to Generate Synthetic 3D Training Data through Hybrid Gradient

High-dimensional Gaussian graphical model for network-linked data

Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video

Deep Slow Motion Video Reconstruction with Hybrid Imaging System

Causal network learning with non-invertible functional relationships

MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models

Taxonomy of Dual Block-Coordinate Ascent Methods for Discrete Energy Minimization

Exact MAP-Inference by Confining Combinatorial Search with LP Relaxation

Compressed Sensing Plus Motion (CS+M): A New Perspective for Improving Undersampled MR Image Reconstruction

DPVis: Visual Analytics with Hidden Markov Models for Disease Progression Pathways

Multimodal Image Synthesis with Conditional Implicit Maximum Likelihood Estimation

Traversing the noise of dynamic mini-batch sub-sampled loss functions: A visual guide

Monocular Real-time Hand Shape and Motion Capture using Multi-modal Data

Synchronizing Probability Measures on Rotations via Optimal Transport

PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization

SoftSMPL: Data-driven Modeling of Nonlinear Soft-tissue Dynamics for Parametric Humans

MaskGAN: Towards Diverse and Interactive Facial Image Manipulation

A theory of independent mechanisms for extrapolation in generative models

Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables

DeepDeform: Learning Non-rigid RGB-D Reconstruction with Semi-supervised Data

Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Images

Predictively Encoded Graph Convolutional Network for Noise-Robust Skeleton-based Action Recognition

Complexity of Shapes Embedded in ${\mathbb Z^n}$ with a Bias Towards Squares

TailorNet: Predicting Clothing in 3D as a Function of Human Pose, Shape and Garment Style

Towards Photo-Realistic Virtual Try-On by Adaptively Generating$\leftrightarrow$Preserving Image Content

Gaussian Graphical Model exploration and selection in high dimension low sample size setting

Cross-modal Multi-task Learning for Graphic Recognition of Caricature Face

Learning Some Popular Gaussian Graphical Models without Condition Number Bounds

Audio-driven Talking Face Video Generation with Learning-based Personalized Head Pose

Convergence Rates of Smooth Message Passing with Rounding in Entropy-Regularized MAP Inference

Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data

MINA: Convex Mixed-Integer Programming for Non-Rigid Shape Alignment

A Multi-Channel Neural Graphical Event Model with Negative Evidence

Analytic Marching: An Analytic Meshing Solution from Deep Implicit Surface Networks

Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks

Rotation-invariant Mixed Graphical Model Network for 2D Hand Pose Estimation

Front2Back: Single View 3D Shape Reconstruction via Front to Back Prediction

Do As I Do: Transferring Human Motion and Appearance between Monocular Videos with Spatial and Temporal Constraints

Approximation of Functions over Manifolds: A Moving Least-Squares Approach

Self-Supervised Learning of Generative Spin-Glasses with Normalizing Flows

Bayesian Tensor Network with Polynomial Complexity for Probabilistic Machine Learning

MW-GAN: Multi-Warping GAN for Caricature Generation with Multi-Style Geometric Exaggeration

Meta-modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia

On the Difference Between the Information Bottleneck and the Deep Information Bottleneck

Projection pursuit based on Gaussian mixtures and evolutionary algorithms

Inverse Rendering Techniques for Physically Grounded Image Editing

EFANet: Exchangeable Feature Alignment Network for Arbitrary Style Transfer

Modeling Human Decision-making in Generalized Gaussian Multi-armed Bandits

Frequency-Aware Reconstruction of Fluid Simulations with Generative Networks

A Heterogeneous Graphical Model to Understand User-Level Sentiments in Social Media

SDFDiff: Differentiable Rendering of Signed Distance Fields for 3D Shape Optimization

A Theory of Uncertainty Variables for State Estimation and Inference

PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization

Smooth Shells: Multi-Scale Shape Registration with Functional Maps

Factor Analysis on Citation, Using a Combined Latent and Logistic Regression Model

CG-GAN: An Interactive Evolutionary GAN-based Approach for Facial Composite Generation)

Learning General Latent-Variable Graphical Models with Predictive Belief Propagation

Recovering Facial Reflectance and Geometry from Multi-view Images

Order Matters at Fanatics Recommending Sequentially Ordered Products by LSTM Embedded with Word2Vec

Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees

Graph Element Networks: adaptive, structured computation and memory

Rejection-Cascade of Gaussians: Real-time adaptive background subtraction framework

Kaolin: A PyTorch Library for Accelerating 3D Deep Learning Research

Improving Spectral Clustering using the Asymptotic Value of the Normalised Cut

Image-based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Era

Combining Generative and Discriminative Models for Hybrid Inference

Variational Bayesian Inference for Audio-Visual Tracking of Multiple Speakers

Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control

Relation Modeling with Graph Convolutional Networks for Facial Action Unit Detection

Effects of Illumination on the Categorization of Shiny Materials

Sketch2Code: Transformation of Sketches to UI in Real-time Using Deep Neural Network

FeatureLego: Volume Exploration Using Exhaustive Clustering of Super-Voxels

Illumination-Based Data Augmentation for Robust Background Subtraction

A Universal Hierarchy of Shift-Stable Distributions and the Tradeoff Between Stability and Performance

Universal Marginaliser for Deep Amortised Inference for Probabilistic Programs

Identifiability of Generalized Hypergeometric Distribution (GHD) Directed Acyclic Graphical Models

C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion

Supporting Analysis of Dimensionality Reduction Results with Contrastive Learning

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing

Refining 6D Object Pose Predictions using Abstract Render-and-Compare

Distributionally Robust Formulation and Model Selection for the Graphical Lasso

Face Reflectance and Geometry Modeling via Differentiable Ray Tracing

Context-Aware Image Matting for Simultaneous Foreground and Alpha Estimation

Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures

Few-Shot Adversarial Learning of Realistic Neural Talking Head Models

Interpreting Distortions in Dimensionality Reduction by Superimposing Neighbourhood Graphs

Graph Representations for Higher-Order Logic and Theorem Proving

Skeleton Image Representation for 3D Action Recognition based on Tree Structure and Reference Joints

Scalable Probabilistic Matrix Factorization with Graph-Based Priors

Computer-Aided Automated Detection of Gene-Controlled Social Actions of Drosophila

Curve Fitting from Probabilistic Emissions and Applications to Dynamic Item Response Theory

Deep Iterative Frame Interpolation for Full-frame Video Stabilization

A Neural-Symbolic Architecture for Inverse Graphics Improved by Lifelong Meta-Learning

ExpandNet: A Deep Convolutional Neural Network for High Dynamic Range Expansion from Low Dynamic Range Content

Estimation of Absolute Scale in Monocular SLAM Using Synthetic Data

EventCap: Monocular 3D Capture of High-Speed Human Motions using an Event Camera

Diverse Image Synthesis from Semantic Layouts via Conditional IMLE

Predicting Animation Skeletons for 3D Articulated Models via Volumetric Nets

Pro-Cam SSfM: Projector-Camera System for Structure and Spectral Reflectance from Motion

Uncertainty Modeling of Contextual-Connections between Tracklets for Unconstrained Video-based Face Recognition

CUDA optimized Neural Network predicts blood glucose control from quantified joint mobility and anthropometrics

Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables

Supervised Negative Binomial Classifier for Probabilistic Record Linkage

Chainer: A Deep Learning Framework for Accelerating the Research Cycle

Simultaneous Iris and Periocular Region Detection Using Coarse Annotations

Auto-labelling of Markers in Optical Motion Capture by Permutation Learning

RNNbow: Visualizing Learning via Backpropagation Gradients in Recurrent Neural Networks

Regularizing Proxies with Multi-Adversarial Training for Unsupervised Domain-Adaptive Semantic Segmentation

A graphical heuristic for reduction and partitioning of large datasets for scalable supervised training

Block based Singular Value Decomposition approach to matrix factorization for recommender systems

Variational Shape Completion for Virtual Planning of Jaw Reconstructive Surgery

Tiny-Inception-ResNet-v2: Using Deep Learning for Eliminating Bonded Labors of Brick Kilns in South Asia

Quantifying Confounding Bias in Neuroimaging Datasets with Causal Inference

Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization

Fast Universal Style Transfer for Artistic and Photorealistic Rendering

Collaborative Large-Scale Dense 3D Reconstruction with Online Inter-Agent Pose Optimisation

Evading classifiers in discrete domains with provable optimality guarantees

Learning to Approximate Directional Fields Defined over 2D Planes

Temporally Coherent Full 3D Mesh Human Pose Recovery from Monocular Video

Graphical Lasso and Thresholding: Equivalence and Closed-form Solutions

Joint Nonparametric Precision Matrix Estimation with Confounding

Inference in Probabilistic Graphical Models by Graph Neural Networks

On the Sample Complexity of Graphical Model Selection for Non-Stationary Processes

Joint Multi-frame Detection and Segmentation for Multi-cell Tracking

Weakly Supervised Deep Recurrent Neural Networks for Basic Dance Step Generation

Robust Non-Rigid Registration with Reweighted Position and Transformation Sparsity

Analytical Derivatives for Differentiable Renderer: 3D Pose Estimation by Silhouette Consistency

Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models

Learning Restricted Boltzmann Machines with Arbitrary External Fields

A Survey on Deep Learning Architectures for Image-based Depth Reconstruction

Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck

Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification

Clustered Gaussian Graphical Model via Symmetric Convex Clustering

Reasoning Visual Dialogs with Structural and Partial Observations

Low-Complexity Data-Parallel Earth Mover's Distance Approximations

High-Dimensional Poisson DAG Model Learning Using $\ell_1$-Regularized Regression

EgoFace: Egocentric Face Performance Capture and Videorealistic Reenactment

Computationally Efficient Deep Neural Network for Computed Tomography Image Reconstruction

Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay

Real-time Approximate Bayesian Computation for Scene Understanding

PANDA: AdaPtive Noisy Data Augmentation for Regularization of Undirected Graphical Models

Efficient Plane-Based Optimization of Geometry and Texture for Indoor RGB-D Reconstruction

Synthetic Defocus and Look-Ahead Autofocus for Casual Videography

A Comparative Analysis of Feature Selection Methods for Biomarker Discovery in Study of Toxicant-treated Atlantic Cod (Gadus morhua) Liver

Accelerating Deterministic and Stochastic Binarized Neural Networks on FPGAs Using OpenCL

LightTrack: A Generic Framework for Online Top-Down Human Pose Tracking

Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelines

A note on 'A fully parallel 3D thinning algorithm and its applications'

Towards Sampling from Nondirected Probabilistic Graphical models using a D-Wave Quantum Annealer

Separation of water and fat signal in whole-body gradient echo scans using convolutional neural networks

SurfelWarp: Efficient Non-Volumetric Single View Dynamic Reconstruction

Optimizing regularized Cholesky score for order-based learning of Bayesian networks

Deferred Neural Rendering: Image Synthesis using Neural Textures

Quantum-assisted associative adversarial network: Applying quantum annealing in deep learning

Solution of Definite Integrals using Functional Link Artificial Neural Networks

Client/Server Based Online Environment for Manual Segmentation of Medical Images

Variational Prototyping-Encoder: One-Shot Learning with Prototypical Images

Vid2Game: Controllable Characters Extracted from Real-World Videos

Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models

A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models

Custom Video-Oculography Device and Its Application to Fourth Purkinje Image Detection during Saccades

Geometric Shape Features Extraction Using a Steady State Partial Differential Equation System

Towards radiologist-level cancer risk assessment in CT lung screening using deep learning

Probabilistic Permutation Synchronization using the Riemannian Structure of the Birkhoff Polytope

Predicting Future Pedestrian Motion in Video Sequences using Crowd Simulation

Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras

Generalized Zero-Shot Recognition based on Visually Semantic Embedding

FineGAN: Unsupervised Hierarchical Disentanglement for Fine-Grained Object Generation and Discovery

Context-Aware Query Selection for Active Learning in Event Recognition

Generalized active learning and design of statistical experiments for manifold-valued data

Information Theoretic Feature Transformation Learning for Brain Interfaces

Coverage-Based Designs Improve Sample Mining and Hyper-Parameter Optimization

FEAFA: A Well-Annotated Dataset for Facial Expression Analysis and 3D Facial Animation

DeepLight: Learning Illumination for Unconstrained Mobile Mixed Reality

RenderNet: A deep convolutional network for differentiable rendering from 3D shapes

A Review of Learning with Deep Generative Models from Perspective of Graphical Modeling

Phenotype Inference with Semi-Supervised Mixed Membership Models

Photometric Mesh Optimization for Video-Aligned 3D Object Reconstruction

Machine Learning for Data-Driven Movement Generation: a Review of the State of the Art

Superpixel Contracted Graph-Based Learning for Hyperspectral Image Classification

Automatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Images

Higher-order Projected Power Iterations for Scalable Multi-Matching

A Capsule-unified Framework of Deep Neural Networks for Graphical Programming

Directed-Info GAIL: Learning Hierarchical Policies from Unsegmented Demonstrations using Directed Information

Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Polya Urns

Learning Quantum Graphical Models using Constrained Gradient Descent on the Stiefel Manifold

PDP: A General Neural Framework for Learning Constraint Satisfaction Solvers

Latent-space Physics: Towards Learning the Temporal Evolution of Fluid Flow

Joint Face Detection and Facial Motion Retargeting for Multiple Faces

Tensor Graphical Model: Non-convex Optimization and Statistical Inference

Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations

Model-based clustering in very high dimensions via adaptive projections

Deep CNN-based Speech Balloon Detection and Segmentation for Comic Books

Distributed Generalized Cross-Validation for Divide-and-Conquer Kernel Ridge Regression and its Asymptotic Optimality

On resampling vs. adjusting probabilistic graphical models in estimation of distribution algorithms

An Expectation Conditional Maximization approach for Gaussian graphical models

Deep Fluids: A Generative Network for Parameterized Fluid Simulations

Probabilistic Discriminative Learning with Layered Graphical Models

Cartoonish sketch-based face editing in videos using identity deformation transfer

Graphical-model based estimation and inference for differential privacy

Ask less - Scale Market Research without Annoying Your Customers

Can Adversarial Networks Hallucinate Occluded People With a Plausible Aspect?

DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation

Summarization and Visualization of Large Volumes of Broadcast Video Data

The Achievement of Higher Flexibility in Multiple Choice-based Tests Using Image Classification Techniques

A Curriculum Domain Adaptation Approach to the Semantic Segmentation of Urban Scenes

Graphical model inference: Sequential Monte Carlo meets deterministic approximations

Extreme Relative Pose Estimation for RGB-D Scans via Scene Completion

Batch Size Influence on Performance of Graphic and Tensor Processing Units during Training and Inference Phases

Wide Activation for Efficient and Accurate Image Super-Resolution

Training on Art Composition Attributes to Influence CycleGAN Art Generation

Fashion is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources

Nrityantar: Pose oblivious Indian classical dance sequence classification system

Reading Industrial Inspection Sheets by Inferring Visual Relations

Learning Spherical Convolution for Fast Features from 360° Imagery

Rigid Body Structure and Motion From Two-Frame Point-Correspondences Under Perspective Projection

Monocular Total Capture: Posing Face, Body, and Hands in the Wild

Generating High Fidelity Images with Subscale Pixel Networks and Multidimensional Upscaling

Improving Landmark Recognition using Saliency detection and Feature classification

Instance-level Facial Attributes Transfer with Geometry-Aware Flow

Fast and Flexible Indoor Scene Synthesis via Deep Convolutional Generative Models

Faithful Inversion of Generative Models for Effective Amortized Inference

Information Theoretic Optimal Learning of Gaussian Graphical Models

Probabilistic Graphs for Sensor Data-driven Modelling of Power Systems at Scale

Evaluating the Readability of Force Directed Graph Layouts: A Deep Learning Approach

Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes

Block Belief Propagation for Parameter Learning in Markov Random Fields

Learning Restricted Boltzmann Machines via Influence Maximization

Deep Structured Prediction with Nonlinear Output Transformations

Divergence Network: Graphical calculation method of divergence functions

Learning and Inference in Hilbert Space with Quantum Graphical Models

IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis

Capsule-Forensics: Using Capsule Networks to Detect Forged Images and Videos

LMap: Shape-Preserving Local Mappings for Biomedical Visualization

Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena

Fruit and Vegetable Identification Using Machine Learning for Retail Applications

RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records

Corresponding Supine and Prone Colon Visualization Using Eigenfunction Analysis and Fold Modeling

Efficient, Certifiably Optimal Clustering with Applications to Latent Variable Graphical Models

Maximum Regularized Likelihood Estimators: A General Prediction Theory and Applications

On the Learning of Deep Local Features for Robust Face Spoofing Detection

Super-Resolution via Conditional Implicit Maximum Likelihood Estimation

Spontaneous Facial Expression Recognition using Sparse Representation

Improving Bag-of-Visual-Words Towards Effective Facial Expressive Image Classification

A Sparse Non-negative Matrix Factorization Framework for Identifying Functional Units of Tongue Behavior from MRI

DFTerNet: Towards 2-bit Dynamic Fusion Networks for Accurate Human Activity Recognition

A Semi-Supervised Data Augmentation Approach using 3D Graphical Engines

Embedded-State Latent Conditional Random Fields for Sequence Labeling

Model-Preserving Sensitivity Analysis for Families of Gaussian Distributions

A Simple Approach to Intrinsic Correspondence Learning on Unstructured 3D Meshes

Properties and Bayesian fitting of restricted Boltzmann machines

Weakly-Supervised Learning of Metric Aggregations for Deformable Image Registration

Vis-DSS: An Open-Source toolkit for Visual Data Selection and Summarization

Data-Driven Design: Exploring new Structural Forms using Machine Learning and Graphic Statics

Learning of Tree-Structured Gaussian Graphical Models on Distributed Data under Communication Constraints

Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World

Modelling Latent Travel Behaviour Characteristics with Generative Machine Learning

A Hierarchical Deep Architecture and Mini-Batch Selection Method For Joint Traffic Sign and Light Detection

Urban MV and LV Distribution Grid Topology Estimation via Group Lasso

Unsupervised Deep Single-Image Intrinsic Decomposition using Illumination-Varying Image Sequences

Improved Breast Mass Segmentation in Mammograms with Conditional Residual U-net

Deep multi-task learning for a geographically-regularized semantic segmentation of aerial images

Learning Discriminative 3D Shape Representations by View Discerning Networks

A Distribution Similarity Based Regularizer for Learning Bayesian Networks

Imagining the Unseen: Learning a Distribution over Incomplete Images with Dense Latent Trees

MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics

Counterfactual Normalization: Proactively Addressing Dataset Shift and Improving Reliability Using Causal Mechanisms

Learning the effect of latent variables in Gaussian Graphical models with unobserved variables

EBIC: an evolutionary-based parallel biclustering algorithm for pattern discover

A Projection Pursuit Forest Algorithm for Supervised Classification

CaricatureShop: Personalized and Photorealistic Caricature Sketching

3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context

The Contextual Loss for Image Transformation with Non-Aligned Data

A Deep Learning Driven Active Framework for Segmentation of Large 3D Shape Collections

EndNet: Sparse AutoEncoder Network for Endmember Extraction and Hyperspectral Unmixing

Belief Propagation Min-Sum Algorithm for Generalized Min-Cost Network Flow

Flow Network Tracking for Spatiotemporal and Periodic Point Matching: Applied to Cardiac Motion Analysis

3D Human Action Recognition with Siamese-LSTM Based Deep Metric Learning

Who did What at Where and When: Simultaneous Multi-Person Tracking and Activity Recognition

Towards automatic initialization of registration algorithms using simulated endoscopy images

Dilated Temporal Fully-Convolutional Network for Semantic Segmentation of Motion Capture Data

Sequential change-point detection in high-dimensional Gaussian graphical models

Easily parallelizable and distributable class of algorithms for structured sparsity, with optimal acceleration

Stein Variational Message Passing for Continuous Graphical Models

Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion

Graphical posterior predictive classifier: Bayesian model averaging with particle Gibbs

Automatic Large-Scale Data Acquisition via Crowdsourcing for Crosswalk Classification: A Deep Learning Approach

Distributed Cartesian Power Graph Segmentation for Graphon Estimation

Stereo Magnification: Learning View Synthesis using Multiplane Images

Geographical Hidden Markov Tree for Flood Extent Mapping (With Proof Appendix)

Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure

GPU Accelerated Cascade Hashing Image Matching for Large Scale 3D Reconstruction

Analysis of Thompson Sampling for Graphical Bandits Without the Graphs

Bayesian Regularization for Graphical Models with Unequal Shrinkage

Extracting textual overlays from social media videos using neural networks

A Canonical Image Set for Examining and Comparing Image Processing Algorithms

Predictive Independence Testing, Predictive Conditional Independence Testing, and Predictive Graphical Modelling

Probabilistic Plant Modeling via Multi-View Image-to-Image Translation

A Saliency-based Convolutional Neural Network for Table and Chart Detection in Digitized Documents

Convolutional Neural Networks for Skull-stripping in Brain MR Imaging using Consensus-based Silver standard Masks

Transformation on Computer-Generated Facial Image to Avoid Detection by Spoofing Detector

Evaluation of the visual odometry methods for semi-dense real-time

The Unreasonable Effectiveness of Deep Features as a Perceptual Metric

Pilot Comparative Study of Different Deep Features for Palmprint Identification in Low-Quality Images

Convolutional Point-set Representation: A Convolutional Bridge Between a Densely Annotated Image and 3D Face Alignment

FloorNet: A Unified Framework for Floorplan Reconstruction from 3D Scans

Semi-supervised learning for structured regression on partially observed attributed graphs

Bayesian model and dimension reduction for uncertainty propagation: applications in random media

