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DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues | 17 | iclr | 5 | 1 | 2023-06-18 09:24:51.189000 | https://github.com/rishabhjoshi/DialoGraph_ICLR21 | 12 | Dialograph: Incorporating interpretable strategy-graph networks into negotiation dialogues | https://scholar.google.com/scholar?cluster=13588714176146046430&hl=en&as_sdt=0,33 | 3 | 2,021 |
Multi-Time Attention Networks for Irregularly Sampled Time Series | 67 | iclr | 16 | 5 | 2023-06-18 09:24:51.391000 | https://github.com/reml-lab/mTAN | 76 | Multi-time attention networks for irregularly sampled time series | https://scholar.google.com/scholar?cluster=6069781928255471893&hl=en&as_sdt=0,33 | 3 | 2,021 |
SEED: Self-supervised Distillation For Visual Representation | 116 | iclr | 11 | 1 | 2023-06-18 09:24:51.595000 | https://github.com/jacobswan1/SEED | 32 | Seed: Self-supervised distillation for visual representation | https://scholar.google.com/scholar?cluster=8472207324878329601&hl=en&as_sdt=0,6 | 2 | 2,021 |
Effective and Efficient Vote Attack on Capsule Networks | 14 | iclr | 1 | 0 | 2023-06-18 09:24:51.798000 | https://github.com/JindongGu/VoteAttack | 8 | Effective and efficient vote attack on capsule networks | https://scholar.google.com/scholar?cluster=17735896064607887754&hl=en&as_sdt=0,5 | 1 | 2,021 |
Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization | 44 | iclr | 1 | 2 | 2023-06-18 09:24:52.001000 | https://github.com/kaidic/HAR | 30 | Heteroskedastic and imbalanced deep learning with adaptive regularization | https://scholar.google.com/scholar?cluster=5140614749291211049&hl=en&as_sdt=0,39 | 1 | 2,021 |
Neural Thompson Sampling | 60 | iclr | 3 | 0 | 2023-06-18 09:24:52.204000 | https://github.com/ZeroWeight/NeuralTS | 9 | Neural thompson sampling | https://scholar.google.com/scholar?cluster=5718992412450799651&hl=en&as_sdt=0,31 | 1 | 2,021 |
Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics | 42 | iclr | 3 | 1 | 2023-06-18 09:24:52.408000 | https://github.com/danielkunin/neural-mechanics | 18 | Neural mechanics: Symmetry and broken conservation laws in deep learning dynamics | https://scholar.google.com/scholar?cluster=8694895381782484369&hl=en&as_sdt=0,11 | 3 | 2,021 |
Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction | 18 | iclr | 2 | 0 | 2023-06-18 09:24:52.618000 | https://github.com/1Konny/HierarchicalVideoPrediction | 21 | Revisiting hierarchical approach for persistent long-term video prediction | https://scholar.google.com/scholar?cluster=3252280345602395682&hl=en&as_sdt=0,34 | 3 | 2,021 |
Modelling Hierarchical Structure between Dialogue Policy and Natural Language Generator with Option Framework for Task-oriented Dialogue System | 31 | iclr | 0 | 2 | 2023-06-18 09:24:52.824000 | https://github.com/mikezhang95/HDNO | 18 | Modelling hierarchical structure between dialogue policy and natural language generator with option framework for task-oriented dialogue system | https://scholar.google.com/scholar?cluster=10305196769092538999&hl=en&as_sdt=0,5 | 3 | 2,021 |
Categorical Normalizing Flows via Continuous Transformations | 20 | iclr | 11 | 1 | 2023-06-18 09:24:53.027000 | https://github.com/phlippe/CategoricalNF | 51 | Categorical normalizing flows via continuous transformations | https://scholar.google.com/scholar?cluster=3325488278431925119&hl=en&as_sdt=0,18 | 3 | 2,021 |
Learning to Represent Action Values as a Hypergraph on the Action Vertices | 11 | iclr | 6 | 0 | 2023-06-18 09:24:53.230000 | https://github.com/atavakol/action-hypergraph-networks | 19 | Learning to represent action values as a hypergraph on the action vertices | https://scholar.google.com/scholar?cluster=8032720011491457722&hl=en&as_sdt=0,5 | 1 | 2,021 |