FaceForensics: A Large-scale Video Dataset for Forgery Detection in Human Faces

Deep Structure Inference Network for Facial Action Unit Recognition

BioTracker: An Open-Source Computer Vision Framework for Visual Animal Tracking

Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network

A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models

Momentum-Space Renormalization Group Transformation in Bayesian Image Modeling by Gaussian Graphical Model

Fast and robust curve skeletonization for real-world elongated objects

Learning Sparse Deep Feedforward Networks via Tree Skeleton Expansion

Wasserstein Dictionary Learning: Optimal Transport-based unsupervised non-linear dictionary learning

DeepN-JPEG: A Deep Neural Network Favorable JPEG-based Image Compression Framework

Exact and approximate inference in graphical models: variable elimination and beyond

Learning Large-Scale Bayesian Networks with the sparsebn Package

Inference Networks for Sequential Monte Carlo in Graphical Models

NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps

Fusion of multispectral satellite imagery using a cluster of graphics processing unit

Multi-Instance Dynamic Ordinal Random Fields for Weakly-supervised Facial Behavior Analysis

The State of the Art in Integrating Machine Learning into Visual Analytics

Iterative Refinement of the Approximate Posterior for Directed Belief Networks

Mesh Interest Point Detection Based on Geometric Measures and Sparse Refinement

Barista - a Graphical Tool for Designing and Training Deep Neural Networks

Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models

Robust 3D Human Motion Reconstruction Via Dynamic Template Construction

TernaryNet: Faster Deep Model Inference without GPUs for Medical 3D Segmentation using Sparse and Binary Convolutions

A Tutorial on Modeling and Inference in Undirected Graphical Models for Hyperspectral Image Analysis

Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment

Network-Scale Traffic Modeling and Forecasting with Graphical Lasso and Neural Networks

Bilinear residual Neural Network for the identification and forecasting of dynamical systems

GibbsNet: Iterative Adversarial Inference for Deep Graphical Models

An Integrated Platform for Live 3D Human Reconstruction and Motion Capturing

O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis

Dialectical Multispectral Classification of Diffusion-Weighted Magnetic Resonance Images as an Alternative to Apparent Diffusion Coefficients Maps to Perform Anatomical Analysis

Fuzzy-Based Dialectical Non-Supervised Image Classification and Clustering

Dynamic Graph Generation Network: Generating Relational Knowledge from Diagrams

Learning Graph-Structured Sum-Product Networks for Probabilistic Semantic Maps

Finding Differentially Covarying Needles in a Temporally Evolving Haystack: A Scan Statistics Perspective

Neural Variational Inference and Learning in Undirected Graphical Models

Learning Disentangled Representations with Semi-Supervised Deep Generative Models

Vertebral body segmentation with GrowCut: Initial experience, workflow and practical application

Keypoint-based object tracking and localization using networks of low-power embedded smart cameras

Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net

Beyond normality: Learning sparse probabilistic graphical models in the non-Gaussian setting

Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks

A Universal Marginalizer for Amortized Inference in Generative Models

An Integrated Approach to Crowd Video Analysis: From Tracking to Multi-level Activity Recognition

Automated Tumor Segmentation and Brain Mapping for the Tumor Area

Standard detectors aren't (currently) fooled by physical adversarial stop signs

Algorithm guided outlining of 105 pancreatic cancer liver metastases in Ultrasound

High-Resolution Shape Completion Using Deep Neural Networks for Global Structure and Local Geometry Inference

Inference in Graphical Models via Semidefinite Programming Hierarchies

A General Framework for the Recognition of Online Handwritten Graphics

pix2code: Generating Code from a Graphical User Interface Screenshot

Restoration of Atmospheric Turbulence-distorted Images via RPCA and Quasiconformal Maps

A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks

A constrained L1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models

Deep Scattering: Rendering Atmospheric Clouds with Radiance-Predicting Neural Networks

Dependence Modeling in Ultra High Dimensions with Vine Copulas and the Graphical Lasso

High-Dimensional Dependency Structure Learning for Physical Processes

Urban morphology meets deep learning: Exploring urban forms in one million cities, town and villages across the planet

SketchParse : Towards Rich Descriptions for Poorly Drawn Sketches using Multi-Task Hierarchical Deep Networks

Learning Local Shape Descriptors from Part Correspondences With Multi-view Convolutional Networks

Learning Implicit Generative Models Using Differentiable Graph Tests

Adversarial Inverse Graphics Networks: Learning 2D-to-3D Lifting and Image-to-Image Translation from Unpaired Supervision

A General Family of Trimmed Estimators for Robust High-dimensional Data Analysis

Accelerating recurrent neural network training using sequence bucketing and multi-GPU data parallelization

Using GPI-2 for Distributed Memory Paralleliziation of the Caffe Toolbox to Speed up Deep Neural Network Training

Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-Package flacco

Sparse Partially Collapsed MCMC for Parallel Inference in Topic Models

Personalized Cinemagraphs using Semantic Understanding and Collaborative Learning

Anveshak - A Groundtruth Generation Tool for Foreground Regions of Document Images

Weakly- and Self-Supervised Learning for Content-Aware Deep Image Retargeting

Knowledge-Guided Deep Fractal Neural Networks for Human Pose Estimation

Interpatient Respiratory Motion Model Transfer for Virtual Reality Simulations of Liver Punctures

Generation of High Dynamic Range Illumination from a Single Image for the Enhancement of Undesirably Illuminated Images

Learning to Hallucinate Face Images via Component Generation and Enhancement

FontCode: Embedding Information in Text Documents using Glyph Perturbation

Higher-Order Minimum Cost Lifted Multicuts for Motion Segmentation

Iterative Hard Thresholding for Model Selection in Genome-Wide Association Studies

Mesh Denoising based on Normal Voting Tensor and Binary Optimization

Fast Algorithms for Learning Latent Variables in Graphical Models

Composing graphical models with neural networks for structured representations and fast inference

Fast Estimation of Haemoglobin Concentration in Tissue Via Wavelet Decomposition

Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models

Learning Arbitrary Sum-Product Network Leaves with Expectation-Maximization

Getting deep recommenders fit: Bloom embeddings for sparse binary input/output networks

Graphical Nonconvex Optimization for Optimal Estimation in Gaussian Graphical Models

Production-Level Facial Performance Capture Using Deep Convolutional Neural Networks

Discriminative conditional restricted Boltzmann machine for discrete choice and latent variable modelling

Fixed Points of Belief Propagation -- An Analysis via Polynomial Homotopy Continuation

Causal Effect Identification in Acyclic Directed Mixed Graphs and Gated Models

Learning Gaussian Graphical Models Using Discriminated Hub Graphical Lasso

A Correspondence Relaxation Approach for 3D Shape Reconstruction

Distribution of degrees of freedom over structure and motion of rigid bodies

Light Field Video Capture Using a Learning-Based Hybrid Imaging System

Pixel Normalization from Numeric Data as Input to Neural Networks

Deep 360 Pilot: Learning a Deep Agent for Piloting through 360° Sports Video

VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera

XES Tensorflow - Process Prediction using the Tensorflow Deep-Learning Framework

Recovery of structure of looped jointed objects from multiframes

A closed-form approach to Bayesian inference in tree-structured graphical models

Learning Quadratic Variance Function (QVF) DAG models via OverDispersion Scoring (ODS)

A Fully Convolutional Neural Network for Cardiac Segmentation in Short-Axis MRI

Integrating Additional Knowledge Into Estimation of Graphical Models

3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study

Interactive Outlining of Pancreatic Cancer Liver Metastases in Ultrasound Images

Reconstruction of~3-D Rigid Smooth Curves Moving Free when Two Traceable Points Only are Available

Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models

Feature Selection for Regression Problems Based on the Morisita Estimator of Intrinsic Dimension

AMIDST: a Java Toolbox for Scalable Probabilistic Machine Learning

Learning a Variational Network for Reconstruction of Accelerated MRI Data

Complexity-Aware Assignment of Latent Values in Discriminative Models for Accurate Gesture Recognition

CDVAE: Co-embedding Deep Variational Auto Encoder for Conditional Variational Generation

Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs

A New Unbiased and Efficient Class of LSH-Based Samplers and Estimators for Partition Function Computation in Log-Linear Models

Growing Interpretable Part Graphs on ConvNets via Multi-Shot Learning

Combining Bayesian Approaches and Evolutionary Techniques for the Inference of Breast Cancer Networks

Parallel Implementation of Efficient Search Schemes for the Inference of Cancer Progression Models

Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions

Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimizations

Learning to Generate Posters of Scientific Papers by Probabilistic Graphical Models

RenderMap: Exploiting the Link Between Perception and Rendering for Dense Mapping

Maximum Persistency via Iterative Relaxed Inference with Graphical Models

Online Sequence Training of Recurrent Neural Networks with Connectionist Temporal Classification

Automatic Generation of Typographic Font from a Small Font Subset

Online Structure Learning for Sum-Product Networks with Gaussian Leaves

Son of Zorn's Lemma: Targeted Style Transfer Using Instance-aware Semantic Segmentation

Optimal statistical decision for Gaussian graphical model selection

Communication-efficient Distributed Estimation and Inference for Transelliptical Graphical Models

Unsupervised Video Segmentation via Spatio-Temporally Nonlocal Appearance Learning

Visual Compiler: Synthesizing a Scene-Specific Pedestrian Detector and Pose Estimator

Summary - TerpreT: A Probabilistic Programming Language for Program Induction

Photorealistic Facial Texture Inference Using Deep Neural Networks

Associative Memory using Dictionary Learning and Expander Decoding

FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Cameras

PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI

A Distance Function for Comparing Straight-Edge Geometric Figures

Inducing Interpretable Representations with Variational Autoencoders

CAS-CNN: A Deep Convolutional Neural Network for Image Compression Artifact Suppression

Nonlinear Statistical Learning with Truncated Gaussian Graphical Models

Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity

Generalisation and Sharing in Triplet Convnets for Sketch based Visual Search

Annealing Gaussian into ReLU: a New Sampling Strategy for Leaky-ReLU RBM

Audio-Visual Speaker Diarization Based on Spatiotemporal Bayesian Fusion

Recent Advances in Transient Imaging: A Computer Graphics and Vision Perspective

Streaming regularization parameter selection via stochastic gradient descent

Natural-Parameter Networks: A Class of Probabilistic Neural Networks

Embedding Deep Metric for Person Re-identication A Study Against Large Variations

Provably Good Early Detection of Diseases using Non-Sparse Covariance-Regularized Linear Discriminant Analysis

A new algorithm for identity verification based on the analysis of a handwritten dynamic signature

A Birth and Death Process for Bayesian Network Structure Inference

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution

Non-convex Global Minimization and False Discovery Rate Control for the TREX

An Interactive Segmentation Tool for Quantifying Fat in Lumbar Muscles using Axial Lumbar-Spine MRI

Towards Bayesian Deep Learning: A Framework and Some Existing Methods

Joint Estimation of Multiple Dependent Gaussian Graphical Models with Applications to Mouse Genomics

Rigid Slice-To-Volume Medical Image Registration through Markov Random Fields

TerpreT: A Probabilistic Programming Language for Program Induction

Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition

An equalised global graphical model-based approach for multi-camera object tracking

Dynamic Sum Product Networks for Tractable Inference on Sequence Data (Extended Version)

Model-Driven Feed-Forward Prediction for Manipulation of Deformable Objects

Pixel-level Encoding and Depth Layering for Instance-level Semantic Labeling

A New Hierarchical Redundancy Eliminated Tree Augmented Naive Bayes Classifier for Coping with Gene Ontology-based Features

Identifiability Assumptions and Algorithm for Directed Graphical Models with Feedback

Sparse Graphical Representation based Discriminant Analysis for Heterogeneous Face Recognition

Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization

Persistence Lenses: Segmentation, Simplification, Vectorization, Scale Space and Fractal Analysis of Images

Distributed Machine Learning in Materials that Couple Sensing, Actuation, Computation and Communication

Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies

Generalized Root Models: Beyond Pairwise Graphical Models for Univariate Exponential Families

An unsupervised spatiotemporal graphical modeling approach to anomaly detection in distributed CPS

Modeling and Estimation of Discrete-Time Reciprocal Processes via Probabilistic Graphical Models

Fast and High-Quality Bilateral Filtering Using Gauss-Chebyshev Approximation

Contrastive Structured Anomaly Detection for Gaussian Graphical Models

Incremental Reconstruction of Urban Environments by Edge-Points Delaunay Triangulation

Using Apache Lucene to Search Vector of Locally Aggregated Descriptors

Pieces-of-parts for supervoxel segmentation with global context: Application to DCE-MRI tumour delineation

Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition

A U-statistic Approach to Hypothesis Testing for Structure Discovery in Undirected Graphical Models

On the Geometry of Message Passing Algorithms for Gaussian Reciprocal Processes

Learning from Imbalanced Multiclass Sequential Data Streams Using Dynamically Weighted Conditional Random Fields

On the inconsistency of $\ell_1$-penalised sparse precision matrix estimation

Interactive and Scale Invariant Segmentation of the Rectum/Sigmoid via User-Defined Templates

Cellular Automata Segmentation of the Boundary between the Compacta of Vertebral Bodies and Surrounding Structures

US-Cut: Interactive Algorithm for rapid Detection and Segmentation of Liver Tumors in Ultrasound Acquisitions

Learning Gaussian Graphical Models With Fractional Marginal Pseudo-likelihood

Segmentation Rectification for Video Cutout via One-Class Structured Learning

An End-to-End Neural Network for Polyphonic Piano Music Transcription

Detection and Visualization of Endoleaks in CT Data for Monitoring of Thoracic and Abdominal Aortic Aneurysm Stents

Efficient Multi-view Performance Capture of Fine-Scale Surface Detail

On the Nyström and Column-Sampling Methods for the Approximate Principal Components Analysis of Large Data Sets

Virtual Rephotography: Novel View Prediction Error for 3D Reconstruction

B-spline Shape from Motion & Shading: An Automatic Free-form Surface Modeling for Face Reconstruction

Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis

Computational Pathology: Challenges and Promises for Tissue Analysis

Using Causal Discovery to Track Information Flow in Spatio-Temporal Data - A Testbed and Experimental Results Using Advection-Diffusion Simulations

Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models

A Multiresolution Clinical Decision Support System Based on Fractal Model Design for Classification of Histological Brain Tumours

Assessment of texture measures susceptibility to noise in conventional and contrast enhanced computed tomography lung tumour images

Sparse Reconstruction of Compressive Sensing MRI using Cross-Domain Stochastically Fully Connected Conditional Random Fields

Learning population and subject-specific brain connectivity networks via Mixed Neighborhood Selection

SceneNet: Understanding Real World Indoor Scenes With Synthetic Data

Maximum Likelihood Learning With Arbitrary Treewidth via Fast-Mixing Parameter Sets

Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso

On the Statistical Efficiency of $\ell_{1,p}$ Multi-Task Learning of Gaussian Graphical Models

Expresso : A user-friendly GUI for Designing, Training and Exploring Convolutional Neural Networks

GPU-Based Computation of 2D Least Median of Squares with Applications to Fast and Robust Line Detection

Parallel Stochastic Gradient Markov Chain Monte Carlo for Matrix Factorisation Models

Multi-view Convolutional Neural Networks for 3D Shape Recognition

A Robust Regression Approach for Background/Foreground Segmentation

Probabilistic Dependency Networks for Prediction and Diagnostics

Agglomerative clustering and collectiveness measure via exponent generating function

IT-Dendrogram: A New Member of the In-Tree (IT) Clustering Family

Massively Deep Artificial Neural Networks for Handwritten Digit Recognition

Multi-Step Stochastic ADMM in High Dimensions: Applications to Sparse Optimization and Noisy Matrix Decomposition

Local and Global Inference for High Dimensional Nonparanormal Graphical Models

A hybrid algorithm for Bayesian network structure learning with application to multi-label learning

Learning Scale-Free Networks by Dynamic Node-Specific Degree Prior

Spectral Learning of Large Structured HMMs for Comparative Epigenomics

Facial Expressions Tracking and Recognition: Database Protocols for Systems Validation and Evaluation

Fast and Accurate Bilateral Filtering using Gauss-Polynomial Decomposition

Rendering of Eyes for Eye-Shape Registration and Gaze Estimation

Algorithmic Analysis of Edge Ranking and Profiling for MTF Determination of an Imaging System

Template-based Monocular 3D Shape Recovery using Laplacian Meshes

Activity recognition from videos with parallel hypergraph matching on GPUs

Learning the Structure and Parameters of Large-Population Graphical Games from Behavioral Data

Combining Local Appearance and Holistic View: Dual-Source Deep Neural Networks for Human Pose Estimation

Sketch-based 3D Shape Retrieval using Convolutional Neural Networks

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

Deep Structured Output Learning for Unconstrained Text Recognition

Fast algorithms for morphological operations using run-length encoded binary images

Properties of simple sets in digital spaces. Contractions of simple sets preserving the homotopy type of a digital space

Polarization Measurement of High Dimensional Social Media Messages With Support Vector Machine Algorithm Using Mapreduce

Sublinear-Time Approximate MCMC Transitions for Probabilistic Programs

The Informed Sampler: A Discriminative Approach to Bayesian Inference in Generative Computer Vision Models

Fast image-based obstacle detection from unmanned surface vehicles

Partial light field tomographic reconstruction from a fixed-camera focal stack

Frequency Domain TOF: Encoding Object Depth in Modulation Frequency

A provably convergent alternating minimization method for mean field inference

NeuroSVM: A Graphical User Interface for Identification of Liver Patients

Landmark-Guided Elastic Shape Analysis of Human Character Motions

Data-Driven Scene Understanding with Adaptively Retrieved Exemplars

A Light Transport Model for Mitigating Multipath Interference in TOF Sensors

A Proximal Bregman Projection Approach to Continuous Max-Flow Problems Using Entropic Distances

Structure Regularization for Structured Prediction: Theories and Experiments

Risk Estimation Without Using Stein's Lemma -- Application to Image Denoising

HSI based colour image equalization using iterative nth root and nth power

Locating Tables in Scanned Documents for Reconstructing and Republishing (ICIAfS14)

The Affine Transforms for Image Enhancement in the Context of Logarithmic Models

Combining the Best of Graphical Models and ConvNets for Semantic Segmentation

Metric Learning Driven Multi-Task Structured Output Optimization for Robust Keypoint Tracking

Marginal Pseudo-Likelihood Learning of Markov Network structures

Articulated Pose Estimation by a Graphical Model with Image Dependent Pairwise Relations

Extended Dynamic Programming and Fast Multidimensional Search Algorithm for Energy Minization in Stereo and Motion

A Logic-based Approach to Generatively Defined Discriminative Modeling

SAME but Different: Fast and High-Quality Gibbs Parameter Estimation

Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation

Speeding-up Graphical Model Optimization via a Coarse-to-fine Cascade of Pruning Classifiers

Code Generation for High-Level Synthesis of Multiresolution Applications on FPGAs

Marginal Likelihoods for Distributed Parameter Estimation of Gaussian Graphical Models

Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality

Gaussian Process Structural Equation Models with Latent Variables

Modeling the Complex Dynamics and Changing Correlations of Epileptic Events

A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation

Newton-Type Iterative Solver for Multiple View $L2$ Triangulation

Composite Likelihood Estimation for Restricted Boltzmann machines

Parsing Semantic Parts of Cars Using Graphical Models and Segment Appearance Consistency

Distributed Parameter Estimation in Probabilistic Graphical Models

A Continuous Max-Flow Approach to Multi-Labeling Problems under Arbitrary Region Regularization

Supervised Dictionary Learning by a Variational Bayesian Group Sparse Nonnegative Matrix Factorization

Human Pose Estimation from RGB Input Using Synthetic Training Data

Robust Temporally Coherent Laplacian Protrusion Segmentation of 3D Articulated Bodies

Dynamic Hierarchical Bayesian Network for Arabic Handwritten Word Recognition

Review of Statistical Shape Spaces for 3D Data with Comparative Analysis for Human Faces

Pupil: An Open Source Platform for Pervasive Eye Tracking and Mobile Gaze-based Interaction

High Dimensional Semiparametric Latent Graphical Model for Mixed Data

Constraint Reduction using Marginal Polytope Diagrams for MAP LP Relaxations

Structural Intervention Distance (SID) for Evaluating Causal Graphs

An Efficient Search Strategy for Aggregation and Discretization of Attributes of Bayesian Networks Using Minimum Description Length

Extraction of Line Word Character Segments Directly from Run Length Compressed Printed Text Documents

Marginal and simultaneous predictive classification using stratified graphical models

Infrared face recognition: a comprehensive review of methodologies and databases

Reversible MCMC on Markov equivalence classes of sparse directed acyclic graphs

Embedding Graphs under Centrality Constraints for Network Visualization

Learning AMP Chain Graphs and some Marginal Models Thereof under Faithfulness: Extended Version

Nonparametric Latent Tree Graphical Models: Inference, Estimation, and Structure Learning

Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses

Markov Network Structure Learning via Ensemble-of-Forests Models

Parametric Modelling of Multivariate Count Data Using Probabilistic Graphical Models

A Junction Tree Framework for Undirected Graphical Model Selection

ADMM Algorithm for Graphical Lasso with an $\ell_{\infty}$ Element-wise Norm Constraint

Supervised Texture Classification Using a Novel Compression-Based Similarity Measure

Learning Pairwise Graphical Models with Nonlinear Sufficient Statistics

Stratified Graphical Models - Context-Specific Independence in Graphical Models

Anatomical Feature-guided Volumeric Registration of Multimodal Prostate MRI

Bayesian inference as iterated random functions with applications to sequential inference in graphical models

Distributed parameter estimation of discrete hierarchical models via marginal likelihoods