Lifelong Learning of Compositional Structures | 25 | iclr | 8 | 1 | 2023-06-18 09:24:53.433000 | https://github.com/GRASP-ML/Mendez2020Compositional | 12 | Lifelong learning of compositional structures | https://scholar.google.com/scholar?cluster=11061523929398124661&hl=en&as_sdt=0,5 | 5 | 2,021 |
Creative Sketch Generation | 42 | iclr | 13 | 0 | 2023-06-18 09:24:53.643000 | https://github.com/facebookresearch/DoodlerGAN | 101 | Creative sketch generation | https://scholar.google.com/scholar?cluster=2511600747232100268&hl=en&as_sdt=0,5 | 8 | 2,021 |
Concept Learners for Few-Shot Learning | 61 | iclr | 13 | 6 | 2023-06-18 09:24:53.863000 | https://github.com/snap-stanford/comet | 104 | Concept learners for few-shot learning | https://scholar.google.com/scholar?cluster=14029381289602972954&hl=en&as_sdt=0,5 | 8 | 2,021 |
DeLighT: Deep and Light-weight Transformer | 88 | iclr | 50 | 7 | 2023-06-18 09:24:54.066000 | https://github.com/sacmehta/delight | 443 | Delight: Deep and light-weight transformer | https://scholar.google.com/scholar?cluster=13638554196274165568&hl=en&as_sdt=0,47 | 14 | 2,021 |
Mastering Atari with Discrete World Models | 385 | iclr | 183 | 6 | 2023-06-18 09:24:54.269000 | https://github.com/danijar/dreamerv2 | 767 | Mastering atari with discrete world models | https://scholar.google.com/scholar?cluster=2696098032395844049&hl=en&as_sdt=0,5 | 27 | 2,021 |
Learning Neural Event Functions for Ordinary Differential Equations | 76 | iclr | 848 | 61 | 2023-06-18 09:24:54.472000 | https://github.com/rtqichen/torchdiffeq | 4,676 | Learning neural event functions for ordinary differential equations | https://scholar.google.com/scholar?cluster=15727092148990578310&hl=en&as_sdt=0,1 | 123 | 2,021 |
Contemplating Real-World Object Classification | 6 | iclr | 0 | 0 | 2023-06-18 09:24:54.675000 | https://github.com/aliborji/ObjectNetReanalysis | 15 | Contemplating real-world object classification | https://scholar.google.com/scholar?cluster=6078463704696071400&hl=en&as_sdt=0,14 | 3 | 2,021 |
Neural Spatio-Temporal Point Processes | 56 | iclr | 16 | 5 | 2023-06-18 09:24:54.878000 | https://github.com/facebookresearch/neural_stpp | 85 | Neural spatio-temporal point processes | https://scholar.google.com/scholar?cluster=6976487564397209584&hl=en&as_sdt=0,33 | 10 | 2,021 |
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach | 105 | iclr | 5 | 0 | 2023-06-18 09:24:55.081000 | https://github.com/UCSC-REAL/cores | 27 | Learning with instance-dependent label noise: A sample sieve approach | https://scholar.google.com/scholar?cluster=1816427362683189606&hl=en&as_sdt=0,22 | 4 | 2,021 |
Unbiased Teacher for Semi-Supervised Object Detection | 254 | iclr | 82 | 32 | 2023-06-18 09:24:55.284000 | https://github.com/facebookresearch/unbiased-teacher | 393 | Unbiased teacher for semi-supervised object detection | https://scholar.google.com/scholar?cluster=860392753310305868&hl=en&as_sdt=0,33 | 17 | 2,021 |
Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks | 183 | iclr | 13 | 0 | 2023-06-18 09:24:55.487000 | https://github.com/bboylyg/NAD | 98 | Neural attention distillation: Erasing backdoor triggers from deep neural networks | https://scholar.google.com/scholar?cluster=11473045902984731830&hl=en&as_sdt=0,22 | 2 | 2,021 |
Contrastive Learning with Adversarial Perturbations for Conditional Text Generation | 66 | iclr | 3 | 3 | 2023-06-18 09:24:55.690000 | https://github.com/seanie12/CLAPS | 77 | Contrastive learning with adversarial perturbations for conditional text generation | https://scholar.google.com/scholar?cluster=13654340302052439773&hl=en&as_sdt=0,5 | 4 | 2,021 |
Text Generation by Learning from Demonstrations | 34 | iclr | 6 | 0 | 2023-06-18 09:24:55.893000 | https://github.com/yzpang/gold-off-policy-text-gen-iclr21 | 42 | Text generation by learning from demonstrations | https://scholar.google.com/scholar?cluster=7301017997862747001&hl=en&as_sdt=0,5 | 3 | 2,021 |
Learning Long-term Visual Dynamics with Region Proposal Interaction Networks | 40 | iclr | 12 | 0 | 2023-06-18 09:24:56.097000 | https://github.com/HaozhiQi/RPIN | 110 | Learning long-term visual dynamics with region proposal interaction networks | https://scholar.google.com/scholar?cluster=12876852900832613209&hl=en&as_sdt=0,5 | 5 | 2,021 |
ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations | 21 | iclr | 7 | 5 | 2023-06-18 09:24:56.301000 | https://github.com/transmuteAI/ChipNet | 20 | Chipnet: Budget-aware pruning with heaviside continuous approximations | https://scholar.google.com/scholar?cluster=18315278844626956767&hl=en&as_sdt=0,5 | 4 | 2,021 |
Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation | 17 | iclr | 0 | 1 | 2023-06-18 09:24:56.504000 | https://github.com/INK-USC/deceive-KG-models | 4 | Learning to deceive knowledge graph augmented models via targeted perturbation | https://scholar.google.com/scholar?cluster=10251964553453690301&hl=en&as_sdt=0,5 | 5 | 2,021 |
IEPT: Instance-Level and Episode-Level Pretext Tasks for Few-Shot Learning | 67 | iclr | 4 | 5 | 2023-06-18 09:24:56.708000 | https://github.com/rucmlcv/IEPT_FSL | 32 | IEPT: Instance-level and episode-level pretext tasks for few-shot learning | https://scholar.google.com/scholar?cluster=13782822580168472981&hl=en&as_sdt=0,33 | 1 | 2,021 |
Training with Quantization Noise for Extreme Model Compression | 163 | iclr | 5,883 | 1,031 | 2023-06-18 09:24:56.912000 | https://github.com/pytorch/fairseq | 26,500 | Training with quantization noise for extreme model compression | https://scholar.google.com/scholar?cluster=10846655234663420432&hl=en&as_sdt=0,38 | 411 | 2,021 |
Distilling Knowledge from Reader to Retriever for Question Answering | 113 | iclr | 98 | 18 | 2023-06-18 09:24:57.115000 | https://github.com/facebookresearch/FiD | 410 | Distilling knowledge from reader to retriever for question answering | https://scholar.google.com/scholar?cluster=18188741483036284668&hl=en&as_sdt=0,24 | 8 | 2,021 |
not-MIWAE: Deep Generative Modelling with Missing not at Random Data | 35 | iclr | 2 | 1 | 2023-06-18 09:24:57.318000 | https://github.com/nbip/notMIWAE | 10 | not-MIWAE: Deep generative modelling with missing not at random data | https://scholar.google.com/scholar?cluster=6702862707745789629&hl=en&as_sdt=0,5 | 1 | 2,021 |
Learning with AMIGo: Adversarially Motivated Intrinsic Goals | 107 | iclr | 7 | 6 | 2023-06-18 09:24:57.522000 | https://github.com/facebookresearch/adversarially-motivated-intrinsic-goals | 60 | Learning with amigo: Adversarially motivated intrinsic goals | https://scholar.google.com/scholar?cluster=10840346887158319600&hl=en&as_sdt=0,5 | 13 | 2,021 |
CaPC Learning: Confidential and Private Collaborative Learning | 41 | iclr | 6 | 0 | 2023-06-18 09:24:57.726000 | https://github.com/cleverhans-lab/capc-iclr | 25 | Capc learning: Confidential and private collaborative learning | https://scholar.google.com/scholar?cluster=10267580043538476414&hl=en&as_sdt=0,33 | 2 | 2,021 |
Self-supervised Representation Learning with Relative Predictive Coding | 25 | iclr | 1 | 0 | 2023-06-18 09:24:57.929000 | https://github.com/martinmamql/relative_predictive_coding | 17 | Self-supervised representation learning with relative predictive coding | https://scholar.google.com/scholar?cluster=17809486725301186145&hl=en&as_sdt=0,33 | 3 | 2,021 |