Inference, Sampling, and Learning in Copula Cumulative Distribution Networks

Labeled Directed Acyclic Graphs: a generalization of context-specific independence in directed graphical models

Correcting Multi-focus Images via Simple Standard Deviation for Image Fusion

Inverse Covariance Estimation for High-Dimensional Data in Linear Time and Space: Spectral Methods for Riccati and Sparse Models

Multiple Instance Learning by Discriminative Training of Markov Networks

Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction

GRED: Graph-Regularized 3D Shape Reconstruction from Highly Anisotropic and Noisy Images

Maximizing submodular functions using probabilistic graphical models

Bayesian Conditional Gaussian Network Classifiers with Applications to Mass Spectra Classification

A Max-Product EM Algorithm for Reconstructing Markov-tree Sparse Signals from Compressive Samples

The Cluster Graphical Lasso for improved estimation of Gaussian graphical models

Increasing Compression Ratio in PNG Images by k-Modulus Method for Image Transformation

Joint estimation of sparse multivariate regression and conditional graphical models

On Identifying Significant Edges in Graphical Models of Molecular Networks

Learning loopy graphical models with latent variables: Efficient methods and guarantees

pROST : A Smoothed Lp-norm Robust Online Subspace Tracking Method for Realtime Background Subtraction in Video

Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization

On the Geometry of Bayesian Graphical Models with Hidden Variables

Mixture Representations for Inference and Learning in Boltzmann Machines

Inferring Parameters and Structure of Latent Variable Models by Variational Bayes

Variational Approximations between Mean Field Theory and the Junction Tree Algorithm

Learning Features with Structure-Adapting Multi-view Exponential Family Harmoniums

Learning Graphical Model Parameters with Approximate Marginal Inference

Hierarchical Graphical Models for Multigroup Shape Analysis using Expectation Maximization with Sampling in Kendall's Shape Space

Network-based clustering with mixtures of L1-penalized Gaussian graphical models: an empirical investigation

Convex Relaxations for Learning Bounded Treewidth Decomposable Graphs

Learning a Common Substructure of Multiple Graphical Gaussian Models

High-dimensional structure estimation in Ising models: Local separation criterion

High Dimensional Semiparametric Gaussian Copula Graphical Models

An Integrated, Conditional Model of Information Extraction and Coreference with Applications to Citation Matching

Bayesian Learning in Undirected Graphical Models: Approximate MCMC algorithms

Approximated Structured Prediction for Learning Large Scale Graphical Models

A submodular-supermodular procedure with applications to discriminative structure learning

How To Grade a Test Without Knowing the Answers --- A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing

Dependence Maximizing Temporal Alignment via Squared-Loss Mutual Information

A Graphical Model Formulation of Collaborative Filtering Neighbourhood Methods with Fast Maximum Entropy Training

Learning the Bayesian Network Structure: Dirichlet Prior versus Data

The Phylogenetic Indian Buffet Process: A Non-Exchangeable Nonparametric Prior for Latent Features

Convergent Message-Passing Algorithms for Inference over General Graphs with Convex Free Energies

Causal discovery of linear acyclic models with arbitrary distributions

Cumulative distribution networks and the derivative-sum-product algorithm

Modeling Discrete Interventional Data using Directed Cyclic Graphical Models

A New Approach for Arabic Handwritten Postal Addresses Recognition

Finding Non-overlapping Clusters for Generalized Inference Over Graphical Models

Inference-less Density Estimation using Copula Bayesian Networks

Combining Spatial and Telemetric Features for Learning Animal Movement Models

Hybrid Generative/Discriminative Learning for Automatic Image Annotation

Learning Structural Changes of Gaussian Graphical Models in Controlled Experiments

Video Object Tracking and Analysis for Computer Assisted Surgery

Substructure and Boundary Modeling for Continuous Action Recognition

High-Dimensional Gaussian Graphical Model Selection: Walk Summability and Local Separation Criterion

An Efficient Algorithm for Computing Interventional Distributions in Latent Variable Causal Models

A PCA-Based Super-Resolution Algorithm for Short Image Sequences

High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods

Structure Learning of Probabilistic Graphical Models: A Comprehensive Survey

Discriminative Local Sparse Representations for Robust Face Recognition

Spectral Methods for Learning Multivariate Latent Tree Structure

A Flexible, Scalable and Efficient Algorithmic Framework for Primal Graphical Lasso

Efficient Latent Variable Graphical Model Selection via Split Bregman Method

Mixtures of conditional Gaussian scale mixtures applied to multiscale image representations

Design of an Optical Character Recognition System for Camera-based Handheld Devices

Exact covariance thresholding into connected components for large-scale Graphical Lasso

Hypothesize and Bound: A Computational Focus of Attention Mechanism for Simultaneous N-D Segmentation, Pose Estimation and Classification Using Shape Priors

Sparse Inverse Covariance Estimation via an Adaptive Gradient-Based Method

High-dimensional covariance estimation based on Gaussian graphical models

Face Shape and Reflectance Acquisition using a Multispectral Light Stage

DimReduction - Interactive Graphic Environment for Dimensionality Reduction

Feedback Message Passing for Inference in Gaussian Graphical Models

Defining and Generating Axial Lines from Street Center Lines for better Understanding of Urban Morphologies

Automatic Detection of Ringworm using Local Binary Pattern (LBP)

Handwritten Digit Recognition with a Committee of Deep Neural Nets on GPUs

Split Bregman Method for Sparse Inverse Covariance Estimation with Matrix Iteration Acceleration

Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference

Illustrating Color Evolution and Color Blindness by the Decoding Model of Color Vision

Brain covariance selection: better individual functional connectivity models using population prior

Sparse Inverse Covariance Selection via Alternating Linearization Methods

An Embarrassingly Simple Speed-Up of Belief Propagation with Robust Potentials

Fully automatic extraction of salient objects from videos in near real-time

Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models

L2-optimal image interpolation and its applications to medical imaging

Employing fuzzy intervals and loop-based methodology for designing structural signature: an application to symbol recognition

Graphic Symbol Recognition using Graph Based Signature and Bayesian Network Classifier

An empirical comparative study of approximate methods for binary graphical models; application to the search of associations among causes of death in French death certificates

Large Margin Boltzmann Machines and Large Margin Sigmoid Belief Networks

Medical Image Compression using Wavelet Decomposition for Prediction Method

Learning Gaussian Tree Models: Analysis of Error Exponents and Extremal Structures

Penalized Likelihood Methods for Estimation of Sparse High Dimensional Directed Acyclic Graphs

Positive factor networks: A graphical framework for modeling non-negative sequential data

Multiresolution Elastic Medical Image Registration in Standard Intensity Scale

Learning as Search Optimization: Approximate Large Margin Methods for Structured Prediction

Inferring Dynamic Bayesian Networks using Frequent Episode Mining

Learning Multiple Belief Propagation Fixed Points for Real Time Inference

A Standalone Markerless 3D Tracker for Handheld Augmented Reality

Distributed Preemption Decisions: Probabilistic Graphical Model, Algorithm and Near-Optimality

Survival tree and meld to predict long term survival in liver transplantation waiting list

Robust Near-Isometric Matching via Structured Learning of Graphical Models

Parameterizations and fitting of bi-directed graph models to categorical data

Graph rigidity, Cyclic Belief Propagation and Point Pattern Matching

Automatic Face Recognition System Based on Local Fourier-Bessel Features

Convexity Analysis of Snake Models Based on Hamiltonian Formulation

Semi-automatic vectorization of linear networks on rasterized cartographic maps

Stochastic Neural Radiance Fields: Quantifying Uncertainty in Implicit 3D Representations

Learning Object-Compositional Neural Radiance Field for Editable Scene Rendering

In-Place Scene Labelling and Understanding with Implicit Scene Representation

FLAME-in-NeRF : Neural control of Radiance Fields for Free View Face Animation

KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs

A Deep Signed Directional Distance Function for Object Shape Representation

Moving in a 360 World: Synthesizing Panoramic Parallaxes from a Single Panorama

MirrorNeRF: One-shot Neural Portrait Radiance Field from Multi-mirror Catadioptric Imaging

UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction

FiG-NeRF: Figure-Ground Neural Radiance Fields for 3D Object Category Modelling

Unconstrained Scene Generation with Locally Conditioned Radiance Fields

DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows

Resolution based Feature Distillation for Cross Resolution Person Re-Identification

D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-Resolution

Spectral Splitting and Aggregation Network for Hyperspectral Face Super-Resolution

Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Bursts

Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images

Super-Resolving Cross-Domain Face Miniatures by Peeking at One-Shot Exemplar

Hyperspectral Image Super-Resolution in Arbitrary Input-Output Band Settings

Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution

Fourier Series Expansion Based Filter Parametrization for Equivariant Convolutions

Real-Time Super-Resolution System of 4K-Video Based on Deep Learning

Learned super resolution ultrasound for improved breast lesion characterization

Effectiveness of State-of-the-Art Super Resolution Algorithms in Surveillance Environment

From General to Specific: Online Updating for Blind Super-Resolution

Super Resolution in Human Pose Estimation: Pixelated Poses to a Resolution Result?

Decoder-side Cross Resolution Synthesis for Video Compression Enhancement

Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis

Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects

SinIR: Efficient General Image Manipulation with Single Image Reconstruction

Variational AutoEncoder for Reference based Image Super-Resolution

NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results

Noise Conditional Flow Model for Learning the Super-Resolution Space

MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution

Feedback Network for Mutually Boosted Stereo Image Super-Resolution and Disparity Estimation

Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understanding

Low Resolution Information Also Matters: Learning Multi-Resolution Representations for Person Re-Identification

Towards Compact Single Image Super-Resolution via Contrastive Self-distillation

LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and Beyond

Extremely Lightweight Quantization Robust Real-Time Single-Image Super Resolution for Mobile Devices

Overparametrization of HyperNetworks at Fixed FLOP-Count Enables Fast Neural Image Enhancement

Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics

Fourier Neural Operator for Parametric Partial Differential Equations

Unsupervised Super-Resolution of Satellite Imagery for High Fidelity Material Label Transfer

An end-to-end Optical Character Recognition approach for ultra-low-resolution printed text images

Real-Time Video Super-Resolution by Joint Local Inference and Global Parameter Estimation

Multitask Learning for VVC Quality Enhancement and Super-Resolution

Multi Scale Identity-Preserving Image-to-Image Translation Network for Low-Resolution Face Recognition

Temporal Modulation Network for Controllable Space-Time Video Super-Resolution

BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment

Trilevel Neural Architecture Search for Efficient Single Image Super-Resolution

Intentional Deep Overfit Learning (IDOL): A Novel Deep Learning Strategy for Adaptive Radiation Therapy

Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations

Photothermal-SR-Net: A Customized Deep Unfolding Neural Network for Photothermal Super Resolution Imaging

Neural Architecture Search for Image Super-Resolution Using Densely Constructed Search Space: DeCoNAS

VSpSR: Explorable Super-Resolution via Variational Sparse Representation

Zooming SlowMo: An Efficient One-Stage Framework for Space-Time Video Super-Resolution

Towards Fast and Accurate Real-World Depth Super-Resolution: Benchmark Dataset and Baseline

SRR-Net: A Super-Resolution-Involved Reconstruction Method for High Resolution MR Imaging

Conditional Meta-Network for Blind Super-Resolution with Multiple Degradations

Joint Super-Resolution and Rectification for Solar Cell Inspection

Efficient Video Compression via Content-Adaptive Super-Resolution

Hyperspectral Image Super-Resolution with Spectral Mixup and Heterogeneous Datasets

Learning Continuous Image Representation with Local Implicit Image Function

Exploring Sparsity in Image Super-Resolution for Efficient Inference

KOALAnet: Blind Super-Resolution using Kernel-Oriented Adaptive Local Adjustment

Flow-based Kernel Prior with Application to Blind Super-Resolution

UltraSR: Spatial Encoding is a Missing Key for Implicit Image Function-based Arbitrary-Scale Super-Resolution

Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling

Adaptive Pixel-wise Structured Sparse Network for Efficient CNNs

ShipSRDet: An End-to-End Remote Sensing Ship Detector Using Super-Resolved Feature Representation

3D Human Pose, Shape and Texture from Low-Resolution Images and Videos

ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic

Provable Compressed Sensing with Generative Priors via Langevin Dynamics

Selfie Periocular Verification using an Efficient Super-Resolution Approach

Intermediate Layer Optimization for Inverse Problems using Deep Generative Models

Deep learning architectural designs for super-resolution of noisy images

Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans

Learning a Generative Motion Model from Image Sequences based on a Latent Motion Matrix

Proba-V-ref: Repurposing the Proba-V challenge for reference-aware super resolution

Regularization via deep generative models: an analysis point of view

Analysis and evaluation of Deep Learning based Super-Resolution algorithms to improve performance in Low-Resolution Face Recognition

Multiple Exemplars-based Hallucinationfor Face Super-resolution and Editing

Deep Likelihood Network for Image Restoration with Multiple Degradation Levels

Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis

DAQ: Distribution-Aware Quantization for Deep Image Super-Resolution Networks

Boosting High-Level Vision with Joint Compression Artifacts Reduction and Super-Resolution

Geometry Enhancements from Visual Content: Going Beyond Ground Truth

Physics-Informed Neural Network Super Resolution for Advection-Diffusion Models

Detailed 3D Human Body Reconstruction from Multi-view Images Combining Voxel Super-Resolution and Learned Implicit Representation

Learned Block Iterative Shrinkage Thresholding Algorithm for Photothermal Super Resolution Imaging

Boosting Image Super-Resolution Via Fusion of Complementary Information Captured by Multi-Modal Sensors

Perceptual Deep Neural Networks: Adversarial Robustness through Input Recreation

Unfolding the Alternating Optimization for Blind Super Resolution

FireSRnet: Geoscience-Driven Super-Resolution of Future Fire Risk from Climate Change

Learnable Sampling 3D Convolution for Video Enhancement and Action Recognition

Denoising Prior Driven Deep Neural Network for Image Restoration

Wavelet Flow: Fast Training of High Resolution Normalizing Flows

Cross-Scale Internal Graph Neural Network for Image Super-Resolution

A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery

Across Scales & Across Dimensions: Temporal Super-Resolution using Deep Internal Learning

DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-Resolution

FAN: Feature Adaptation Network for Surveillance Face Recognition and Normalization

MetH: A family of high-resolution and variable-shape image challenges

Augmented Convolutional LSTMs for Generation of High-Resolution Climate Change Projections

AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results

Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in Network

Biased Mixtures Of Experts: Enabling Computer Vision Inference Under Data Transfer Limitations

MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework

A Study of Efficient Light Field Subsampling and Reconstruction Strategies

3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised Learning

Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images

SRFlow: Learning the Super-Resolution Space with Normalizing Flow

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

Efficient Deep Neural Network for Photo-realistic Image Super-Resolution

Learning with Privileged Information for Efficient Image Super-Resolution

Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation

Lightweight Modules for Efficient Deep Learning based Image Restoration

BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture

Hierarchical Neural Architecture Search for Single Image Super-Resolution

Fast Generation of High Fidelity RGB-D Images by Deep-Learning with Adaptive Convolution

Unstructured Road Vanishing Point Detection Using the Convolutional Neural Network and Heatmap Regression

Correction Filter for Single Image Super-Resolution: Robustifying Off-the-Shelf Deep Super-Resolvers

Learning Sparse Low-Precision Neural Networks With Learnable Regularization

Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution

Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation

SRDA-Net: Super-Resolution Domain Adaptation Networks for Semantic Segmentation

Always Look on the Bright Side of the Field: Merging Pose and Contextual Data to Estimate Orientation of Soccer Players

AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results

Joint-SRVDNet: Joint Super Resolution and Vehicle Detection Network

Unsupervised Real Image Super-Resolution via Generative Variational AutoEncoder

Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and Latency

Mining self-similarity: Label super-resolution with epitomic representations

SimUSR: A Simple but Strong Baseline for Unsupervised Image Super-resolution

Super-resolution of clinical CT volumes with modified CycleGAN using micro CT volumes

Light Field Spatial Super-resolution via Deep Combinatorial Geometry Embedding and Structural Consistency Regularization

Unsupervised Real-world Image Super Resolution via Domain-distance Aware Training

Robust Single-Image Super-Resolution via CNNs and TV-TV Minimization

Algorithmic Guarantees for Inverse Imaging with Untrained Network Priors

MAMNet: Multi-path Adaptive Modulation Network for Image Super-Resolution

An End-to-end Framework For Low-Resolution Remote Sensing Semantic Segmentation

EventSR: From Asynchronous Events to Image Reconstruction, Restoration, and Super-Resolution via End-to-End Adversarial Learning

Is There Tradeoff between Spatial and Temporal in Video Super-Resolution?

Robust Online Video Super-Resolution Using an Efficient Alternating Projections Scheme

Semantic Object Prediction and Spatial Sound Super-Resolution with Binaural Sounds

FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution

Creating High Resolution Images with a Latent Adversarial Generator

Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution

Super-Resolving Commercial Satellite Imagery Using Realistic Training Data

3D U-Net for Segmentation of Plant Root MRI Images in Super-Resolution

HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery

Multi-Level Feature Fusion Mechanism for Single Image Super-Resolution

Learning Deep Analysis Dictionaries -- Part II: Convolutional Dictionaries

ERNet Family: Hardware-Oriented CNN Models for Computational Imaging Using Block-Based Inference

Spatial-Spectral Residual Network for Hyperspectral Image Super-Resolution

Efficient Residual Dense Block Search for Image Super-Resolution

Learning Filter Basis for Convolutional Neural Network Compression

FISR: Deep Joint Frame Interpolation and Super-Resolution with A Multi-scale Temporal Loss

Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational Approach

Deep Hyperspectral Prior: Denoising, Inpainting, Super-Resolution

Neural Network-Inspired Analog-to-Digital Conversion to Achieve Super-Resolution with Low-Precision RRAM Devices

Single Image Super-Resolution via CNN Architectures and TV-TV Minimization

Sub-frame Appearance and 6D Pose Estimation of Fast Moving Objects

Cascaded Detail-Preserving Networks for Super-Resolution of Document Images

Self-Enhanced Convolutional Network for Facial Video Hallucination

AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results

Learned Image Downscaling for Upscaling using Content Adaptive Resampler

Probabilistic Super-Resolution of Solar Magnetograms: Generating Many Explanations and Measuring Uncertainties

Multimodal Image Super-resolution via Deep Unfolding with Side Information

Practical License Plate Recognition in Unconstrained Surveillance Systems with Adversarial Super-Resolution

Deep Convolutional Neural Network for Multi-modal Image Restoration and Fusion

Evaluating Robustness of Deep Image Super-Resolution against Adversarial Attacks

Probabilistic Motion Modeling from Medical Image Sequences: Application to Cardiac Cine-MRI

DRFN: Deep Recurrent Fusion Network for Single-Image Super-Resolution with Large Factors

Flickr1024: A Large-Scale Dataset for Stereo Image Super-Resolution

SROBB: Targeted Perceptual Loss for Single Image Super-Resolution

CFSNet: Toward a Controllable Feature Space for Image Restoration

Frank-Wolfe Network: An Interpretable Deep Structure for Non-Sparse Coding

Benefiting from Multitask Learning to Improve Single Image Super-Resolution

Improved Super-Resolution Convolution Neural Network for Large Images

Learning Resolution-Invariant Deep Representations for Person Re-Identification

DFuseNet: Deep Fusion of RGB and Sparse Depth Information for Image Guided Dense Depth Completion

Distilling with Residual Network for Single Image Super Resolution

Super-Resolution of PROBA-V Images Using Convolutional Neural Networks

Super-Resolution for Hyperspectral and Multispectral Image Fusion Accounting for Seasonal Spectral Variability

A Single Video Super-Resolution GAN for Multiple Downsampling Operators based on Pseudo-Inverse Image Formation Models

A CNN-Based Super-Resolution Technique for Active Fire Detection on Sentinel-2 Data

3DSRnet: Video Super-resolution using 3D Convolutional Neural Networks

Exemplar Guided Face Image Super-Resolution without Facial Landmarks

Toward Bridging the Simulated-to-Real Gap: Benchmarking Super-Resolution on Real Data

Suppressing Model Overfitting for Image Super-Resolution Networks

Compressed Sensing MRI via a Multi-scale Dilated Residual Convolution Network

Single Image Blind Deblurring Using Multi-Scale Latent Structure Prior

Hybrid Function Sparse Representation towards Image Super Resolution

Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layers

Super-Resolution via Image-Adapted Denoising CNNs: Incorporating External and Internal Learning

Deep Residual Networks with a Fully Connected Recon-struction Layer for Single Image Super-Resolution

Improving Super-Resolution Methods via Incremental Residual Learning

Image quality assessment for determining efficacy and limitations of Super-Resolution Convolutional Neural Network (SRCNN)

Adapting Image Super-Resolution State-of-the-arts and Learning Multi-model Ensemble for Video Super-Resolution

Perceptual Video Super Resolution with Enhanced Temporal Consistency

PIRM2018 Challenge on Spectral Image Super-Resolution: Dataset and Study

Difficulty-aware Image Super Resolution via Deep Adaptive Dual-Network

An approach to image denoising using manifold approximation without clean images

Multi-scale deep neural networks for real image super-resolution

Adaptive Transform Domain Image Super-resolution Via Orthogonally Regularized Deep Networks

Deep Learning-based Image Super-Resolution Considering Quantitative and Perceptual Quality

Lightweight Feature Fusion Network for Single Image Super-Resolution

Fast Spatio-Temporal Residual Network for Video Super-Resolution

Lightweight Image Super-Resolution with Adaptive Weighted Learning Network

Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Model

On Low-Resolution Face Recognition in the Wild: Comparisons and New Techniques

Verification of Very Low-Resolution Faces Using An Identity-Preserving Deep Face Super-Resolution Network