On the Impossibility of Global Convergence in Multi-Loss Optimization | 28 | iclr | 0 | 0 | 2023-06-18 09:24:58.134000 | https://github.com/aletcher/impossibility-global-convergence | 1 | On the impossibility of global convergence in multi-loss optimization | https://scholar.google.com/scholar?cluster=12737917021502438759&hl=en&as_sdt=0,8 | 2 | 2,021 |
Discrete Graph Structure Learning for Forecasting Multiple Time Series | 90 | iclr | 32 | 10 | 2023-06-18 09:24:58.337000 | https://github.com/chaoshangcs/GTS | 138 | Discrete graph structure learning for forecasting multiple time series | https://scholar.google.com/scholar?cluster=10547313552848250901&hl=en&as_sdt=0,5 | 1 | 2,021 |
Contrastive Learning with Hard Negative Samples | 372 | iclr | 29 | 4 | 2023-06-18 09:24:58.541000 | https://github.com/joshr17/HCL | 209 | Contrastive learning with hard negative samples | https://scholar.google.com/scholar?cluster=9395538845107330163&hl=en&as_sdt=0,33 | 4 | 2,021 |
Sliced Kernelized Stein Discrepancy | 32 | iclr | 1 | 0 | 2023-06-18 09:24:58.754000 | https://github.com/WenboGong/Sliced_Kernelized_Stein_Discrepancy | 1 | Sliced kernelized Stein discrepancy | https://scholar.google.com/scholar?cluster=2996953406646769622&hl=en&as_sdt=0,33 | 1 | 2,021 |
Denoising Diffusion Implicit Models | 888 | iclr | 117 | 9 | 2023-06-18 09:24:58.968000 | https://github.com/ermongroup/ddim | 739 | Denoising diffusion implicit models | https://scholar.google.com/scholar?cluster=15692403916484267912&hl=en&as_sdt=0,5 | 7 | 2,021 |
Hierarchical Reinforcement Learning by Discovering Intrinsic Options | 39 | iclr | 5 | 0 | 2023-06-18 09:24:59.171000 | https://github.com/jesbu1/hidio | 33 | Hierarchical reinforcement learning by discovering intrinsic options | https://scholar.google.com/scholar?cluster=13774457898597661274&hl=en&as_sdt=0,31 | 3 | 2,021 |
Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval | 31 | iclr | 20 | 10 | 2023-06-18 09:24:59.375000 | https://github.com/facebookresearch/multihop_dense_retrieval | 193 | Answering complex open-domain questions with multi-hop dense retrieval | https://scholar.google.com/scholar?cluster=950426100300537362&hl=en&as_sdt=0,11 | 10 | 2,021 |
Rethinking Soft Labels for Knowledge Distillation: A Bias-Variance Tradeoff Perspective | 68 | iclr | 8 | 2 | 2023-06-18 09:24:59.579000 | https://github.com/bellymonster/Weighted-Soft-Label-Distillation | 51 | Rethinking soft labels for knowledge distillation: A bias-variance tradeoff perspective | https://scholar.google.com/scholar?cluster=3419265116885877699&hl=en&as_sdt=0,33 | 2 | 2,021 |
Learning to Set Waypoints for Audio-Visual Navigation | 66 | iclr | 50 | 35 | 2023-06-18 09:24:59.782000 | https://github.com/facebookresearch/sound-spaces | 265 | Learning to set waypoints for audio-visual navigation | https://scholar.google.com/scholar?cluster=3241754597982195177&hl=en&as_sdt=0,34 | 14 | 2,021 |
Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective | 144 | iclr | 31 | 1 | 2023-06-18 09:24:59.985000 | https://github.com/VITA-Group/TENAS | 160 | Neural architecture search on imagenet in four gpu hours: A theoretically inspired perspective | https://scholar.google.com/scholar?cluster=8900374722066786979&hl=en&as_sdt=0,33 | 5 | 2,021 |
Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning | 129 | iclr | 15 | 3 | 2023-06-18 09:25:00.188000 | https://github.com/wyjeong/FedMatch | 58 | Federated semi-supervised learning with inter-client consistency & disjoint learning | https://scholar.google.com/scholar?cluster=7065606493210904394&hl=en&as_sdt=0,44 | 1 | 2,021 |
Representation Learning for Sequence Data with Deep Autoencoding Predictive Components | 11 | iclr | 2 | 0 | 2023-06-18 09:25:00.391000 | https://github.com/JunwenBai/DAPC | 9 | Representation learning for sequence data with deep autoencoding predictive components | https://scholar.google.com/scholar?cluster=14928540791785699734&hl=en&as_sdt=0,5 | 2 | 2,021 |
Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search | 21 | iclr | 6 | 0 | 2023-06-18 09:25:00.595000 | https://github.com/PerdonLiu/CSE-Autoloss | 56 | Loss function discovery for object detection via convergence-simulation driven search | https://scholar.google.com/scholar?cluster=14213953429648652822&hl=en&as_sdt=0,5 | 2 | 2,021 |
Effective Abstract Reasoning with Dual-Contrast Network | 15 | iclr | 1 | 0 | 2023-06-18 09:25:00.798000 | https://github.com/visiontao/dcnet | 9 | Effective abstract reasoning with dual-contrast network | https://scholar.google.com/scholar?cluster=17541928737490000806&hl=en&as_sdt=0,5 | 1 | 2,021 |
Set Prediction without Imposing Structure as Conditional Density Estimation | 9 | iclr | 1 | 0 | 2023-06-18 09:25:01.001000 | https://github.com/davzha/DESP | 5 | Set prediction without imposing structure as conditional density estimation | https://scholar.google.com/scholar?cluster=3129155688534171639&hl=en&as_sdt=0,5 | 1 | 2,021 |
Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation | 49 | iclr | 7 | 4 | 2023-06-18 09:25:01.208000 | https://github.com/TTN-YKK/Clustering_friendly_representation_learning | 48 | Clustering-friendly representation learning via instance discrimination and feature decorrelation | https://scholar.google.com/scholar?cluster=11187160992598838223&hl=en&as_sdt=0,5 | 2 | 2,021 |
Language-Agnostic Representation Learning of Source Code from Structure and Context | 95 | iclr | 29 | 3 | 2023-06-18 09:25:01.412000 | https://github.com/danielzuegner/code-transformer | 147 | Language-agnostic representation learning of source code from structure and context | https://scholar.google.com/scholar?cluster=4574202408084137820&hl=en&as_sdt=0,5 | 9 | 2,021 |
Training GANs with Stronger Augmentations via Contrastive Discriminator | 48 | iclr | 25 | 1 | 2023-06-18 09:25:01.615000 | https://github.com/jh-jeong/ContraD | 182 | Training gans with stronger augmentations via contrastive discriminator | https://scholar.google.com/scholar?cluster=14845144713420069894&hl=en&as_sdt=0,5 | 11 | 2,021 |
Continual learning in recurrent neural networks | 25 | iclr | 6 | 0 | 2023-06-18 09:25:01.834000 | https://github.com/mariacer/cl_in_rnns | 34 | Continual learning in recurrent neural networks | https://scholar.google.com/scholar?cluster=11490619605153761902&hl=en&as_sdt=0,15 | 6 | 2,021 |
A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention | 32 | iclr | 12 | 4 | 2023-06-18 09:25:02.038000 | https://github.com/claying/OTK | 99 | A trainable optimal transport embedding for feature aggregation and its relationship to attention | https://scholar.google.com/scholar?cluster=10719309701133188267&hl=en&as_sdt=0,31 | 3 | 2,021 |
Noise or Signal: The Role of Image Backgrounds in Object Recognition | 227 | iclr | 15 | 2 | 2023-06-18 09:25:02.241000 | https://github.com/MadryLab/backgrounds_challenge | 125 | Noise or signal: The role of image backgrounds in object recognition | https://scholar.google.com/scholar?cluster=14729938011425134088&hl=en&as_sdt=0,33 | 8 | 2,021 |
Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation | 56 | iclr | 2 | 7 | 2023-06-18 09:25:02.446000 | https://github.com/KelestZ/Latent2im | 43 | Enjoy your editing: Controllable gans for image editing via latent space navigation | https://scholar.google.com/scholar?cluster=15259069119096220128&hl=en&as_sdt=0,47 | 4 | 2,021 |