Pixel-aware Deep Function-mixture Network for Spectral Super-Resolution

Robust Super-Resolution GAN, with Manifold-based and Perception Loss

Learning Super-resolution 3D Segmentation of Plant Root MRI Images from Few Examples

Generative Collaborative Networks for Single Image Super-Resolution

Blind Hyperspectral-Multispectral Image Fusion via Graph Laplacian Regularization

Super-Resolution of Brain MRI Images using Overcomplete Dictionaries and Nonlocal Similarity

Face hallucination using cascaded super-resolution and identity priors

Adversarial training with cycle consistency for unsupervised super-resolution in endomicroscopy

Three-dimensional Optical Coherence Tomography Image Denoising through Multi-input Fully-Convolutional Networks

Single MR Image Super-Resolution via Channel Splitting and Serial Fusion Network

Learning a Deep Convolution Network with Turing Test Adversaries for Microscopy Image Super Resolution

Linearized ADMM and Fast Nonlocal Denoising for Efficient Plug-and-Play Restoration

Detecting Overfitting of Deep Generative Networks via Latent Recovery

Image Super-Resolution via RL-CSC: When Residual Learning Meets Convolutional Sparse Coding

Multi-Frame Super-Resolution Reconstruction with Applications to Medical Imaging

Multimodal Sensor Fusion In Single Thermal image Super-Resolution

SREdgeNet: Edge Enhanced Single Image Super Resolution using Dense Edge Detection Network and Feature Merge Network

Advanced Super-Resolution using Lossless Pooling Convolutional Networks

Single Image Super-Resolution Using Lightweight CNN with Maxout Units

Binary Document Image Super Resolution for Improved Readability and OCR Performance

Lightweight and Efficient Image Super-Resolution with Block State-based Recursive Network

Accurate Spectral Super-resolution from Single RGB Image Using Multi-scale CNN

Privacy-Preserving Action Recognition for Smart Hospitals using Low-Resolution Depth Images

NeuroTreeNet: A New Method to Explore Horizontal Expansion Network

Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancement

Deep Unfolded Robust PCA with Application to Clutter Suppression in Ultrasound

Learning to synthesize: splitting and recombining low and high spatial frequencies for image recovery

Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation

LookinGood: Enhancing Performance Capture with Real-time Neural Re-Rendering

Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution

Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual Network

An Effective Single-Image Super-Resolution Model Using Squeeze-and-Excitation Networks

PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report

Theory of Generative Deep Learning : Probe Landscape of Empirical Error via Norm Based Capacity Control

Super-resolution of Sentinel-2 images: Learning a globally applicable deep neural network

Kernel based low-rank sparse model for single image super-resolution

Image Denoising and Super-Resolution using Residual Learning of Deep Convolutional Network

Dual Reconstruction Nets for Image Super-Resolution with Gradient Sensitive Loss

Efficient Single Image Super Resolution using Enhanced Learned Group Convolutions

MSCE: An edge preserving robust loss function for improving super-resolution algorithms

A New Adaptive Video Super-Resolution Algorithm With Improved Robustness to Innovations

Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Networks

Deep Learning Super-Resolution Enables Rapid Simultaneous Morphological and Quantitative Magnetic Resonance Imaging

The Unreasonable Effectiveness of Texture Transfer for Single Image Super-resolution

Multi-bin Trainable Linear Unit for Fast Image Restoration Networks

Gated Fusion Network for Joint Image Deblurring and Super-Resolution

CrossNet: An End-to-end Reference-based Super Resolution Network using Cross-scale Warping

A Tensor Factorization Method for 3D Super-Resolution with Application to Dental CT

Unsupervised Sparse Dirichlet-Net for Hyperspectral Image Super-Resolution

GUN: Gradual Upsampling Network for Single Image Super-Resolution

Local Patch Encoding-Based Method for Single Image Super-Resolution

Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination

Multi-modal Image Processing based on Coupled Dictionary Learning

Can Deep Learning Relax Endomicroscopy Hardware Miniaturization Requirements?

Dual Recovery Network with Online Compensation for Image Super-Resolution

New Techniques for Preserving Global Structure and Denoising with Low Information Loss in Single-Image Super-Resolution

Light field super resolution through controlled micro-shifts of light field sensor

Super-Resolution using Convolutional Neural Networks without Any Checkerboard Artifacts

Adaptive Importance Learning for Improving Lightweight Image Super-resolution Network

Patch-Based Image Hallucination for Super Resolution with Detail Reconstruction from Similar Sample Images

Quantifying Uncertainty in Discrete-Continuous and Skewed Data with Bayesian Deep Learning

Learning a Single Convolutional Super-Resolution Network for Multiple Degradations

A hybrid approach of interpolations and CNN to obtain super-resolution

Super-Resolution Reconstruction of Electrical Impedance Tomography Images

Learning Dual Convolutional Neural Networks for Low-Level Vision

Large Receptive Field Networks for High-Scale Image Super-Resolution

Densely Connected High Order Residual Network for Single Frame Image Super Resolution

A two-stage 3D Unet framework for multi-class segmentation on full resolution image

Computation-Performance Optimization of Convolutional Neural Networks with Redundant Kernel Removal

Reference-Conditioned Super-Resolution by Neural Texture Transfer

Blind Image Fusion for Hyperspectral Imaging with the Directional Total Variation

Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transform

Learning Descriptor Networks for 3D Shape Synthesis and Analysis

Learning to Become an Expert: Deep Networks Applied To Super-Resolution Microscopy

Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs

Fast and Accurate Single Image Super-Resolution via Information Distillation Network

xUnit: Learning a Spatial Activation Function for Efficient Image Restoration

Super-resolution of spatiotemporal event-stream image captured by the asynchronous temporal contrast vision sensor

Multimodal Image Super-resolution via Joint Sparse Representations induced by Coupled Dictionaries

Learning Discriminative Multilevel Structured Dictionaries for Supervised Image Classification

Single Image Super-Resolution via Cascaded Multi-Scale Cross Network

MagnifyMe: Aiding Cross Resolution Face Recognition via Identity Aware Synthesis

Deep Residual Network for Joint Demosaicing and Super-Resolution

Learning from a Handful Volumes: MRI Resolution Enhancement with Volumetric Super-Resolution Forests

UG^2: a Video Benchmark for Assessing the Impact of Image Restoration and Enhancement on Automatic Visual Recognition

Multispectral Compressive Imaging Strategies using Fabry-Pérot Filtered Sensors

Orthogonally Regularized Deep Networks For Image Super-resolution

SESR: Single Image Super Resolution with Recursive Squeeze and Excitation Networks

How should a fixed budget of dwell time be spent in scanning electron microscopy to optimize image quality?

Brain MRI Super Resolution Using 3D Deep Densely Connected Neural Networks

Deep Appearance Models: A Deep Boltzmann Machine Approach for Face Modeling

A Frequency Domain Neural Network for Fast Image Super-resolution

BLADE: Filter Learning for General Purpose Computational Photography

Single Image Super-resolution via a Lightweight Residual Convolutional Neural Network

Single Image Super-Resolution based on Wiener Filter in Similarity Domain

Deep Inception-Residual Laplacian Pyramid Networks for Accurate Single Image Super-Resolution

CT-SRCNN: Cascade Trained and Trimmed Deep Convolutional Neural Networks for Image Super Resolution

Fast single image super-resolution based on sigmoid transformation

Accelerating GMM-based patch priors for image restoration: Three ingredients for a 100$\times$ speed-up

Multi-frame image super-resolution with fast upscaling technique

Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution

Temporal shape super-resolution by intra-frame motion encoding using high-fps structured light

Locally-adapted convolution-based super-resolution of irregularly-sampled ocean remote sensing data

Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging

CISRDCNN: Super-resolution of compressed images using deep convolutional neural networks

Joint Estimation of Camera Pose, Depth, Deblurring, and Super-Resolution from a Blurred Image Sequence

Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach

Weighted Low-rank Tensor Recovery for Hyperspectral Image Restoration

FAST: A Framework to Accelerate Super-Resolution Processing on Compressed Videos

Unsupervised Video Understanding by Reconciliation of Posture Similarities

A Framework for Super-Resolution of Scalable Video via Sparse Reconstruction of Residual Frames

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis

Structure-Preserving Image Super-resolution via Contextualized Multi-task Learning

Single Image Super-Resolution with Dilated Convolution based Multi-Scale Information Learning Inception Module

Enhanced Deep Residual Networks for Single Image Super-Resolution

How Does the Low-Rank Matrix Decomposition Help Internal and External Learnings for Super-Resolution

Low Resolution Face Recognition Using a Two-Branch Deep Convolutional Neural Network Architecture

DOTE: Dual cOnvolutional filTer lEarning for Super-Resolution and Cross-Modality Synthesis in MRI

Deep Learning for Isotropic Super-Resolution from Non-Isotropic 3D Electron Microscopy

Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification

Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution

Single Image Super-Resolution Using Multi-Scale Convolutional Neural Network

Effect of Super Resolution on High Dimensional Features for Unsupervised Face Recognition in the Wild

Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images using Weakly-Supervised Joint Convolutional Sparse Coding

Regularized Residual Quantization: a multi-layer sparse dictionary learning approach

Real-Time Video Super-Resolution with Spatio-Temporal Networks and Motion Compensation

Isotropic reconstruction of 3D fluorescence microscopy images using convolutional neural networks

One Network to Solve Them All --- Solving Linear Inverse Problems using Deep Projection Models

Single image super-resolution using self-optimizing mask via fractional-order gradient interpolation and reconstruction

LesionSeg: Semantic segmentation of skin lesions using Deep Convolutional Neural Network

DeepSD: Generating High Resolution Climate Change Projections through Single Image Super-Resolution

Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes

Manifold Based Low-rank Regularization for Image Restoration and Semi-supervised Learning

Language Independent Single Document Image Super-Resolution using CNN for improved recognition

Joint Dictionary Learning for Example-based Image Super-resolution

Learning a Mixture of Deep Networks for Single Image Super-Resolution

Privacy-Preserving Human Activity Recognition from Extreme Low Resolution

Deeply Aggregated Alternating Minimization for Image Restoration

Learning a No-Reference Quality Metric for Single-Image Super-Resolution

Super-resolution Reconstruction of SAR Image based on Non-Local Means Denoising Combined with BP Neural Network

Texture Enhancement via High-Resolution Style Transfer for Single-Image Super-Resolution

Multi-resolution Data Fusion for Super-Resolution Electron Microscopy

Plug-and-Play ADMM for Image Restoration: Fixed Point Convergence and Applications

Deeply-Recursive Convolutional Network for Image Super-Resolution

Accurate Image Super-Resolution Using Very Deep Convolutional Networks

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

Transport-based analysis, modeling, and learning from signal and data distributions

Confidence-aware Levenberg-Marquardt optimization for joint motion estimation and super-resolution

Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections

Constraint matrix factorization for space variant PSFs field restoration

Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections

Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

New wavelet-based superresolution algorithm for speckle reduction in SAR images

End-to-End Image Super-Resolution via Deep and Shallow Convolutional Networks

Deep Edge Guided Recurrent Residual Learning for Image Super-Resolution

Off-the-Grid Recovery of Piecewise Constant Images from Few Fourier Samples

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

Image Super-Resolution Based on Sparsity Prior via Smoothed $l_0$ Norm

Patch-Ordering as a Regularization for Inverse Problems in Image Processing

Structured illumination microscopy image reconstruction algorithm

An Efficient Algorithm for Video Super-Resolution Based On a Sequential Model

Super-resolution reconstruction of hyperspectral images via low rank tensor modeling and total variation regularization

Geometry-Aware Neighborhood Search for Learning Local Models for Image Reconstruction

Image Resolution Enhancement by Using Interpolation Followed by Iterative Back Projection

Face Hallucination using Linear Models of Coupled Sparse Support

Fidelity-Naturalness Evaluation of Single Image Super Resolution

Seven ways to improve example-based single image super resolution

Learning Super-Resolution Jointly from External and Internal Examples

Boosting Optical Character Recognition: A Super-Resolution Approach

Simple, Accurate, and Robust Nonparametric Blind Super-Resolution

Single image super-resolution by approximated Heaviside functions

Fast Sublinear Sparse Representation using Shallow Tree Matching Pursuit

Super-resolution method using sparse regularization for point-spread function recovery

A New Approach for Super resolution by Using Web Images and FFT Based Image Registration

Adaptive Mesh Representation and Restoration of Biomedical Images

Group Iterative Spectrum Thresholding for Super-Resolution Sparse Spectral Selection

A Joint Intensity and Depth Co-Sparse Analysis Model for Depth Map Super-Resolution

Analysis Operator Learning and Its Application to Image Reconstruction

A polygon-based interpolation operator for super-resolution imaging

Image Super-Resolution via Sparse Bayesian Modeling of Natural Images

Image Super-Resolution via Dual-Dictionary Learning And Sparse Representation

Posterior Mean Super-resolution with a Causal Gaussian Markov Random Field Prior

Posterior Mean Super-Resolution with a Compound Gaussian Markov Random Field Prior

POCS Based Super-Resolution Image Reconstruction Using an Adaptive Regularization Parameter

An Iterative Algorithm for Fitting Nonconvex Penalized Generalized Linear Models with Grouped Predictors

A novel super resolution reconstruction of low reoslution images progressively using dct and zonal filter based denoising

Image Deblurring and Super-resolution by Adaptive Sparse Domain Selection and Adaptive Regularization

Large Scale Variational Inference and Experimental Design for Sparse Generalized Linear Models

Variational local structure estimation for image super-resolution

Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes

Clustering with Tangles: Algorithmic Framework and Theoretical Guarantees

Grouptron: Dynamic Multi-Scale Graph Convolutional Networks for Group-Aware Dense Crowd Trajectory Forecasting

Integrating Contextual Knowledge to Visual Features for Fine Art Classification

Survey of Visual-Semantic Embedding Methods for Zero-Shot Image Retrieval

Modelling Neighbor Relation in Joint Space-Time Graph for Video Correspondence Learning

Fusion-GCN: Multimodal Action Recognition using Graph Convolutional Networks

Meta-Aggregator: Learning to Aggregate for 1-bit Graph Neural Networks

HAGEN: Homophily-Aware Graph Convolutional Recurrent Network for Crime Forecasting

DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks

A Hard Label Black-box Adversarial Attack Against Graph Neural Networks

Skeleton-Graph: Long-Term 3D Motion Prediction From 2D Observations Using Deep Spatio-Temporal Graph CNNs

Graph-Based Spatial-Temporal Convolutional Network for Vehicle Trajectory Prediction in Autonomous Driving

RaWaNet: Enriching Graph Neural Network Input via Random Walks on Graphs

Partial to Whole Knowledge Distillation: Progressive Distilling Decomposed Knowledge Boosts Student Better

Spatial Aggregation and Temporal Convolution Networks for Real-time Kriging

Nishimori meets Bethe: a spectral method for node classification in sparse weighted graphs

An automatic differentiation system for the age of differential privacy

Consistency of spectral clustering for directed network community detection

GOHOME: Graph-Oriented Heatmap Output for future Motion Estimation

Transferability of Graph Neural Networks: an Extended Graphon Approach

OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association

Graph Random Neural Network for Semi-Supervised Learning on Graphs

Structural Agnostic Modeling: Adversarial Learning of Causal Graphs

Relative Entropy-Regularized Optimal Transport on a Graph: a new algorithm and an experimental comparison

Feature Correlation Aggregation: on the Path to Better Graph Neural Networks

Homogeneous and Heterogeneous Relational Graph for Visible-infrared Person Re-identification

Efficient Variational Graph Autoencoders for Unsupervised Cross-domain Prerequisite Chains

LEAN: graph-based pruning for convolutional neural networks by extracting longest chains

Dynamic Spatiotemporal Graph Convolutional Neural Networks for Traffic Data Imputation with Complex Missing Patterns

Heterogeneous Relational Complement for Vehicle Re-identification

SPIN Road Mapper: Extracting Roads from Aerial Images via Spatial and Interaction Space Graph Reasoning for Autonomous Driving

Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals

Sample-Efficient L0-L2 Constrained Structure Learning of Sparse Ising Models

Learning Dynamical Human-Joint Affinity for 3D Pose Estimation in Videos

Image Captioning for Effective Use of Language Models in Knowledge-Based Visual Question Answering

Entropic Inequality Constraints from $e$-separation Relations in Directed Acyclic Graphs with Hidden Variables

IGNNITION: Bridging the Gap Between Graph Neural Networks and Networking Systems

Incremental Abstraction in Distributed Probabilistic SLAM Graphs

Auto-encoding brain networks with applications to analyzing large-scale brain imaging datasets

Graph-Based 3D Multi-Person Pose Estimation Using Multi-View Images

Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification?

CoG: a Two-View Co-training Framework for Defending Adversarial Attacks on Graph

GraphITE: Estimating Individual Effects of Graph-structured Treatments

Understanding Structural Vulnerability in Graph Convolutional Networks

Robust Max Entrywise Error Bounds for Sparse Tensor Estimation via Similarity Based Collaborative Filtering

Fairness without the sensitive attribute via Causal Variational Autoencoder

Unfolding Projection-free SDP Relaxation of Binary Graph Classifier via GDPA Linearization

Differentially Private Federated Learning with Laplacian Smoothing

A Fast PC Algorithm with Reversed-order Pruning and A Parallelization Strategy

Spatially Focused Attack against Spatiotemporal Graph Neural Networks

S3G-ARM: Highly Compressive Visual Self-localization from Sequential Semantic Scene Graph Using Absolute and Relative Measurements

SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings

Ergodic Limits, Relaxations, and Geometric Properties of Random Walk Node Embeddings

General Partial Label Learning via Dual Bipartite Graph Autoencoder

Fea2Fea: Exploring Structural Feature Correlations via Graph Neural Networks

Popularity Adjusted Block Models are Generalized Random Dot Product Graphs

OSSR-PID: One-Shot Symbol Recognition in P&ID Sheets using Path Sampling and GCN

Power to the Relational Inductive Bias: Graph Neural Networks in Electrical Power Grids

DeepAltTrip: Top-k Alternative Itineraries for Trip Recommendation

Distance preserving model order reduction of graph-Laplacians and cluster analysis

Fast Hypergraph Regularized Nonnegative Tensor Ring Factorization Based on Low-Rank Approximation

Quantifying the Reproducibility of Graph Neural Networks using Multigraph Brain Data

Reasoning Graph Networks for Kinship Verification: from Star-shaped to Hierarchical

Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks

Node Feature Kernels Increase Graph Convolutional Network Robustness

Information Symmetry Matters: A Modal-Alternating Propagation Network for Few-Shot Learning

ReLU Neural Networks of Polynomial Size for Exact Maximum Flow Computation

TLRM: Task-level Relation Module for GNN-based Few-Shot Learning

Bridge the Gap Between Model-based and Model-free Human Reconstruction

CycleCluster: Modernising Clustering Regularisation for Deep Semi-Supervised Classification

Quantized convolutional neural networks through the lens of partial differential equations

Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning

Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs

Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer

Adaptive Label Smoothing To Regularize Large-Scale Graph Training

Spatial-Temporal Conv-sequence Learning with Accident Encoding for Traffic Flow Prediction

DNNFusion: Accelerating Deep Neural Networks Execution with Advanced Operator Fusion

Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience (VesselGraph)

GeoVectors: A Linked Open Corpus of OpenStreetMap Embeddings on World Scale

Demystifying Drug Repurposing Domain Comprehension with Knowledge Graph Embedding

NeuroCartography: Scalable Automatic Visual Summarization of Concepts in Deep Neural Networks

Solving Viewing Graph Optimization for Simultaneous Position and Rotation Registration

Parallel Multi-Graph Convolution Network For Metro Passenger Volume Prediction

Action Sequence Augmentation for Early Graph-based Anomaly Detection

Power Normalizations in Fine-grained Image, Few-shot Image and Graph Classification

Adaptive and Interpretable Graph Convolution Networks Using Generalized Pagerank

VisGraphNet: a complex network interpretation of convolutional neural features

DC-GNet: Deep Mesh Relation Capturing Graph Convolution Network for 3D Human Shape Reconstruction

Group-Aware Graph Neural Network for Nationwide City Air Quality Forecasting

DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions

Exploiting Emotional Dependencies with Graph Convolutional Networks for Facial Expression Recognition

DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNN

Spatio-Temporal Dynamic Inference Network for Group Activity Recognition

GNNSampler: Bridging the Gap between Sampling Algorithms of GNN and Hardware

Predicting Sequences of Traversed Nodes in Graphs using Network Models with Multiple Higher Orders

Hierarchical Object-oriented Spatio-Temporal Reasoning for Video Question Answering

Applying Semi-Automated Hyperparameter Tuning for Clustering Algorithms

NGC: A Unified Framework for Learning with Open-World Noisy Data

DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene Context Graph and Relation-based Optimization

A Unifying Perspective on Neighbor Embeddings along the Attraction-Repulsion Spectrum

Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study

An Inverse QSAR Method Based on Linear Regression and Integer Programming

Understanding the Basis of Graph Convolutional Neural Networks via an Intuitive Matched Filtering Approach

Integrating Transductive And Inductive Embeddings Improves Link Prediction Accuracy

Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition

Efficient Online Estimation of Causal Effects by Deciding What to Observe

Learning 1-Dimensional Submanifolds for Subsequent Inference on Random Dot Product Graphs

TabGNN: Multiplex Graph Neural Network for Tabular Data Prediction

Graph-to-3D: End-to-End Generation and Manipulation of 3D Scenes Using Scene Graphs

Spatio-Temporal Interaction Graph Parsing Networks for Human-Object Interaction Recognition