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models | 141 | iclr | 8 | 4 | 2023-06-18 09:25:02.659000 | https://github.com/cassidylaidlaw/perceptual-advex | 50 | Perceptual adversarial robustness: Defense against unseen threat models | https://scholar.google.com/scholar?cluster=8526799141352056555&hl=en&as_sdt=0,5 | 2 | 2,021 |
Zero-Cost Proxies for Lightweight NAS | 148 | iclr | 15 | 7 | 2023-06-18 09:25:02.865000 | https://github.com/mohsaied/zero-cost-nas | 132 | Zero-cost proxies for lightweight nas | https://scholar.google.com/scholar?cluster=9734890465405015230&hl=en&as_sdt=0,33 | 8 | 2,021 |
Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit | 12 | iclr | 178 | 119 | 2023-06-18 09:25:03.069000 | https://github.com/google/uncertainty-baselines | 1,244 | Exploring the uncertainty properties of neural networks' implicit priors in the infinite-width limit | https://scholar.google.com/scholar?cluster=4194918161901179822&hl=en&as_sdt=0,48 | 20 | 2,021 |
DC3: A learning method for optimization with hard constraints | 75 | iclr | 15 | 1 | 2023-06-18 09:25:03.272000 | https://github.com/locuslab/DC3 | 86 | DC3: A learning method for optimization with hard constraints | https://scholar.google.com/scholar?cluster=2253295560281589124&hl=en&as_sdt=0,5 | 5 | 2,021 |
Shape-Texture Debiased Neural Network Training | 78 | iclr | 9 | 2 | 2023-06-18 09:25:03.477000 | https://github.com/LiYingwei/ShapeTextureDebiasedTraining | 104 | Shape-texture debiased neural network training | https://scholar.google.com/scholar?cluster=13815083807768708857&hl=en&as_sdt=0,5 | 6 | 2,021 |
Model Patching: Closing the Subgroup Performance Gap with Data Augmentation | 78 | iclr | 4 | 1 | 2023-06-18 09:25:03.680000 | https://github.com/HazyResearch/model-patching | 40 | Model patching: Closing the subgroup performance gap with data augmentation | https://scholar.google.com/scholar?cluster=501938357242145399&hl=en&as_sdt=0,44 | 17 | 2,021 |
Linear Mode Connectivity in Multitask and Continual Learning | 59 | iclr | 1 | 0 | 2023-06-18 09:25:03.885000 | https://github.com/imirzadeh/MC-SGD | 9 | Linear mode connectivity in multitask and continual learning | https://scholar.google.com/scholar?cluster=10468811797723946398&hl=en&as_sdt=0,48 | 3 | 2,021 |
Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures | 32 | iclr | 8 | 3 | 2023-06-18 09:25:04.089000 | https://github.com/phermosilla/IEConv_proteins | 41 | Intrinsic-extrinsic convolution and pooling for learning on 3d protein structures | https://scholar.google.com/scholar?cluster=10539365407241907053&hl=en&as_sdt=0,5 | 3 | 2,021 |
AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights | 99 | iclr | 53 | 0 | 2023-06-18 09:25:04.292000 | https://github.com/clovaai/AdamP | 397 | Adamp: Slowing down the slowdown for momentum optimizers on scale-invariant weights | https://scholar.google.com/scholar?cluster=6696661613902754889&hl=en&as_sdt=0,5 | 13 | 2,021 |
MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering | 32 | iclr | 7 | 2 | 2023-06-18 09:25:04.495000 | https://github.com/TsungWeiTsai/MiCE | 44 | Mice: Mixture of contrastive experts for unsupervised image clustering | https://scholar.google.com/scholar?cluster=16325984607726397092&hl=en&as_sdt=0,5 | 1 | 2,021 |
Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose? | 9 | iclr | 1 | 0 | 2023-06-18 09:25:04.699000 | https://github.com/ramp-kits/rl_simulator | 12 | Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose? | https://scholar.google.com/scholar?cluster=13333175726397843154&hl=en&as_sdt=0,33 | 10 | 2,021 |