Semantic Compositional Learning for Low-shot Scene Graph Generation

GP-S3Net: Graph-based Panoptic Sparse Semantic Segmentation Network

WildGait: Learning Gait Representations from Raw Surveillance Streams

Target Adaptive Context Aggregation for Video Scene Graph Generation

On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity

Clustering dynamics on graphs: from spectral clustering to mean shift through Fokker-Planck interpolation

HyperSF: Spectral Hypergraph Coarsening via Flow-based Local Clustering

RRLFSOR: An Efficient Self-Supervised Learning Strategy of Graph Convolutional Networks

Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation

MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction

Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation

ROSITA: Enhancing Vision-and-Language Semantic Alignments via Cross- and Intra-modal Knowledge Integration

Non-Local Feature Aggregation on Graphs via Latent Fixed Data Structures

Causal Incremental Graph Convolution for Recommender System Retraining

Hierarchical graph neural nets can capture long-range interactions

Effective and Efficient Graph Learning for Multi-view Clustering

Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture

Fusing Higher-Order Features in Graph Neural Networks for Skeleton-Based Action Recognition

AdaGNN: A multi-modal latent representation meta-learner for GNNs based on AdaBoosting

Neural Ordinary Differential Equation Control of Dynamics on Graphs

Multi-Stage Graph Peeling Algorithm for Probabilistic Core Decomposition

Adaptive Boundary Proposal Network for Arbitrary Shape Text Detection

Track without Appearance: Learn Box and Tracklet Embedding with Local and Global Motion Patterns for Vehicle Tracking

Room Classification on Floor Plan Graphs using Graph Neural Networks

EV-VGCNN: A Voxel Graph CNN for Event-based Object Classification

Learning Based Proximity Matrix Factorization for Node Embedding

Towards Novel Target Discovery Through Open-Set Domain Adaptation

EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks

Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound

Semantics-STGCNN: A Semantics-guided Spatial-Temporal Graph Convolutional Network for Multi-class Trajectory Prediction

Select, Substitute, Search: A New Benchmark for Knowledge-Augmented Visual Question Answering

Transferring Knowledge Distillation for Multilingual Social Event Detection

Learning Multi-Granular Spatio-Temporal Graph Network for Skeleton-based Action Recognition

PSGR: Pixel-wise Sparse Graph Reasoning for COVID-19 Pneumonia Segmentation in CT Images

MAF-GNN: Multi-adaptive Spatiotemporal-flow Graph Neural Network for Traffic Speed Forecasting

Multilevel Graph Matching Networks for Deep Graph Similarity Learning

Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss

Learning and Segmenting Dense Voxel Embeddings for 3D Neuron Reconstruction

Understanding Human Innate Immune System Dependencies using Graph Neural Networks

Enterprise Analytics using Graph Database and Graph-based Deep Learning

AutoLL: Automatic Linear Layout of Graphs based on Deep Neural Network

On Generalization of Graph Autoencoders with Adversarial Training

Conditional Directed Graph Convolution for 3D Human Pose Estimation

ItNet: iterative neural networks with small graphs for accurate, efficient and anytime semantic segmentation

Skeleton Split Strategies for Spatial Temporal Graph Convolution Networks

Pure Exploration in Multi-armed Bandits with Graph Side Information

Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data

Cold Start Similar Artists Ranking with Gravity-Inspired Graph Autoencoders

Neural Weighted A*: Learning Graph Costs and Heuristics with Differentiable Anytime A*

Masking Neural Networks Using Reachability Graphs to Predict Process Events

STEP: Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits

Relational Graph Neural Networks for Fraud Detection in a Super-App environment

Automatic Vocabulary and Graph Verification for Accurate Loop Closure Detection

Enhancing Social Relation Inference with Concise Interaction Graph and Discriminative Scene Representation

Large sample spectral analysis of graph-based multi-manifold clustering

Towards Neural Schema Alignment for OpenStreetMap and Knowledge Graphs

Structack: Structure-based Adversarial Attacks on Graph Neural Networks

Multi-Graph Convolutional-Recurrent Neural Network (MGC-RNN) for Short-Term Forecasting of Transit Passenger Flow

Explicit Pairwise Factorized Graph Neural Network for Semi-Supervised Node Classification

Channel-Wise Early Stopping without a Validation Set via NNK Polytope Interpolation

Estimating Parkinsonism Severity in Natural Gait Videos of Older Adults with Dementia

Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance

Subgraph-aware Few-Shot Inductive Link Prediction via Meta-Learning

CP-loss: Connectivity-preserving Loss for Road Curb Detection in Autonomous Driving with Aerial Images

X-GGM: Graph Generative Modeling for Out-of-Distribution Generalization in Visual Question Answering

Toward Automated Classroom Observation: Multimodal Machine Learning to Estimate CLASS Positive Climate and Negative Climate

Human Pose Estimation from Sparse Inertial Measurements through Recurrent Graph Convolution

Label Distribution Amendment with Emotional Semantic Correlations for Facial Expression Recognition

Resource Efficient Mountainous Skyline Extraction using Shallow Learning

Best-of-All-Worlds Bounds for Online Learning with Feedback Graphs

Graph-based Facial Affect Analysis: A Review of Methods, Applications and Challenges

Wide and Deep Graph Neural Network with Distributed Online Learning

Using system context information to complement weakly labeled data

Composite Neural Network: Theory and Application to PM2.5 Prediction

Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models

Train on Small, Play the Large: Scaling Up Board Games with AlphaZero and GNN

Learning Hierarchical Graph Neural Networks for Image Clustering

SportsCap: Monocular 3D Human Motion Capture and Fine-grained Understanding in Challenging Sports Videos

From Local Structures to Size Generalization in Graph Neural Networks

Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More

GREN: Graph-Regularized Embedding Network for Weakly-Supervised Disease Localization in X-ray images

Recommendation system using a deep learning and graph analysis approach

Correlation Analysis between the Robustness of Sparse Neural Networks and their Random Hidden Structural Priors

Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries

Communication-Computation Efficient Secure Aggregation for Federated Learning

BrainNNExplainer: An Interpretable Graph Neural Network Framework for Brain Network based Disease Analysis

Zero-Shot Scene Graph Relation Prediction through Commonsense Knowledge Integration

A unified framework based on graph consensus term for multi-view learning

Prediction of concept lengths for fast concept learning in description logics

Improving Inductive Link Prediction Using Hyper-Relational Facts

Meta-Learning with Graph Neural Networks: Methods and Applications

Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning

DeepRelativeFusion: Dense Monocular SLAM using Single-Image Relative Depth Prediction

Autocalibration and Tweedie-dominance for Insurance Pricing with Machine Learning

GGT: Graph-Guided Testing for Adversarial Sample Detection of Deep Neural Network

Graph-based Deep Generative Modelling for Document Layout Generation

Scaling Gaussian Processes with Derivative Information Using Variational Inference

Classifying Component Function in Product Assemblies with Graph Neural Networks

Short-term Hourly Streamflow Prediction with Graph Convolutional GRU Networks

Mitigating Performance Saturation in Neural Marked Point Processes: Architectures and Loss Functions

Formal derivation of Mesh Neural Networks with their Forward-Only gradient Propagation

Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information

Coarse-to-fine Semantic Localization with HD Map for Autonomous Driving in Structural Scenes

ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training

Dirichlet Energy Constrained Learning for Deep Graph Neural Networks

Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting

Bag of Tricks for Node Classification with Graph Neural Networks

SM-SGE: A Self-Supervised Multi-Scale Skeleton Graph Encoding Framework for Person Re-Identification

Learning a Model for Inferring a Spatial Road Lane Network Graph using Self-Supervision

Latent structure blockmodels for Bayesian spectral graph clustering

Learning Bayesian Networks through Birkhoff Polytope: A Relaxation Method

Leveraging Evidential Deep Learning Uncertainties with Graph-based Clustering to Detect Anomalies

Full interpretable machine learning in 2D with inline coordinates

On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs

Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks

Multi-view Graph Learning by Joint Modeling of Consistency and Inconsistency

Unified Interpretation of Softmax Cross-Entropy and Negative Sampling: With Case Study for Knowledge Graph Embedding

Cluster Representatives Selection in Non-Metric Spaces for Nearest Prototype Classification

Prequential MDL for Causal Structure Learning with Neural Networks

HandVoxNet++: 3D Hand Shape and Pose Estimation using Voxel-Based Neural Networks

Compressive Representations of Weather Scenes for Strategic Air Traffic Flow Management

Bayesian Hyperparameter Optimization with BoTorch, GPyTorch and Ax

Topo-boundary: A Benchmark Dataset on Topological Road-boundary Detection Using Aerial Images for Autonomous Driving

Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets

Learning Large DAGs by Combining Continuous Optimization and Feedback Arc Set Heuristics

GIST: Distributed Training for Large-Scale Graph Convolutional Networks

GraphFM: Graph Factorization Machines for Feature Interaction Modeling

Dual GNNs: Graph Neural Network Learning with Limited Supervision

Diff2Dist: Learning Spectrally Distinct Edge Functions, with Applications to Cell Morphology Analysis

RICE: Refining Instance Masks in Cluttered Environments with Graph Neural Networks

Impossibility of Partial Recovery in the Graph Alignment Problem

Leveraging Static Models for Link Prediction in Temporal Knowledge Graphs

Constructing Stronger and Faster Baselines for Skeleton-based Action Recognition

Relational Graph Learning on Visual and Kinematics Embeddings for Accurate Gesture Recognition in Robotic Surgery

HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps

Adventurer's Treasure Hunt: A Transparent System for Visually Grounded Compositional Visual Question Answering based on Scene Graphs

The KL-Divergence between a Graph Model and its Fair I-Projection as a Fairness Regularizer

Anomaly Detection for Aggregated Data Using Multi-Graph Autoencoder

A Behavior-aware Graph Convolution Network Model for Video Recommendation

Exploring and Distilling Posterior and Prior Knowledge for Radiology Report Generation

Efficient Document Image Classification Using Region-Based Graph Neural Network

Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework

Optimal Pose and Shape Estimation for Category-level 3D Object Perception

Visualizing Graph Neural Networks with CorGIE: Corresponding a Graph to Its Embedding

Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs

Rethinking Graph Neural Architecture Search from Message-passing

Nonlinear Matrix Approximation with Radial Basis Function Components

Leveraging semantically similar queries for ranking via combining representations

Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural Networks

Algorithmic Recourse in Partially and Fully Confounded Settings Through Bounding Counterfactual Effects

A Vertical Federated Learning Framework for Graph Convolutional Network

Effective Semi-Supervised Node Classification on Few-Labeled Graph Data

3D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching

GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Prediction

BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation

Deep Spatio-Temporal Forecasting of Electrical Vehicle Charging Demand

Learned Factor Graphs for Inference from Stationary Time Sequences

The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs

Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem

Opportunities and challenges in partitioning the graph measure space of real-world networks

First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track

Graph Neural Networks for Learning Real-Time Prices in Electricity Market

Stability of Graph Convolutional Neural Networks to Stochastic Perturbations

A non-alternating graph hashing algorithm for large scale image search

A Unified View of Algorithms for Path Planning Using Probabilistic Inference on Factor Graphs

Self-supervised Incremental Deep Graph Learning for Ethereum Phishing Scam Detection

Towards Clustering-friendly Representations: Subspace Clustering via Graph Filtering

Rotation Invariant Graph Neural Networks using Spin Convolutions

NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go

Predicting cognitive scores with graph neural networks through sample selection learning

Joining datasets via data augmentation in the label space for neural networks

AN-GCN: An Anonymous Graph Convolutional Network Defense Against Edge-Perturbing Attack

Towards a Rigorous Theoretical Analysis and Evaluation of GNN Explanations

Regularization of Mixture Models for Robust Principal Graph Learning

Unsupervised Person Re-identification via Multi-Label Prediction and Classification based on Graph-Structural Insight

Tackling the Challenges in Scene Graph Generation with Local-to-Global Interactions

ECKPN: Explicit Class Knowledge Propagation Network for Transductive Few-shot Learning

Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchmark and Adversarial Graph Learning

Graph cuts always find a global optimum for Potts models (with a catch)

Improving Robustness of Graph Neural Networks with Heterophily-Inspired Designs

Variational Causal Networks: Approximate Bayesian Inference over Causal Structures

PI-GNN: A Novel Perspective on Semi-Supervised Node Classification against Noisy Labels

Recoverability Landscape of Tree Structured Markov Random Fields under Symmetric Noise

Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks

Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation

Federated Myopic Community Detection with One-shot Communication

FeatureNorm: L2 Feature Normalization for Dynamic Graph Embedding

Graph Optimal Transport with Transition Couplings of Random Walks

SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation

Weakly-supervised Graph Meta-learning for Few-shot Node Classification

Integer Programming for Causal Structure Learning in the Presence of Latent Variables

DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object Tracking

Independent Prototype Propagation for Zero-Shot Compositionality

Graph-based Visual-Semantic Entanglement Network for Zero-shot Image Recognition

Possibility results for graph clustering: A novel consistency axiom

GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training

Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs

GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings

Unsupervised Video Person Re-identification via Noise and Hard frame Aware Clustering

Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling

GaitGraph: Graph Convolutional Network for Skeleton-Based Gait Recognition

A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs

Simulating Continuum Mechanics with Multi-Scale Graph Neural Networks

CARPe Posterum: A Convolutional Approach for Real-time Pedestrian Path Prediction

NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs

Interaction-GCN: A Graph Convolutional Network based framework for social interaction recognition in egocentric videos

Isometric Gaussian Process Latent Variable Model for Dissimilarity Data

Balancing Geometry and Density: Path Distances on High-Dimensional Data

Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Tracking

HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation

Increase and Conquer: Training Graph Neural Networks on Growing Graphs

MC2G: An Efficient Algorithm for Matrix Completion with Social and Item Similarity Graphs

Conv-MPN: Convolutional Message Passing Neural Network for Structured Outdoor Architecture Reconstruction

Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence

FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation Mechanism

Multi-Level Graph Encoding with Structural-Collaborative Relation Learning for Skeleton-Based Person Re-Identification

Training Robust Graph Neural Networks with Topology Adaptive Edge Dropping

Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data

GraphMI: Extracting Private Graph Data from Graph Neural Networks

NF-GNN: Network Flow Graph Neural Networks for Malware Detection and Classification

A Deep Local and Global Scene-Graph Matching for Image-Text Retrieval

DeepActsNet: Spatial and Motion features from Face, Hands, and Body Combined with Convolutional and Graph Networks for Improved Action Recognition

Mesh-based graph convolutional neural network models of processes with complex initial states

Equivalence of Dataflow Graphs via Rewrite Rules Using a Graph-to-Sequence Neural Model

Projection-free Graph-based Classifier Learning using Gershgorin Disc Perfect Alignment

Cross-Network Learning with Partially Aligned Graph Convolutional Networks

Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial Learning

Spectral embedding for dynamic networks with stability guarantees

Interpretable Biomanufacturing Process Risk and Sensitivity Analyses for Quality-by-Design and Stability Control

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming

Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions

Causal Discovery in Knowledge Graphs by Exploiting Asymmetric Properties of Non-Gaussian Distributions

FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data

Low Complexity Recruitment for Collaborative Mobile Crowdsourcing Using Graph Neural Networks

Experiments with graph convolutional networks for solving the vertex $p$-center problem

Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction

Grassmannian diffusion maps based dimension reduction and classification for high-dimensional data

An ordinal CNN approach for the assessment of neurological damage in Parkinson's disease patients

Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologies

How effective are Graph Neural Networks in Fraud Detection for Network Data?

CSCAD: Correlation Structure-based Collective Anomaly Detection in Complex System

Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler

Infer-AVAE: An Attribute Inference Model Based on Adversarial Variational Autoencoder

On the Universality of Graph Neural Networks on Large Random Graphs

Linguistic Structures as Weak Supervision for Visual Scene Graph Generation

Relation Matters in Sampling: A Scalable Multi-Relational Graph Neural Network for Drug-Drug Interaction Prediction

2D-3D Geometric Fusion Network using Multi-Neighbourhood Graph Convolution for RGB-D Indoor Scene Classification

Estimating Fund-Raising Performance for Start-up Projects from a Market Graph Perspective

Adversarial Attack Framework on Graph Embedding Models with Limited Knowledge

Incorporating dynamicity of transportation network with multi-weight traffic graph convolutional network for traffic forecasting

Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth

Tab.IAIS: Flexible Table Recognition and Semantic Interpretation System

GCNBoost: Artwork Classification by Label Propagation through a Knowledge Graph

Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding

Heterogeneous Data Fusion Considering Spatial Correlations using Graph Convolutional Networks and its Application in Air Quality Prediction

Position-Sensing Graph Neural Networks: Proactively Learning Nodes Relative Positions

A hybrid classification-regression approach for 3D hand pose estimation using graph convolutional networks

THP: Topological Hawkes Processes for Learning Granger Causality on Event Sequences

Residual Network and Embedding Usage: New Tricks of Node Classification with Graph Convolutional Networks

A Recursive Markov Boundary-Based Approach to Causal Structure Learning

Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty propagation

AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray

EiGLasso for Scalable Sparse Kronecker-Sum Inverse Covariance Estimation

Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM framework

An Attractor-Guided Neural Networks for Skeleton-Based Human Motion Prediction

The World as a Graph: Improving El Niño Forecasts with Graph Neural Networks

Endless Loops: Detecting and Animating Periodic Patterns in Still Images

Free Energy Node Embedding via Generalized Skip-gram with Negative Sampling

Differentiable SLAM-net: Learning Particle SLAM for Visual Navigation

Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning

An efficient scheme based on graph centrality to select nodes for training for effective learning

On Using Classification Datasets to Evaluate Graph-Level Outlier Detection: Peculiar Observations and New Insights

Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks

Sharp threshold for alignment of graph databases with Gaussian weights

Detecting Beneficial Feature Interactions for Recommender Systems

Graph Neural Networks for Knowledge Enhanced Visual Representation of Paintings

Learning-based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching

Node Masking: Making Graph Neural Networks Generalize and Scale Better

Uncertainty in Minimum Cost Multicuts for Image and Motion Segmentation

Neighbourhood-guided Feature Reconstruction for Occluded Person Re-Identification

OpinionRank: Extracting Ground Truth Labels from Unreliable Expert Opinions with Graph-Based Spectral Ranking

Interpretable Drug Synergy Prediction with Graph Neural Networks for Human-AI Collaboration in Healthcare

REGINA - Reasoning Graph Convolutional Networks in Human Action Recognition

VSR: A Unified Framework for Document Layout Analysis combining Vision, Semantics and Relations

Graph Neural Networks for Inconsistent Cluster Detection in Incremental Entity Resolution

Latent Event-Predictive Encodings through Counterfactual Regularization

GLSearch: Maximum Common Subgraph Detection via Learning to Search

Cross-Modal and Multimodal Data Analysis Based on Functional Mapping of Spectral Descriptors and Manifold Regularization

Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear Time

An Empirical Experiment on Deep Learning Models for Predicting Traffic Data

Recurrent Graph Tensor Networks: A Low-Complexity Framework for Modelling High-Dimensional Multi-Way Sequence

Temporal graph-based approach for behavioural entity classification

MetaConcept: Learn to Abstract via Concept Graph for Weakly-Supervised Few-Shot Learning

Accelerating Large Scale Real-Time GNN Inference using Channel Pruning

Supervised Domain Adaptation: A Graph Embedding Perspective and a Rectified Experimental Protocol

Protecting Individual Interests across Clusters: Spectral Clustering with Guarantees

Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs

Learning Graph Representation by Aggregating Subgraphs via Mutual Information Maximization

FedGL: Federated Graph Learning Framework with Global Self-Supervision

More Separable and Easier to Segment: A Cluster Alignment Method for Cross-Domain Semantic Segmentation

An Influence-based Approach for Root Cause Alarm Discovery in Telecom Networks

Neural Graph Matching Network: Learning Lawler's Quadratic Assignment Problem with Extension to Hypergraph and Multiple-graph Matching

Semidefinite Programming for Community Detection with Side Information

Learning Neighborhood Representation from Multi-Modal Multi-Graph: Image, Text, Mobility Graph and Beyond

Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning

An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images

Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion

Learning Graph Embeddings for Open World Compositional Zero-Shot Learning

Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution

Schema-Aware Deep Graph Convolutional Networks for Heterogeneous Graphs

A Comparison of Deep-Learning Methods for Analysing and Predicting Business Processes

Multi-view Clustering with Deep Matrix Factorization and Global Graph Refinement

A Computational Framework for Modeling Complex Sensor Network Data Using Graph Signal Processing and Graph Neural Networks in Structural Health Monitoring

Exploiting Transductive Property of Graph Convolutional Neural Networks with Less Labeling Effort

Bermuda Triangles: GNNs Fail to Detect Simple Topological Structures

Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification

Scalable Semi-supervised Landmark Localization for X-ray Images using Few-shot Deep Adaptive Graph

Bipartite Graph Network with Adaptive Message Passing for Unbiased Scene Graph Generation

Bridge to Answer: Structure-aware Graph Interaction Network for Video Question Answering

Power System Event Identification based on Deep Neural Network with Information Loading

Tail-Net: Extracting Lowest Singular Triplets for Big Data Applications

Reconstructing nodal pressures in water distribution systems with graph neural networks

Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding

Interpretable Embedding Procedure Knowledge Transfer via Stacked Principal Component Analysis and Graph Neural Network

Combinatorial optimization and reasoning with graph neural networks

Building-GAN: Graph-Conditioned Architectural Volumetric Design Generation

Semi-supervised Superpixel-based Multi-Feature Graph Learning for Hyperspectral Image Data