Private Image Reconstruction from System Side Channels Using Generative Models | 2 | iclr | 1 | 0 | 2023-06-18 09:25:04.902000 | https://github.com/genSCA/genSCA | 3 | Private image reconstruction from system side channels using generative models | https://scholar.google.com/scholar?cluster=2761181288645087029&hl=en&as_sdt=0,33 | 2 | 2,021 |
IOT: Instance-wise Layer Reordering for Transformer Structures | 4 | iclr | 1 | 0 | 2023-06-18 09:25:05.106000 | https://github.com/instance-wise-ordered-transformer/IOT | 19 | IoT: Instance-wise layer reordering for transformer structures | https://scholar.google.com/scholar?cluster=5895076023042170097&hl=en&as_sdt=0,5 | 2 | 2,021 |
Counterfactual Generative Networks | 88 | iclr | 24 | 3 | 2023-06-18 09:25:05.309000 | https://github.com/autonomousvision/counterfactual_generative_networks | 94 | Counterfactual generative networks | https://scholar.google.com/scholar?cluster=445809661981357040&hl=en&as_sdt=0,33 | 8 | 2,021 |
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data | 54 | iclr | 11 | 1 | 2023-06-18 09:25:05.512000 | https://github.com/CAMTL/CA-MTL | 48 | Conditionally adaptive multi-task learning: Improving transfer learning in nlp using fewer parameters & less data | https://scholar.google.com/scholar?cluster=814007091936446416&hl=en&as_sdt=0,33 | 3 | 2,021 |
Domain-Robust Visual Imitation Learning with Mutual Information Constraints | 5 | iclr | 2 | 0 | 2023-06-18 09:25:05.715000 | https://github.com/Aladoro/domain-robust-visual-il | 11 | Domain-robust visual imitation learning with mutual information constraints | https://scholar.google.com/scholar?cluster=18023915525010137640&hl=en&as_sdt=0,5 | 1 | 2,021 |
Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding | 82 | iclr | 15 | 8 | 2023-06-18 09:25:05.919000 | https://github.com/sanatonek/TNC_representation_learning | 86 | Unsupervised representation learning for time series with temporal neighborhood coding | https://scholar.google.com/scholar?cluster=12306257235943010010&hl=en&as_sdt=0,6 | 1 | 2,021 |
Enforcing robust control guarantees within neural network policies | 58 | iclr | 10 | 0 | 2023-06-18 09:25:06.123000 | https://github.com/locuslab/robust-nn-control | 48 | Enforcing robust control guarantees within neural network policies | https://scholar.google.com/scholar?cluster=18128961654135874405&hl=en&as_sdt=0,33 | 7 | 2,021 |
Active Contrastive Learning of Audio-Visual Video Representations | 57 | iclr | 5 | 2 | 2023-06-18 09:25:06.327000 | https://github.com/yunyikristy/CM-ACC | 18 | Active contrastive learning of audio-visual video representations | https://scholar.google.com/scholar?cluster=1763906632624707840&hl=en&as_sdt=0,26 | 3 | 2,021 |
Efficient Wasserstein Natural Gradients for Reinforcement Learning | 12 | iclr | 3 | 0 | 2023-06-18 09:25:06.533000 | https://github.com/tedmoskovitz/WNPG | 9 | Efficient wasserstein natural gradients for reinforcement learning | https://scholar.google.com/scholar?cluster=18097668228161879279&hl=en&as_sdt=0,5 | 1 | 2,021 |
Probing BERT in Hyperbolic Spaces | 19 | iclr | 5 | 0 | 2023-06-18 09:25:06.736000 | https://github.com/FranxYao/PoincareProbe | 43 | Probing BERT in hyperbolic spaces | https://scholar.google.com/scholar?cluster=17283548434643857820&hl=en&as_sdt=0,5 | 6 | 2,021 |
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning | 29 | iclr | 23 | 1 | 2023-06-18 09:25:06.944000 | https://github.com/wangren09/MetaAdv | 73 | On fast adversarial robustness adaptation in model-agnostic meta-learning | https://scholar.google.com/scholar?cluster=16465003726106659039&hl=en&as_sdt=0,33 | 7 | 2,021 |