Pose2Mesh: Graph Convolutional Network for 3D Human Pose and Mesh Recovery from a 2D Human Pose

Structure-Aware Hierarchical Graph Pooling using Information Bottleneck

Unsupervised Multi-Source Domain Adaptation for Person Re-Identification

Progressive Spatio-Temporal Graph Convolutional Network for Skeleton-Based Human Action Recognition

Parallel mesh reconstruction streams for pose estimation of interacting hands

LGD-GCN: Local and Global Disentangled Graph Convolutional Networks

Learnable Online Graph Representations for 3D Multi-Object Tracking

Deep learning for detecting bid rigging: Flagging cartel participants based on convolutional neural networks

Efficient Relation-aware Scoring Function Search for Knowledge Graph Embedding

GraphTheta: A Distributed Graph Neural Network Learning System With Flexible Training Strategy

Fast Interactive Video Object Segmentation with Graph Neural Networks

GMLP: Building Scalable and Flexible Graph Neural Networks with Feature-Message Passing

Face-GCN: A Graph Convolutional Network for 3D Dynamic Face Identification/Recognition

Hierarchically Modeling Micro and Macro Behaviors via Multi-Task Learning for Conversion Rate Prediction

Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures

Adversarial Diffusion Attacks on Graph-based Traffic Prediction Models

The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning

Graph-based Thermal-Inertial SLAM with Probabilistic Neural Networks

Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis

GCNNMatch: Graph Convolutional Neural Networks for Multi-Object Tracking via Sinkhorn Normalization

On the Ambiguity of Rank-Based Evaluation of Entity Alignment or Link Prediction Methods

DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks

Segmentation of EM showers for neutrino experiments with deep graph neural networks

Histopathology WSI Encoding based on GCNs for Scalable and Efficient Retrieval of Diagnostically Relevant Regions

NePTuNe: Neural Powered Tucker Network for Knowledge Graph Completion

Spatial-Temporal Correlation and Topology Learning for Person Re-Identification in Videos

Structure-Enhanced Meta-Learning For Few-Shot Graph Classification

A Tunable Model for Graph Generation Using LSTM and Conditional VAE

Harmonious Semantic Line Detection via Maximal Weight Clique Selection

Geometric graphs from data to aid classification tasks with graph convolutional networks

FastGAE: Scalable Graph Autoencoders with Stochastic Subgraph Decoding

Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification

Visual Camera Re-Localization Using Graph Neural Networks and Relative Pose Supervision

Learning Chebyshev Basis in Graph Convolutional Networks for Skeleton-based Action Recognition

Optimizing Memory Efficiency of Graph Neural Networks on Edge Computing Platforms

Towards Fundamental Limits of Multi-armed Bandits with Random Walk Feedback

Auto-weighted Multi-view Feature Selection with Graph Optimization

Skeleton-based Hand-Gesture Recognition with Lightweight Graph Convolutional Networks

FL-AGCNS: Federated Learning Framework for Automatic Graph Convolutional Network Search

RTIC: Residual Learning for Text and Image Composition using Graph Convolutional Network

GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference

Multi-point dimensionality reduction to improve projection layout reliability

Automated freezing of gait assessment with marker-based motion capture and multi-stage graph convolutional neural networks approaches expert-level detection

Few-Shot Incremental Learning with Continually Evolved Classifiers

Graph-based Normalizing Flow for Human Motion Generation and Reconstruction

Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels

Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos

gradSim: Differentiable simulation for system identification and visuomotor control

Structured Citation Trend Prediction Using Graph Neural Networks

Learning Spatial Context with Graph Neural Network for Multi-Person Pose Grouping

Spatio-Temporal Graph Convolutional Networks for Road Network Inundation Status Prediction during Urban Flooding

Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs

Label-GCN: An Effective Method for Adding Label Propagation to Graph Convolutional Networks

Analyzing the Performance of Graph Neural Networks with Pipe Parallelism

Non-Homogeneous Haze Removal via Artificial Scene Prior and Bidimensional Graph Reasoning

Improving the Expressive Power of Graph Neural Network with Tinhofer Algorithm

Predicting Mergers and Acquisitions using Graph-based Deep Learning

STOPPAGE: Spatio-temporal Data Driven Cloud-Fog-Edge Computing Framework for Pandemic Monitoring and Management

Decentralized Statistical Inference with Unrolled Graph Neural Networks

SGCN:Sparse Graph Convolution Network for Pedestrian Trajectory Prediction

PTP: Parallelized Tracking and Prediction with Graph Neural Networks and Diversity Sampling

Joint Geometric and Topological Analysis of Hierarchical Datasets

Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts

Weakly-Supervised Image Semantic Segmentation Using Graph Convolutional Networks

PTN: A Poisson Transfer Network for Semi-supervised Few-shot Learning

Graph-Based Intercategory and Intermodality Network for Multilabel Classification and Melanoma Diagnosis of Skin Lesions in Dermoscopy and Clinical Images

High-Dimensional Bayesian Optimization with Multi-Task Learning for RocksDB

When Segmentation is Not Enough: Rectifying Visual-Volume Discordance Through Multisensor Depth-Refined Semantic Segmentation for Food Intake Tracking in Long-Term Care

Joint Deep Multi-Graph Matching and 3D Geometry Learning from Inhomogeneous 2D Image Collections

SOON: Scenario Oriented Object Navigation with Graph-based Exploration

Towards Better Graph Representation: Two-Branch Collaborative Graph Neural Networks for Multimodal Marketing Intention Detection

ModGNN: Expert Policy Approximation in Multi-Agent Systems with a Modular Graph Neural Network Architecture

Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning

Nonlinear Weighted Directed Acyclic Graph and A Priori Estimates for Neural Networks

SSFG: Stochastically Scaling Features and Gradients for Regularizing Graph Convolutional Networks

clDice -- a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation

Learnable Graph Matching: Incorporating Graph Partitioning with Deep Feature Learning for Multiple Object Tracking

Graph Intention Network for Click-through Rate Prediction in Sponsored Search

Video Self-Stitching Graph Network for Temporal Action Localization

Bringing UMAP Closer to the Speed of Light with GPU Acceleration

Tight Integration of Feature-based Relocalization in Monocular Direct Visual Odometry

Tackling Over-Smoothing for General Graph Convolutional Networks

Learning Differentiable Programs with Admissible Neural Heuristics

Temporally-Weighted Hierarchical Clustering for Unsupervised Action Segmentation

Hybrid Rotation Averaging: A Fast and Robust Rotation Averaging Approach

A nonlinear diffusion method for semi-supervised learning on hypergraphs

Dual Geometric Graph Network (DG2N) -- Iterative network for deformable shape alignment

Structure-Aware Face Clustering on a Large-Scale Graph with $\bf{10^{7}}$ Nodes

Non-Salient Region Object Mining for Weakly Supervised Semantic Segmentation

GeoSP: A parallel method for a cortical surface parcellation based on geodesic distance

Spatial Dual-Modality Graph Reasoning for Key Information Extraction

FRITL: A Hybrid Method for Causal Discovery in the Presence of Latent Confounders

Self-Labeling of Fully Mediating Representations by Graph Alignment

Regularized Optimal Transport for Dynamic Semi-supervised Learning

GPRAR: Graph Convolutional Network based Pose Reconstruction and Action Recognition for Human Trajectory Prediction

Graph-SIM: A Graph-based Spatiotemporal Interaction Modelling for Pedestrian Action Prediction

Spatial-spectral Hyperspectral Image Classification via Multiple Random Anchor Graphs Ensemble Learning

SketchGNN: Semantic Sketch Segmentation with Graph Neural Networks

Multi-view Subspace Clustering Networks with Local and Global Graph Information

Learning Fine-Grained Segmentation of 3D Shapes without Part Labels

Bandit Learning for Dynamic Colonel Blotto Game with a Budget Constraint

ROBIN: a Graph-Theoretic Approach to Reject Outliers in Robust Estimation using Invariants

Applying graph matching techniques to enhance reuse of plant design information

DualConv: Dual Mesh Convolutional Networks for Shape Correspondence

Distance-Geometric Graph Convolutional Network (DG-GCN) for Three-Dimensional (3D) Graphs

Learning physical properties of anomalous random walks using graph neural networks

Deepened Graph Auto-Encoders Help Stabilize and Enhance Link Prediction

ERNIE-ViL: Knowledge Enhanced Vision-Language Representations Through Scene Graph

Point-supervised Segmentation of Microscopy Images and Volumes via Objectness Regularization

A Unified Framework of Constrained Robust Submodular Optimization with Applications

Optimal Gradient Checkpoint Search for Arbitrary Computation Graphs

Diversified Multiscale Graph Learning with Graph Self-Correction

Context-Aware Graph Convolution Network for Target Re-identification

Pose-GNN : Camera Pose Estimation System Using Graph Neural Networks

Efficient Bayesian Optimization using Multiscale Graph Correlation

GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks

AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models

3DCaricShop: A Dataset and A Baseline Method for Single-view 3D Caricature Face Reconstruction

BreakingBED -- Breaking Binary and Efficient Deep Neural Networks by Adversarial Attacks

Ensemble Learning with Manifold-Based Data Splitting for Noisy Label Correction

On the Equivalence Between Temporal and Static Graph Representations for Observational Predictions

Sim2Real 3D Object Classification using Spherical Kernel Point Convolution and a Deep Center Voting Scheme

Spatial-Temporal Tensor Graph Convolutional Network for Traffic Prediction

GraphTCN: Spatio-Temporal Interaction Modeling for Human Trajectory Prediction

Probabilistic Modeling of Semantic Ambiguity for Scene Graph Generation

Optimistic Policy Iteration for MDPs with Acyclic Transient State Structure

On the Bottleneck of Graph Neural Networks and its Practical Implications

Multi-view Sensor Fusion by Integrating Model-based Estimation and Graph Learning for Collaborative Object Localization

Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting

On the Impact of Communities on Semi-supervised Classification Using Graph Neural Networks

Data-Driven Short-Term Voltage Stability Assessment Based on Spatial-Temporal Graph Convolutional Network

Foundations of Population-Based SHM, Part IV: The Geometry of Spaces of Structures and their Feature Spaces

Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs

Artificial Neural Networks generated by Low Discrepancy Sequences

Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs

ByzShield: An Efficient and Robust System for Distributed Training

Learning Asynchronous and Sparse Human-Object Interaction in Videos

On the Importance of Sampling in Learning Graph Convolutional Networks

How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks

A Matrix Factorization Model for Hellinger-based Trust Management in Social Internet of Things

Submodular Combinatorial Information Measures with Applications in Machine Learning

Connecting Graph Convolutional Networks and Graph-Regularized PCA

Road Network and Travel Time Extraction from Multiple Look Angles with SpaceNet Data

Financial Crime & Fraud Detection Using Graph Computing: Application Considerations & Outlook

FinMatcher at FinSim-2: Hypernym Detection in the Financial Services Domain using Knowledge Graphs

Kernel-Based Models for Influence Maximization on Graphs based on Gaussian Process Variance Minimization

ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations

Snowflake: Scaling GNNs to High-Dimensional Continuous Control via Parameter Freezing

Partitioned Graph Convolution Using Adversarial and Regression Networks for Road Travel Speed Prediction

Predicting Livelihood Indicators from Community-Generated Street-Level Imagery

Detection of Alzheimer's Disease Using Graph-Regularized Convolutional Neural Network Based on Structural Similarity Learning of Brain Magnetic Resonance Images

Mixed Variable Bayesian Optimization with Frequency Modulated Kernels

Spanning Tree Constrained Determinantal Point Processes are Hard to (Approximately) Evaluate

Multi-Level Adaptive Region of Interest and Graph Learning for Facial Action Unit Recognition

A Simulation-Based Test of Identifiability for Bayesian Causal Inference

In-game Residential Home Planning via Visual Context-aware Global Relation Learning

Few-shot Network Anomaly Detection via Cross-network Meta-learning

GLAM: Graph Learning by Modeling Affinity to Labeled Nodes for Graph Neural Networks

Unavailable Transit Feed Specification: Making it Available with Recurrent Neural Networks

Generalization bounds for graph convolutional neural networks via Rademacher complexity

BayGo: Joint Bayesian Learning and Information-Aware Graph Optimization

Supporting Financial Inclusion with Graph Machine Learning and Super-App Alternative Data

Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory

Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels

Bridging Graph Neural Networks and Statistical Relational Learning: Relational One-Class GCN

On the Stability of Graph Convolutional Neural Networks under Edge Rewiring

On the Fundamental Limits of Exact Inference in Structured Prediction

Markov Random Geometric Graph (MRGG): A Growth Model for Temporal Dynamic Networks

NODE-SELECT: A Graph Neural Network Based On A Selective Propagation Technique

Semi-Supervised Speech Recognition via Graph-based Temporal Classification

A Multiscale Graph Convolutional Network for Change Detection in Homogeneous and Heterogeneous Remote Sensing Images

Structured Graph Learning for Scalable Subspace Clustering: From Single-view to Multi-view

KNH: Multi-View Modeling with K-Nearest Hyperplanes Graph for Misinformation Detection

Distributed Online Learning for Joint Regret with Communication Constraints

Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs

Sparse-Push: Communication- & Energy-Efficient Decentralized Distributed Learning over Directed & Time-Varying Graphs with non-IID Datasets

SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks

Semi-Supervised Few-Shot Learning with Prototypical Random Walks

Dynamic Emotion Modeling with Learnable Graphs and Graph Inception Network

EigenGame Unloaded: When playing games is better than optimizing

Ising Model Selection Using $\ell_{1}$-Regularized Linear Regression

A Graph Convolutional Topic Model for Short and Noisy Text Streams

Scalable Robust Graph and Feature Extraction for Arbitrary Vessel Networks in Large Volumetric Datasets

A Deep Learning Approach Based on Graphs to Detect Plantation Lines

Commonsense Knowledge Aware Concept Selection For Diverse and Informative Visual Storytelling

Isometric Propagation Network for Generalized Zero-shot Learning

A Technique for Determining Relevance Scores of Process Activities using Graph-based Neural Networks

A General Pairwise Comparison Model for Extremely Sparse Networks

Symmetric Boolean Factor Analysis with Applications to InstaHide

Leveraging Activity Recognition to Enable Protective Behavior Detection in Continuous Data

Consensus-Aware Visual-Semantic Embedding for Image-Text Matching

Cross Chest Graph for Disease Diagnosis with Structural Relational Reasoning

Forecasting Action through Contact Representations from First Person Video

Graph Neural Networks to Predict Customer Satisfaction Following Interactions with a Corporate Call Center

LABNet: Local Graph Aggregation Network with Class Balanced Loss for Vehicle Re-Identification

Scalable Spectral Clustering with Nystrom Approximation: Practical and Theoretical Aspects

A Unifying Generative Model for Graph Learning Algorithms: Label Propagation, Graph Convolutions, and Combinations

Learning continuous-time PDEs from sparse data with graph neural networks

Detecting Malicious Accounts in Permissionless Blockchains using Temporal Graph Properties

Graph-based Interpolation of Feature Vectors for Accurate Few-Shot Classification

Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search

Edge-Labeling based Directed Gated Graph Network for Few-shot Learning

Im2Mesh GAN: Accurate 3D Hand Mesh Recovery from a Single RGB Image

Quantifying the Alignment of Graph and Features in Deep Learning

End-to-End Learning from Complex Multigraphs with Latent-Graph Convolutional Networks

Neural Relational Inference with Efficient Message Passing Mechanisms

Class-incremental Learning with Rectified Feature-Graph Preservation

Hierarchical Graph-RNNs for Action Detection of Multiple Activities

Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback

Where are the Keys? -- Learning Object-Centric Navigation Policies on Semantic Maps with Graph Convolutional Networks

Progressive Graph Convolutional Networks for Semi-Supervised Node Classification

PyTorch-Direct: Enabling GPU Centric Data Access for Very Large Graph Neural Network Training with Irregular Accesses

Scalable Optimization for Wind Farm Control using Coordination Graphs

Communication-Efficient Sampling for Distributed Training of Graph Convolutional Networks

Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network

Pose Refinement Graph Convolutional Network for Skeleton-based Action Recognition

Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters

Interpreting Knowledge Graph Relation Representation from Word Embeddings

Ordinal Pattern Kernel for Brain Connectivity Network Classification

Heterogeneous Similarity Graph Neural Network on Electronic Health Records

LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting

Understanding the Role of Scene Graphs in Visual Question Answering

GridTracer: Automatic Mapping of Power Grids using Deep Learning and Overhead Imagery

EAGER: Embedding-Assisted Entity Resolution for Knowledge Graphs

Label Contrastive Coding based Graph Neural Network for Graph Classification

Relation-aware Meta-learning for Market Segment Demand Prediction with Limited Records

HighAir: A Hierarchical Graph Neural Network-Based Air Quality Forecasting Method

Understanding the Message Passing in Graph Neural Networks via Power Iteration Clustering

Deep Diffusion Processes for Active Learning of Hyperspectral Images

ADiag: Graph Neural Network Based Diagnosis of Alzheimer's Disease

Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting

Bayesian Inference of Random Dot Product Graphs via Conic Programming

Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks

TGCN: Time Domain Graph Convolutional Network for Multiple Objects Tracking

Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks

An extension of the angular synchronization problem to the heterogeneous setting

TensorX: Extensible API for Neural Network Model Design and Deployment

Flexible model composition in machine learning and its implementation in MLJ

Image-to-Image Retrieval by Learning Similarity between Scene Graphs

COIN: Contrastive Identifier Network for Breast Mass Diagnosis in Mammography

Spectral Clustering with Graph Neural Networks for Graph Pooling

MS-GWNN:multi-scale graph wavelet neural network for breast cancer diagnosis

Understanding Image Retrieval Re-Ranking: A Graph Neural Network Perspective

Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications

LookHops: light multi-order convolution and pooling for graph classification

Action Recognition with Kernel-based Graph Convolutional Networks

Deep Graph Normalizer: A Geometric Deep Learning Approach for Estimating Connectional Brain Templates

Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records

Adaptive Graph-based Generalized Regression Model for Unsupervised Feature Selection

Renormalized Normalized Maximum Likelihood and Three-Part Code Criteria For Learning Gaussian Networks

A Graph Convolutional Network with Signal Phasing Information for Arterial Traffic Prediction

High-Dimensional Bayesian Optimization via Tree-Structured Additive Models

Multi-grained Trajectory Graph Convolutional Networks for Habit-unrelated Human Motion Prediction

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Self-Growing Spatial Graph Network for Context-Aware Pedestrian Trajectory Prediction

Unsupervised Ensemble Classification with Sequential and Networked Data

Semi-supervised Hyperspectral Image Classification with Graph Clustering Convolutional Networks

Suspicious Massive Registration Detection via Dynamic Heterogeneous Graph Neural Networks

Towards Coarse and Fine-grained Multi-Graph Multi-Label Learning

A pipeline for fair comparison of graph neural networks in node classification tasks

LIGHTEN: Learning Interactions with Graph and Hierarchical TEmporal Networks for HOI in videos

Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design

On the Convergence of Continuous Constrained Optimization for Structure Learning

AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity

A Deep Graph Neural Networks Architecture Design: From Global Pyramid-like Shrinkage Skeleton to Local Topology Link Rewiring

Edge Entropy as an Indicator of the Effectiveness of GNNs over CNNs for Node Classification

Product Graph Learning from Multi-domain Data with Sparsity and Rank Constraints

Coupled Layer-wise Graph Convolution for Transportation Demand Prediction

Decentralized SGD with Asynchronous, Local and Quantized Updates

Mercer Features for Efficient Combinatorial Bayesian Optimization

A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks

Temporal Relational Modeling with Self-Supervision for Action Segmentation

Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework

Knowledge-Routed Visual Question Reasoning: Challenges for Deep Representation Embedding

Iterative Knowledge Exchange Between Deep Learning and Space-Time Spectral Clustering for Unsupervised Segmentation in Videos

Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment

Towards Precise Intra-camera Supervised Person Re-identification

Scalable and interpretable rule-based link prediction for large heterogeneous knowledge graphs

Learning event representations for temporal segmentation of image sequences by dynamic graph embedding

Spatiotemporal Graph Neural Network based Mask Reconstruction for Video Object Segmentation

Uncertainty Intervals for Graph-based Spatio-Temporal Traffic Prediction

Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder

Distributed Training of Graph Convolutional Networks using Subgraph Approximation

JointsGait:A model-based Gait Recognition Method based on Gait Graph Convolutional Networks and Joints Relationship Pyramid Mapping

Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks

GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs

Learning Video Instance Segmentation with Recurrent Graph Neural Networks

LCS Graph Kernel Based on Wasserstein Distance in Longest Common Subsequence Metric Space

Semi-supervised Soil Moisture Prediction through Graph Neural Networks

Learning Graph Neural Networks with Approximate Gradient Descent

Graph Convolutional Networks for Graphs Containing Missing Features

Counting Substructures with Higher-Order Graph Neural Networks: Possibility and Impossibility Results

Traffic4cast 2020 -- Graph Ensemble Net and the Importance of Feature And Loss Function Design for Traffic Prediction

A Multi-Task Learning Approach for Human Activity Segmentation and Ergonomics Risk Assessment

Demographic Influences on Contemporary Art with Unsupervised Style Embeddings

Decentralized Multi-Agent Linear Bandits with Safety Constraints

Combinatorial Learning of Graph Edit Distance via Dynamic Embedding

Semi-Supervised Regression using Cluster Ensemble and Low-Rank Co-Association Matrix Decomposition under Uncertainties

HydroNet: Benchmark Tasks for Preserving Intermolecular Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data

SFTrack++: A Fast Learnable Spectral Segmentation Approach for Space-Time Consistent Tracking

TSSRGCN: Temporal Spectral Spatial Retrieval Graph Convolutional Network for Traffic Flow Forecasting

Conditional Link Prediction of Category-Implicit Keypoint Detection

Curvature Regularization to Prevent Distortion in Graph Embedding

Every Corporation Owns Its Structure: Corporate Credit Ratings via Graph Neural Networks

Predictive Collision Management for Time and Risk Dependent Path Planning

KST-GCN: A Knowledge-Driven Spatial-Temporal Graph Convolutional Network for Traffic Forecasting

Autonomous Graph Mining Algorithm Search with Best Speed/Accuracy Trade-off

Richly Activated Graph Convolutional Network for Robust Skeleton-based Action Recognition

Ranking Deep Learning Generalization using Label Variation in Latent Geometry Graphs

Consistency-aware and Inconsistency-aware Graph-based Multi-view Clustering

Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS

Online Domain Adaptation for Continuous Cross-Subject Liver Viability Evaluation Based on Irregular Thermal Data

Trust but Verify: Assigning Prediction Credibility by Counterfactual Constrained Learning

Who killed Lilly Kane? A case study in applying knowledge graphs to crime fiction

AST-GCN: Attribute-Augmented Spatiotemporal Graph Convolutional Network for Traffic Forecasting

Double Self-weighted Multi-view Clustering via Adaptive View Fusion

A Cognitive Approach based on the Actionable Knowledge Graph for supporting Maintenance Operations

GRAPHSPY: Fused Program Semantic-Level Embedding via Graph Neural Networks for Dead Store Detection

Res-GCNN: A Lightweight Residual Graph Convolutional Neural Networks for Human Trajectory Forecasting

Discovering Symbolic Models from Deep Learning with Inductive Biases

RAIST: Learning Risk Aware Traffic Interactions via Spatio-Temporal Graph Convolutional Networks

MG-GCN: Fast and Effective Learning with Mix-grained Aggregators for Training Large Graph Convolutional Networks

Training highly effective connectivities within neural networks with randomly initialized, fixed weights

Distributed Bandits: Probabilistic Communication on $d$-regular Graphs

Semi-Supervised Node Classification by Graph Convolutional Networks and Extracted Side Information

Learning to Drop: Robust Graph Neural Network via Topological Denoising

Biomedical Information Extraction for Disease Gene Prioritization

New and Explicit Constructions of Unbalanced Ramanujan Bipartite Graphs

Rediscovering alignment relations with Graph Convolutional Networks

GRCNN: Graph Recognition Convolutional Neural Network for Synthesizing Programs from Flow Charts

Semi-supervised Sparse Representation with Graph Regularization for Image Classification

Joint predictions of multi-modal ride-hailing demands: a deep multi-task multigraph learning-based approach

Adaptive Local Structure Consistency based Heterogeneous Remote Sensing Change Detection

Node Attribute Completion in Knowledge Graphs with Multi-Relational Propagation

Statistical learning for change point and anomaly detection in graphs

After All, Only The Last Neuron Matters: Comparing Multi-modal Fusion Functions for Scene Graph Generation

Dual regularized Laplacian spectral clustering methods on community detection

Robustness of Community Detection to Random Geometric Perturbations

A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding

Learning Continuous System Dynamics from Irregularly-Sampled Partial Observations

FusedMM: A Unified SDDMM-SpMM Kernel for Graph Embedding and Graph Neural Networks

Learning Power Control for Cellular Systems with Heterogeneous Graph Neural Network

EnsemFDet: An Ensemble Approach to Fraud Detection based on Bipartite Graph

A Bregman Method for Structure Learning on Sparse Directed Acyclic Graphs

Causal discovery of linear non-Gaussian acyclic models in the presence of latent confounders

Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based Visual Question Answering

Sampling and Recovery of Graph Signals based on Graph Neural Networks

Combining Label Propagation and Simple Models Out-performs Graph Neural Networks

BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search

Anti-perturbation of Online Social Networks by Graph Label Transition

Dark Reciprocal-Rank: Boosting Graph-Convolutional Self-Localization Network via Teacher-to-student Knowledge Transfer

Integer Programming-based Error-Correcting Output Code Design for Robust Classification

Nonnegative Spectral Analysis with Adaptive Graph and $L_{2,0}$-Norm Regularization for Unsupervised Feature Selection

Efficient Algorithms for Device Placement of DNN Graph Operators

Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction

Structural Causal Model with Expert Augmented Knowledge to Estimate the Effect of Oxygen Therapy on Mortality in the ICU

GNNGuard: Defending Graph Neural Networks against Adversarial Attacks

Robust Skeletonization for Plant Root Structure Reconstruction from MRI

A Method of Generating Measurable Panoramic Image for Indoor Mobile Measurement System

Processing of incomplete images by (graph) convolutional neural networks

Quadratic Decomposable Submodular Function Minimization: Theory and Practice (Computation and Analysis of PageRank over Hypergraphs)

Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer Proxies

Video-based Facial Expression Recognition using Graph Convolutional Networks

Semi supervised segmentation and graph-based tracking of 3D nuclei in time-lapse microscopy

Discriminatively Constrained Semi-supervised Multi-view Nonnegative Matrix Factorization with Graph Regularization

Revisiting convolutional neural network on graphs with polynomial approximations of Laplace-Beltrami spectral filtering

Relative concentration bounds for the spectrum of kernel matrices

VICTR: Visual Information Captured Text Representation for Text-to-Image Multimodal Tasks

Robust Multi-object Matching via Iterative Reweighting of the Graph Connection Laplacian

Road Accident Proneness Indicator Based On Time, Weather And Location Specificity Using Graph Neural Networks

Wide and Deep Graph Neural Networks with Distributed Online Learning

Towards More Practical Adversarial Attacks on Graph Neural Networks

Low-rank on Graphs plus Temporally Smooth Sparse Decomposition for Anomaly Detection in Spatiotemporal Data

Building powerful and equivariant graph neural networks with structural message-passing

Algorithmic recourse under imperfect causal knowledge: a probabilistic approach

Graph-Homomorphic Perturbations for Private Decentralized Learning

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs

Adversarial Crowdsourcing Through Robust Rank-One Matrix Completion

Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings

Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing

Push-SAGA: A decentralized stochastic algorithm with variance reduction over directed graphs

EvolveGraph: Multi-Agent Trajectory Prediction with Dynamic Relational Reasoning

Visual link retrieval and knowledge discovery in painting datasets

Cell Segmentation and Tracking using CNN-Based Distance Predictions and a Graph-Based Matching Strategy

Network topology change-point detection from graph signals with prior spectral signatures

3D Meta Point Signature: Learning to Learn 3D Point Signature for 3D Dense Shape Correspondence

Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels

Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings

Graphon Neural Networks and the Transferability of Graph Neural Networks

Anisotropic Graph Convolutional Network for Semi-supervised Learning

Identification of deep breath while moving forward based on multiple body regions and graph signal analysis

Multipole Graph Neural Operator for Parametric Partial Differential Equations

Neural Architecture Performance Prediction Using Graph Neural Networks

Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization

Motif Learning in Knowledge Graphs Using Trajectories Of Differential Equations

Deep Generative Modeling in Network Science with Applications to Public Policy Research

Generalizable Machine Learning in Neuroscience using Graph Neural Networks

Predicting Biomedical Interactions with Higher-Order Graph Convolutional Networks

Node Embeddings and Exact Low-Rank Representations of Complex Networks

Kernelized Multiview Subspace Analysis by Self-weighted Learning

DocStruct: A Multimodal Method to Extract Hierarchy Structure in Document for General Form Understanding

Multi-label Few/Zero-shot Learning with Knowledge Aggregated from Multiple Label Graphs

Map-Based Temporally Consistent Geolocalization through Learning Motion Trajectories

Dense Relational Image Captioning via Multi-task Triple-Stream Networks

Webly Supervised Image Classification with Metadata: Automatic Noisy Label Correction via Visual-Semantic Graph

Speed-up and multi-view extensions to Subclass Discriminant Analysis

Scene Gated Social Graph: Pedestrian Trajectory Prediction Based on Dynamic Social Graphs and Scene Constraints

Graph Pattern Mining and Learning through User-defined Relations (Extended Version)

Improve the Robustness and Accuracy of Deep Neural Network with $L_{2,\infty}$ Normalization

Conformal retrofitting via Riemannian manifolds: distilling task-specific graphs into pretrained embeddings

Unsupervised Joint $k$-node Graph Representations with Compositional Energy-Based Models

TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion

Fast Mesh Data Augmentation via Chebyshev Polynomial of Spectral filtering

Weakly Supervised-Based Oversampling for High Imbalance and High Dimensionality Data Classification

Accurate, Efficient and Scalable Training of Graph Neural Networks

Predictive Coding Approximates Backprop along Arbitrary Computation Graphs

Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score

Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk Estimation

Monocular Rotational Odometry with Incremental Rotation Averaging and Loop Closure

${\rm N{\small ode}S{\small ig}}$: Random Walk Diffusion meets Hashing for Scalable Graph Embeddings

A general approach for identifying hierarchical symmetry constraints for analog circuit layout

StratLearner: Learning a Strategy for Misinformation Prevention in Social Networks

A local geometry of hyperedges in hypergraphs, and its applications to social networks

FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems

Framework for Designing Filters of Spectral Graph Convolutional Neural Networks in the Context of Regularization Theory

Fast and Incremental Loop Closure Detection with Deep Features and Proximity Graphs

A new network-base high-level data classification methodology (Quipus) by modeling attribute-attribute interactions

Interaction-Based Trajectory Prediction Over a Hybrid Traffic Graph

SIA-GCN: A Spatial Information Aware Graph Neural Network with 2D Convolutions for Hand Pose Estimation

Revisiting Graph Convolutional Network on Semi-Supervised Node Classification from an Optimization Perspective

PK-GCN: Prior Knowledge Assisted Image Classification using Graph Convolution Networks

InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions

Multi-View Brain HyperConnectome AutoEncoder For Brain State Classification

Multi-Scale Profiling of Brain Multigraphs by Eigen-based Cross-Diffusion and Heat Tracing for Brain State Profiling

Supervised Multi-topology Network Cross-diffusion for Population-driven Brain Network Atlas Estimation

Spatial-Temporal Block and LSTM Network for Pedestrian Trajectories Prediction

Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition

Simultaneous Dimensionality and Complexity Model Selection for Spectral Graph Clustering

SAMOT: Switcher-Aware Multi-Object Tracking and Still Another MOT Measure

On the Equivalence between Positional Node Embeddings and Structural Graph Representations

Graph Based Multi-layer K-means++ (G-MLKM) for Sensory Pattern Analysis in Constrained Spaces

Multi-Modal Reasoning Graph for Scene-Text Based Fine-Grained Image Classification and Retrieval

Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition

Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning

Multi-Resolution Graph Neural Network for Large-Scale Pointcloud Segmentation

Spatio-Temporal Hybrid Graph Convolutional Network for Traffic Forecasting in Telecommunication Networks

CatGCN: Graph Convolutional Networks with Categorical Node Features

Image Retrieval for Structure-from-Motion via Graph Convolutional Network

Captum: A unified and generic model interpretability library for PyTorch

Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Networks

Graph Convolution Networks Using Message Passing and Multi-Source Similarity Features for Predicting circRNA-Disease Association

HGCN-GJS: Hierarchical Graph Convolutional Network with Groupwise Joint Sampling for Trajectory Prediction

New complex network building methodology for High Level Classification based on attribute-attribute interaction

Relational Fusion Networks: Graph Convolutional Networks for Road Networks

Prior Knowledge about Attributes: Learning a More Effective Potential Space for Zero-Shot Recognition

Semi-supervised dictionary learning with graph regularization and active points

Certified Robustness of Graph Classification against Topology Attack with Randomized Smoothing

Exploring the Hierarchy in Relation Labels for Scene Graph Generation

Learning semantic Image attributes using Image recognition and knowledge graph embeddings

Superpixel Based Graph Laplacian Regularization for Sparse Hyperspectral Unmixing

Deep Modeling of Growth Trajectories for Longitudinal Prediction of Missing Infant Cortical Surfaces

Learning an Interpretable Graph Structure in Multi-Task Learning

Towards Interpretable Multi-Task Learning Using Bilevel Programming

Large-scale empirical validation of Bayesian Network structure learning algorithms with noisy data

Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks

NPENAS: Neural Predictor Guided Evolution for Neural Architecture Search

Walk Extraction Strategies for Node Embeddings with RDF2Vec in Knowledge Graphs

Visual Object Tracking by Segmentation with Graph Convolutional Network

Estimation of Structural Causal Model via Sparsely Mixing Independent Component Analysis

Frontier Detection and Reachability Analysis for Efficient 2D Graph-SLAM Based Active Exploration

Zero-Shot Human-Object Interaction Recognition via Affordance Graphs

Evaluating structure learning algorithms with a balanced scoring function

PCPL: Predicate-Correlation Perception Learning for Unbiased Scene Graph Generation

Online system identification in a Duffing oscillator by free energy minimisation

Boosting House Price Predictions using Geo-Spatial Network Embedding

Structured Graph Learning for Clustering and Semi-supervised Classification

Deep Relational Reasoning Graph Network for Arbitrary Shape Text Detection

Loss convergence in a causal Bayesian neural network of retail firm performance

Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network

Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More

On segmentation of pectoralis muscle in digital mammograms by means of deep learning

Dynamic Graph Neural Network for Traffic Forecasting in Wide Area Networks

A Consistent Diffusion-Based Algorithm for Semi-Supervised Classification on Graphs

Webly Supervised Image Classification with Self-Contained Confidence

A Variational-Sequential Graph Autoencoder for Neural Architecture Performance Prediction

Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks

Graph convolutional networks for learning with few clean and many noisy labels

Graph Domain Adaptation with Localized Graph Signal Representations

Good Graph to Optimize: Cost-Effective, Budget-Aware Bundle Adjustment in Visual SLAM

Unsupervised Multi-view Clustering by Squeezing Hybrid Knowledge from Cross View and Each View

Few-Shot Image Classification via Contrastive Self-Supervised Learning

Unsupervised Deep Metric Learning via Orthogonality based Probabilistic Loss

Optimization of Graph Neural Networks with Natural Gradient Descent

Differentiable TAN Structure Learning for Bayesian Network Classifiers

Learning Domain-invariant Graph for Adaptive Semi-supervised Domain Adaptation with Few Labeled Source Samples

ImagiFilter: A resource to enable the semi-automatic mining of images at scale

Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks

A direct approach for function approximation on data defined manifolds

Rehabilitating Isomap: Euclidean Representation of Geodesic Structure

Generating Adjacency Matrix for Video-Query based Video Moment Retrieval

Instance-Aware Graph Convolutional Network for Multi-Label Classification

Scalable Combinatorial Bayesian Optimization with Tractable Statistical models

Tackling the Unannotated: Scene Graph Generation with Bias-Reduced Models

Bayesian network structure learning with causal effects in the presence of latent variables

Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation

Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction

TempNodeEmb:Temporal Node Embedding considering temporal edge influence matrix

Trajectory Grouping with Curvature Regularization for Tubular Structure Tracking

Peer-inspired Student Performance Prediction in Interactive Online Question Pools with Graph Neural Network

Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates

Towards Generalizable Surgical Activity Recognition Using Spatial Temporal Graph Convolutional Networks

Investigating and Mitigating Degree-Related Biases in Graph Convolutional Networks

Lifelong Property Price Prediction: A Case Study for the Toronto Real Estate Market

Online Graph Completion: Multivariate Signal Recovery in Computer Vision

Asymptotic Convergence Rate of Alternating Minimization for Rank One Matrix Completion

A boosted outlier detection method based on the spectrum of the Laplacian matrix of a graph

Depth image denoising using nuclear norm and learning graph model

Fractal Gaussian Networks: A sparse random graph model based on Gaussian Multiplicative Chaos

Zero-Shot Multi-View Indoor Localization via Graph Location Networks

Group Activity Prediction with Sequential Relational Anticipation Model

GAR: An efficient and scalable Graph-based Activity Regularization for semi-supervised learning

Pose-based Modular Network for Human-Object Interaction Detection

Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers

Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition

Boundary Content Graph Neural Network for Temporal Action Proposal Generation

Stochastic Bundle Adjustment for Efficient and Scalable 3D Reconstruction

Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning

Improving Skeleton-based Action Recognitionwith Robust Spatial and Temporal Features

VisualCOMET: Reasoning about the Dynamic Context of a Still Image

Adversarial Bipartite Graph Learning for Video Domain Adaptation

Multi-label Zero-shot Classification by Learning to Transfer from External Knowledge

Dynamic Character Graph via Online Face Clustering for Movie Analysis

Solving Partial Assignment Problems using Random Clique Complexes

Simplicial Complex based Point Correspondence between Images warped onto Manifolds

Learning Representations using Spectral-Biased Random Walks on Graphs

Dynamic GCN: Context-enriched Topology Learning for Skeleton-based Action Recognition

A SLAM Map Restoration Algorithm Based on Submaps and an Undirected Connected Graph

Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation

Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation

Rich-Item Recommendations for Rich-Users: Exploiting Dynamic and Static Side Information

Bridging Visual Perception with Contextual Semantics for Understanding Robot Manipulation Tasks

A Partially Observable MDP Approach for Sequential Testing for Infectious Diseases such as COVID-19

Genome Sequence Classification for Animal Diagnostics with Graph Representations and Deep Neural Networks

Structured Landmark Detection via Topology-Adapting Deep Graph Learning

Implicit Latent Variable Model for Scene-Consistent Motion Forecasting

Differentiable Hierarchical Graph Grouping for Multi-Person Pose Estimation

S-ADDOPT: Decentralized stochastic first-order optimization over directed graphs

Answering Questions about Data Visualizations using Efficient Bimodal Fusion

Supervised learning on heterogeneous, attributed entities interacting over time

Time-aware Graph Embedding: A temporal smoothness and task-oriented approach

Efficient Graph-Based Active Learning with Probit Likelihood via Gaussian Approximations

GREEN: a Graph REsidual rE-ranking Network for Grading Diabetic Retinopathy

Graph-PCNN: Two Stage Human Pose Estimation with Graph Pose Refinement

Relative Pose from Deep Learned Depth and a Single Affine Correspondence

Graph Neural Network for Video-Query based Video Moment Retrieval

Pairwise Similarity Knowledge Transfer for Weakly Supervised Object Localization

Improving the Long-Range Performance of Gated Graph Neural Networks

PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks

Deep Learning of High-Order Interactions for Protein Interface Prediction

A Systematic Survey on Deep Generative Models for Graph Generation

Explanation-based Weakly-supervised Learning of Visual Relations with Graph Networks

GMNet: Graph Matching Network for Large Scale Part Semantic Segmentation in the Wild

Predicting Citywide Crowd Flows in Irregular Regions Using Multi-View Graph Convolutional Networks

Sketching Image Gist: Human-Mimetic Hierarchical Scene Graph Generation

SpatialSim: Recognizing Spatial Configurations of Objects with Graph Neural Networks

SketchGraphs: A Large-Scale Dataset for Modeling Relational Geometry in Computer-Aided Design

Inductive Link Prediction for Nodes Having Only Attribute Information

VidCEP: Complex Event Processing Framework to Detect Spatiotemporal Patterns in Video Streams

Label Propagation with Augmented Anchors: A Simple Semi-Supervised Learning baseline for Unsupervised Domain Adaptation

Neural networks adapting to datasets: learning network size and topology

ContourRend: A Segmentation Method for Improving Contours by Rendering

OVC-Net: Object-Oriented Video Captioning with Temporal Graph and Detail Enhancement

ADSAGE: Anomaly Detection in Sequences of Attributed Graph Edges applied to insider threat detection at fine-grained level

Topology-Change-Aware Volumetric Fusion for Dynamic Scene Reconstruction

Learning Differential Diagnosis of Skin Conditions with Co-occurrence Supervision using Graph Convolutional Networks

Learning Combinatorial Optimization on Graphs: A Survey with Applications to Networking

Embedding Propagation: Smoother Manifold for Few-Shot Classification

Beyond Graph Neural Networks with Lifted Relational Neural Networks

DinerDash Gym: A Benchmark for Policy Learning in High-Dimensional Action Space

Automated Intracranial Artery Labeling using a Graph Neural Network and Hierarchical Refinement

Node Copying for Protection Against Graph Neural Network Topology Attacks

Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation

Spectral Graph-based Features for Recognition of Handwritten Characters: A Case Study on Handwritten Devanagari Numerals

Orthogonal Structure Search for Efficient Causal Discovery from Observational Data

Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs

GraphX$^{NET}-$ Chest X-Ray Classification Under Extreme Minimal Supervision

A Similarity Inference Metric for RGB-Infrared Cross-Modality Person Re-identification

Maximum Likelihood Estimation and Graph Matching in Errorfully Observed Networks

Ramanujan Bipartite Graph Products for Efficient Block Sparse Neural Networks

TRAMP: Compositional Inference with TRee Approximate Message Passing

HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification

Sparse Randomized Shortest Paths Routing with Tsallis Divergence Regularization

TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear Subspaces

Enhancing the Association in Multi-Object Tracking via Neighbor Graph

A benchmark study on reliable molecular supervised learning via Bayesian learning

G-image Segmentation: Similarity-preserving Fuzzy C-Means with Spatial Information Constraint in Wavelet Space

Bayesian Graph Neural Networks with Adaptive Connection Sampling

A Variational Perturbative Approach to Planning in Graph-based Markov Decision Processes

Learning the piece-wise constant graph structure of a varying Ising model

Multi-Partition Embedding Interaction with Block Term Format for Knowledge Graph Completion

Symbolic Network: Generalized Neural Policies for Relational MDPs

Human Activity Recognition based on Dynamic Spatio-Temporal Relations

DeGNN: Characterizing and Improving Graph Neural Networks with Graph Decomposition

Community detection and percolation of information in a geometric setting

A maximum principle argument for the uniform convergence of graph Laplacian regressors

The GraphNet Zoo: An All-in-One Graph Based Deep Semi-Supervised Framework for Medical Image Classification

CPL-SLAM: Efficient and Certifiably Correct Planar Graph-Based SLAM Using the Complex Number Representation

Background Knowledge Injection for Interpretable Sequence Classification

Comprehensive Information Integration Modeling Framework for Video Titling

Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks

Missing Data Imputation with Adversarially-trained Graph Convolutional Networks

Dynamic Functional Connectivity and Graph Convolution Network for Alzheimer's Disease Classification

Data Augmentation View on Graph Convolutional Network and the Proposal of Monte Carlo Graph Learning

A Closer Look at Small-loss Bounds for Bandits with Graph Feedback

Spectral Evolution with Approximated Eigenvalue Trajectories for Link Prediction

A Multiscale Graph Convolutional Network Using Hierarchical Clustering

Fast and Accurate: Structure Coherence Component for Face Alignment

Self-supervised Learning on Graphs: Deep Insights and New Direction

MoFlow: An Invertible Flow Model for Generating Molecular Graphs

LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments

Causal inference of brain connectivity from fMRI with $ψ$-Learning Incorporated Linear non-Gaussian Acyclic Model ($ψ$-LiNGAM)

Walk Message Passing Neural Networks and Second-Order Graph Neural Networks

DefenseVGAE: Defending against Adversarial Attacks on Graph Data via a Variational Graph Autoencoder

Infinite Feature Selection: A Graph-based Feature Filtering Approach

Graph Hawkes Neural Network for Forecasting on Temporal Knowledge Graphs

Structure learning for CTBN's via penalized maximum likelihood methods

Consistent Semi-Supervised Graph Regularization for High Dimensional Data

GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learning

Making Better Mistakes: Leveraging Class Hierarchies with Deep Networks

Towards Deeper Graph Neural Networks with Differentiable Group Normalization

Learning Global and Local Consistent Representations for Unsupervised Image Retrieval via Deep Graph Diffusion Networks

Regret Analysis of Bandit Problems with Causal Background Knowledge

Entire Space Multi-Task Modeling via Post-Click Behavior Decomposition for Conversion Rate Prediction

A Multi-step and Resilient Predictive Q-learning Algorithm for IoT with Human Operators in the Loop: A Case Study in Water Supply Networks

Computationally Tractable Riemannian Manifolds for Graph Embeddings

Are Graph Convolutional Networks Fully Exploiting Graph Structure?

Learning Bayesian Networks that enable full propagation of evidence

Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identification

Sample Efficient Graph-Based Optimization with Noisy Observations

Visual Summarization of Lecture Video Segments for Enhanced Navigation

SimPool: Towards Topology Based Graph Pooling with Structural Similarity Features

When2com: Multi-Agent Perception via Communication Graph Grouping

Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networks

Tree-Projected Gradient Descent for Estimating Gradient-Sparse Parameters on Graphs

City-Scale Road Extraction from Satellite Imagery v2: Road Speeds and Travel Times

High-order structure preserving graph neural network for few-shot learning

Feedback System Neural Networks for Inferring Causality in Directed Cyclic Graphs

Kernel methods library for pattern analysis and machine learning in python

COVID-19 growth prediction using multivariate long short term memory

NENET: An Edge Learnable Network for Link Prediction in Scene Text

Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs

Deterministic Completion of Rectangular Matrices Using Asymmetric Ramanujan Graphs: Exact and Stable Recovery

DisCoveR: Accurate & Efficient Discovery of Declarative Process Models

Spatial-Temporal Graph Convolutional Networks for Sign Language Recognition

GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous Driving

Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition

A Novel Technique Combining Image Processing, Plant Development Properties, and the Hungarian Algorithm, to Improve Leaf Detection in Maize

Scalable Label Propagation for Multi-relational Learning on the Tensor Product of Graphs

Modeling Pharmacological Effects with Multi-Relation Unsupervised Graph Embedding

Optimal Laplacian regularization for sparse spectral community detection

Analyzing Knowledge Graph Embedding Methods from a Multi-Embedding Interaction Perspective

ODVICE: An Ontology-Driven Visual Analytic Tool for Interactive Cohort Extraction

DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses

EEG-Based Emotion Recognition Using Regularized Graph Neural Networks

Learning Descriptors Invariance Through Equivalence Relations Within Manifold: A New Approach to Expression Invariant 3D Face Recognition

Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks

VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation

Graph Convolution Networks for Probabilistic Modeling of Driving Acceleration

Regression Forest-Based Atlas Localization and Direction Specific Atlas Generation for Pancreas Segmentation

Weighted Cheeger and Buser Inequalities, with Applications to Clustering and Cutting Probability Densities

CoMoGCN: Coherent Motion Aware Trajectory Prediction with Graph Representation

A Dynamical Mean-Field Theory for Learning in Restricted Boltzmann Machines

Decision Support for Intoxication Prediction Using Graph Convolutional Networks

On Learning Combinatorial Patterns to Assist Large-Scale Airline Crew Pairing Optimization

Stochastic Neighbor Embedding of Multimodal Relational Data for Image-Text Simultaneous Visualization

Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning

A 3D Convolutional Approach to Spectral Object Segmentation in Space and Time

GraftNet: An Engineering Implementation of CNN for Fine-grained Multi-label Task

Compressed Sensing Using Binary Matrices of Nearly Optimal Dimensions

Learning Decision Ensemble using a Graph Neural Network for Comorbidity Aware Chest Radiograph Screening

Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting

Graph Convolutional Subspace Clustering: A Robust Subspace Clustering Framework for Hyperspectral Image

Flow-based Algorithms for Improving Clusters: A Unifying Framework, Software, and Performance

Multi-view Self-Constructing Graph Convolutional Networks with Adaptive Class Weighting Loss for Semantic Segmentation

Strong Consistency, Graph Laplacians, and the Stochastic Block Model

Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution

Graph-Partitioning-Based Diffusion Convolutional Recurrent Neural Network for Large-Scale Traffic Forecasting

A Lagrangian Approach to Information Propagation in Graph Neural Networks

Hcore-Init: Neural Network Initialization based on Graph Degeneracy

Identification Methods With Arbitrary Interventional Distributions as Inputs

Mask Combination of Multi-layer Graphs for Global Structure Inference

Vertex Nomination, Consistent Estimation, and Adversarial Modification

Gumbel-softmax-based Optimization: A Simple General Framework for Optimization Problems on Graphs

Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits

Exploiting Interpretable Patterns for Flow Prediction in Dockless Bike Sharing Systems

Inter-Region Affinity Distillation for Road Marking Segmentation

Shoestring: Graph-Based Semi-Supervised Learning with Severely Limited Labeled Data

A Graph Convolutional Network Composition Framework for Semi-supervised Classification

The general theory of permutation equivarant neural networks and higher order graph variational encoders

GraphGen: A Scalable Approach to Domain-agnostic Labeled Graph Generation

Consistent and Complementary Graph Regularized Multi-view Subspace Clustering

Graph Prolongation Convolutional Networks: Explicitly Multiscale Machine Learning on Graphs with Applications to Modeling of Cytoskeleton

Detecting Communities in Heterogeneous Multi-Relational Networks:A Message Passing based Approach

Appearance Shock Grammar for Fast Medial Axis Extraction from Real Images

Let's Agree to Degree: Comparing Graph Convolutional Networks in the Message-Passing Framework

Attribute2vec: Deep Network Embedding Through Multi-Filtering GCN

DualConvMesh-Net: Joint Geodesic and Euclidean Convolutions on 3D Meshes

Unsupervised Feature Learning Architecture with Multi-clustering Integration RBM

High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification

Graph-based fusion for change detection in multi-spectral images

SDFN: Segmentation-based Deep Fusion Network for Thoracic Disease Classification in Chest X-ray Images

DPGN: Distribution Propagation Graph Network for Few-shot Learning

Graph-guided Architecture Search for Real-time Semantic Segmentation

KSR: A Semantic Representation of Knowledge Graph within a Novel Unsupervised Paradigm

Semi-Supervised Cervical Dysplasia Classification With Learnable Graph Convolutional Network

Multi-Modal Graph Neural Network for Joint Reasoning on Vision and Scene Text

A Decentralized Policy with Logarithmic Regret for a Class of Multi-Agent Multi-Armed Bandit Problems with Option Unavailability Constraints and Stochastic Communication Protocols

Spatio-Temporal Graph for Video Captioning with Knowledge Distillation

OCmst: One-class Novelty Detection using Convolutional Neural Network and Minimum Spanning Trees

Stochastic Proximal Gradient Algorithm with Minibatches. Application to Large Scale Learning Models

A Topological Nomenclature for 3D Shape Analysis in Connectomics

GPS-Net: Graph Property Sensing Network for Scene Graph Generation

The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction

The impossibility of low rank representations for triangle-rich complex networks

SceneCAD: Predicting Object Alignments and Layouts in RGB-D Scans

Kernel Truncated Regression Representation for Robust Subspace Clustering

Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs

Where Does It Exist: Spatio-Temporal Video Grounding for Multi-Form Sentences

Incorporating User's Preference into Attributed Graph Clustering

Dynamic Origin-Destination Matrix Prediction with Line Graph Neural Networks and Kalman Filter

Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

Incremental and Decremental Fuzzy Bounded Twin Support Vector Machine

Linguistically Driven Graph Capsule Network for Visual Question Reasoning

UGRWO-Sampling: A modified random walk under-sampling approach based on graphs to imbalanced data classification

MINT: Deep Network Compression via Mutual Information-based Neuron Trimming

Dynamic Multiscale Graph Neural Networks for 3D Skeleton-Based Human Motion Prediction

ReLaText: Exploiting Visual Relationships for Arbitrary-Shaped Scene Text Detection with Graph Convolutional Networks

Tensor Graph Convolutional Networks for Multi-relational and Robust Learning

Vectorizing World Buildings: Planar Graph Reconstruction by Primitive Detection and Relationship Inference

Heterogeneous-Temporal Graph Convolutional Networks: Make the Community Detection Much Better

Dual Temporal Memory Network for Efficient Video Object Segmentation

Interaction Graphs for Object Importance Estimation in On-road Driving Videos

DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs

PSC-Net: Learning Part Spatial Co-occurrence for Occluded Pedestrian Detection

Consistency of semi-supervised learning algorithms on graphs: Probit and one-hot methods

PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures

Neural Operator: Graph Kernel Network for Partial Differential Equations

Centrality Graph Convolutional Networks for Skeleton-based Action Recognition

Factorized Graph Representations for Semi-Supervised Learning from Sparse Data

Cross-GCN: Enhancing Graph Convolutional Network with $k$-Order Feature Interactions

Propagating Asymptotic-Estimated Gradients for Low Bitwidth Quantized Neural Networks

ElixirNet: Relation-aware Network Architecture Adaptation for Medical Lesion Detection

Learning 3D-aware Egocentric Spatial-Temporal Interaction via Graph Convolutional Networks

Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs

Towards a predictive spatio-temporal representation of brain data

Learning Nonparametric Human Mesh Reconstruction from a Single Image without Ground Truth Meshes

Trained Quantization Thresholds for Accurate and Efficient Fixed-Point Inference of Deep Neural Networks

4D Association Graph for Realtime Multi-person Motion Capture Using Multiple Video Cameras

AutoSF: Searching Scoring Functions for Knowledge Graph Embedding

SCALE-Net: Scalable Vehicle Trajectory Prediction Network under Random Number of Interacting Vehicles via Edge-enhanced Graph Convolutional Neural Network

Dynamic Graph Correlation Learning for Disease Diagnosis with Incomplete Labels

Graph Neural Networks for Image Understanding Based on Multiple Cues: Group Emotion Recognition and Event Recognition as Use Cases

TGGLines: A Robust Topological Graph Guided Line Segment Detector for Low Quality Binary Images

Few-Shot Learning on Graphs via Super-Classes based on Graph Spectral Measures

Kernel Bi-Linear Modeling for Reconstructing Data on Manifolds: The Dynamic-MRI Case

Object Relational Graph with Teacher-Recommended Learning for Video Captioning

Infinitely Wide Graph Convolutional Networks: Semi-supervised Learning via Gaussian Processes

PuzzleNet: Scene Text Detection by Segment Context Graph Learning

Towards an Efficient and General Framework of Robust Training for Graph Neural Networks

Poisson Kernel Avoiding Self-Smoothing in Graph Convolutional Networks

MONET: Debiasing Graph Embeddings via the Metadata-Orthogonal Training Unit

Injective Domain Knowledge in Neural Networks for Transprecision Computing

FONDUE: A Framework for Node Disambiguation Using Network Embeddings

Struct-MMSB: Mixed Membership Stochastic Blockmodels with Interpretable Structured Priors

A Decentralized Communication Policy for Multi Agent Multi Armed Bandit Problems

I-SPEC: An End-to-End Framework for Learning Transportable, Shift-Stable Models

Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels

Virtual Adversarial Training on Graph Convolutional Networks in Node Classification

Indirect Adversarial Attacks via Poisoning Neighbors for Graph Convolutional Networks

A flexible outlier detector based on a topology given by graph communities

GraphZoom: A multi-level spectral approach for accurate and scalable graph embedding

Interpretable Neuron Structuring with Graph Spectral Regularization

Generalization and Representational Limits of Graph Neural Networks

A Survey on 3D Skeleton-Based Action Recognition Using Learning Method

Shortest path distance approximation using deep learning techniques

The Gossiping Insert-Eliminate Algorithm for Multi-Agent Bandits

Particle Competition and Cooperation for Semi-Supervised Learning with Label Noise

Building Footprint Generation by IntegratingConvolution Neural Network with Feature PairwiseConditional Random Field (FPCRF)

Efficient Global Multi-object Tracking Under Minimum-cost Circulation Framework

Regularizing Semi-supervised Graph Convolutional Networks with a Manifold Smoothness Loss

When Labelled Data Hurts: Deep Semi-Supervised Classification with the Graph 1-Laplacian

Laplacian-regularized graph bandits: Algorithms and theoretical analysis

From Anchor Generation to Distribution Alignment: Learning a Discriminative Embedding Space for Zero-Shot Recognition

Dynamic Inference: A New Approach Toward Efficient Video Action Recognition

Multi-Agent Thompson Sampling for Bandit Applications with Sparse Neighbourhood Structures

Statistical Outlier Identification in Multi-robot Visual SLAM using Expectation Maximization

DDP-GCN: Multi-Graph Convolutional Network for Spatiotemporal Traffic Forecasting

Low-dimensional statistical manifold embedding of directed graphs

Contextual Translation Embedding for Visual Relationship Detection and Scene Graph Generation

Supervised Learning on Relational Databases with Graph Neural Networks

Action Graphs: Weakly-supervised Action Localization with Graph Convolution Networks

Unbiased Scene Graph Generation via Rich and Fair Semantic Extraction

Edge-based sequential graph generation with recurrent neural networks

Balancing the Tradeoff Between Clustering Value and Interpretability

Covariance and Correlation Kernels on a Graph in the Generalized Bag-of-Paths Formalism

The KEEN Universe: An Ecosystem for Knowledge Graph Embeddings with a Focus on Reproducibility and Transferability

An empirical study on using CNNs for fast radio signal prediction

Efficient and Differentiable Shadow Computation for Inverse Problems

Towards High Fidelity Monocular Face Reconstruction with Rich Reflectance using Self-supervised Learning and Ray Tracing

Next-best-view Regression using a 3D Convolutional Neural Network

PeeledHuman: Robust Shape Representation for Textured 3D Human Body Reconstruction

CoReNet: Coherent 3D scene reconstruction from a single RGB image

Deep Image Translation for Enhancing Simulated Ultrasound Images

ViWi: A Deep Learning Dataset Framework for Vision-Aided Wireless Communications

A Differential Volumetric Approach to Multi-View Photometric Stereo

Deep Learning and Gaussian Process based Band Assignment in Dual Band Systems

Object 3D Reconstruction based on Photometric Stereo and Inverted Rendering

HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO

YAHPO Gym -- Design Criteria and a new Multifidelity Benchmark for Hyperparameter Optimization

Not All Datasets Are Born Equal: On Heterogeneous Data and Adversarial Examples

Fair Representation: Guaranteeing Approximate Multiple Group Fairness for Unknown Tasks

Contrastive Mixup: Self- and Semi-Supervised learning for Tabular Domain

A fuzzy-rough uncertainty measure to discover bias encoded explicitly or implicitly in features of structured pattern classification datasets

Managing ML Pipelines: Feature Stores and the Coming Wave of Embedding Ecosystems

Maxmin Q-learning: Controlling the Estimation Bias of Q-learning

Reducing Unintended Bias of ML Models on Tabular and Textual Data

Automatic Fairness Testing of Neural Classifiers through Adversarial Sampling

Picket: Guarding Against Corrupted Data in Tabular Data during Learning and Inference

Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks

IFedAvg: Interpretable Data-Interoperability for Federated Learning

A Fully Problem-Dependent Regret Lower Bound for Finite-Horizon MDPs

Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density Estimation

Gradient Play in Multi-Agent Markov Stochastic Games: Stationary Points and Convergence

An Analysis of the Deployment of Models Trained on Private Tabular Synthetic Data: Unexpected Surprises

Model-Free Learning for Two-Player Zero-Sum Partially Observable Markov Games with Perfect Recall

Self-Trained One-class Classification for Unsupervised Anomaly Detection

Polynomial magic! Hermite polynomials for private data generation

No MCMC for me: Amortized sampling for fast and stable training of energy-based models

DP-MERF: Differentially Private Mean Embeddings with Random Features for Practical Privacy-Preserving Data Generation

DEHB: Evolutionary Hyberband for Scalable, Robust and Efficient Hyperparameter Optimization

Transitioning from Real to Synthetic data: Quantifying the bias in model

EBIC.JL -- an Efficient Implementation of Evolutionary Biclustering Algorithm in Julia

ALReLU: A different approach on Leaky ReLU activation function to improve Neural Networks Performance

PyTorch Tabular: A Framework for Deep Learning with Tabular Data

Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL

Efficient Click-Through Rate Prediction for Developing Countries via Tabular Learning

NICE: An Algorithm for Nearest Instance Counterfactual Explanations

Holdout-Based Fidelity and Privacy Assessment of Mixed-Type Synthetic Data

CrowdTeacher: Robust Co-teaching with Noisy Answers & Sample-specific Perturbations for Tabular Data

Logical Team Q-learning: An approach towards factored policies in cooperative MARL

Acting in Delayed Environments with Non-Stationary Markov Policies

Learning to Predict with Supporting Evidence: Applications to Clinical Risk Prediction

Recreation of the Periodic Table with an Unsupervised Machine Learning Algorithm

Robust Generalization and Safe Query-Specialization in Counterfactual Learning to Rank

Model Rectification via Unknown Unknowns Extraction from Deployment Samples

DNN2LR: Interpretation-inspired Feature Crossing for Real-world Tabular Data

Unsupervised Functional Data Analysis via Nonlinear Dimension Reduction

Amazon SageMaker Autopilot: a white box AutoML solution at scale

When stakes are high: balancing accuracy and transparency with Model-Agnostic Interpretable Data-driven suRRogates

Leveraging Automated Machine Learning for Text Classification: Evaluation of AutoML Tools and Comparison with Human Performance

Joint Policy Search for Multi-agent Collaboration with Imperfect Information

ReMix: Calibrated Resampling for Class Imbalance in Deep learning

Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data

NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search

AgEBO-Tabular: Joint Neural Architecture and Hyperparameter Search with Autotuned Data-Parallel Training for Tabular Data

New Properties of the Data Distillation Method When Working With Tabular Data

Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling

Tabular Structure Detection from Document Images for Resource Constrained Devices Using A Row Based Similarity Measure

InstanceFlow: Visualizing the Evolution of Classifier Confusion on the Instance Level

Minority Class Oversampling for Tabular Data with Deep Generative Models

Model-based Asynchronous Hyperparameter and Neural Architecture Search

A Recent Survey on the Applications of Genetic Programming in Image Processing

Robust Variational Autoencoder for Tabular Data with Beta Divergence

Network On Network for Tabular Data Classification in Real-world Applications

Uncertainty estimation for classification and risk prediction on medical tabular data

Fine-Grain Few-Shot Vision via Domain Knowledge as Hyperspherical Priors

Learning Model-Agnostic Counterfactual Explanations for Tabular Data

NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search

BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders

Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data

AP-Perf: Incorporating Generic Performance Metrics in Differentiable Learning

Lifting Interpretability-Performance Trade-off via Automated Feature Engineering

DeepErase: Weakly Supervised Ink Artifact Removal in Document Text Images

Scalable methods for computing state similarity in deterministic Markov Decision Processes

A Wide and Deep Neural Network for Survival Analysis from Anatomical Shape and Tabular Clinical Data

AutoCross: Automatic Feature Crossing for Tabular Data in Real-World Applications

SuperTML: Two-Dimensional Word Embedding for the Precognition on Structured Tabular Data

Tabular Benchmarks for Joint Architecture and Hyperparameter Optimization

SAFE ML: Surrogate Assisted Feature Extraction for Model Learning

NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature

Performance Guarantees for Homomorphisms Beyond Markov Decision Processes

Regularization Learning Networks: Deep Learning for Tabular Datasets

Detecting Potential Local Adversarial Examples for Human-Interpretable Defense

Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models

An experimental study of graph-based semi-supervised classification with additional node information

Mining Spatio-temporal Data on Industrialization from Historical Registries

Wav2Letter: an End-to-End ConvNet-based Speech Recognition System