Trusted Multi-View Classification | 83 | iclr | 35 | 0 | 2023-06-18 09:25:07.148000 | https://github.com/hanmenghan/TMC | 146 | Trusted multi-view classification | https://scholar.google.com/scholar?cluster=10693215882520722160&hl=en&as_sdt=0,43 | 1 | 2,021 |
i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning | 69 | iclr | 7 | 0 | 2023-06-18 09:25:07.352000 | https://github.com/kibok90/imix | 74 | i-mix: A domain-agnostic strategy for contrastive representation learning | https://scholar.google.com/scholar?cluster=17225673141444543699&hl=en&as_sdt=0,33 | 3 | 2,021 |
Initialization and Regularization of Factorized Neural Layers | 19 | iclr | 5 | 1 | 2023-06-18 09:25:07.556000 | https://github.com/microsoft/fnl_paper | 23 | Initialization and regularization of factorized neural layers | https://scholar.google.com/scholar?cluster=15693677234095389612&hl=en&as_sdt=0,40 | 7 | 2,021 |
Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning | 26 | iclr | 1 | 0 | 2023-06-18 09:25:07.760000 | https://github.com/boschresearch/imax-calibration | 9 | Multi-class uncertainty calibration via mutual information maximization-based binning | https://scholar.google.com/scholar?cluster=10820552692700202554&hl=en&as_sdt=0,49 | 4 | 2,021 |
Neural ODE Processes | 47 | iclr | 7 | 0 | 2023-06-18 09:25:07.964000 | https://github.com/crisbodnar/ndp | 56 | Neural ode processes | https://scholar.google.com/scholar?cluster=12135997685697455587&hl=en&as_sdt=0,5 | 6 | 2,021 |
An Unsupervised Deep Learning Approach for Real-World Image Denoising | 7 | iclr | 4 | 1 | 2023-06-18 09:25:08.168000 | https://github.com/zhengdharia/Unsupervised_denoising | 26 | An unsupervised deep learning approach for real-world image denoising | https://scholar.google.com/scholar?cluster=10223621556329070926&hl=en&as_sdt=0,33 | 1 | 2,021 |
Learning Parametrised Graph Shift Operators | 15 | iclr | 0 | 0 | 2023-06-18 09:25:08.371000 | https://github.com/gdasoulas/pgso | 2 | Learning parametrised graph shift operators | https://scholar.google.com/scholar?cluster=8306422072823409247&hl=en&as_sdt=0,5 | 2 | 2,021 |
Efficient Conformal Prediction via Cascaded Inference with Expanded Admission | 25 | iclr | 4 | 0 | 2023-06-18 09:25:08.575000 | https://github.com/ajfisch/conformal-cascades | 17 | Efficient conformal prediction via cascaded inference with expanded admission | https://scholar.google.com/scholar?cluster=1762284772897717346&hl=en&as_sdt=0,36 | 5 | 2,021 |
GANs Can Play Lottery Tickets Too | 35 | iclr | 7 | 0 | 2023-06-18 09:25:08.778000 | https://github.com/VITA-Group/GAN-LTH | 24 | Gans can play lottery tickets too | https://scholar.google.com/scholar?cluster=1236790394387307114&hl=en&as_sdt=0,5 | 9 | 2,021 |
Adaptive Universal Generalized PageRank Graph Neural Network | 297 | iclr | 24 | 0 | 2023-06-18 09:25:08.982000 | https://github.com/jianhao2016/GPRGNN | 95 | Adaptive universal generalized pagerank graph neural network | https://scholar.google.com/scholar?cluster=17989054169887872189&hl=en&as_sdt=0,33 | 1 | 2,021 |
My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control | 34 | iclr | 2 | 2 | 2023-06-18 09:25:09.185000 | https://github.com/yobibyte/amorpheus | 36 | My body is a cage: the role of morphology in graph-based incompatible control | https://scholar.google.com/scholar?cluster=5888918560420712353&hl=en&as_sdt=0,5 | 3 | 2,021 |
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning | 135 | iclr | 8 | 3 | 2023-06-18 09:25:09.388000 | https://github.com/hongyouc/fedbe | 28 | Fedbe: Making bayesian model ensemble applicable to federated learning | https://scholar.google.com/scholar?cluster=14031237302830163445&hl=en&as_sdt=0,5 | 1 | 2,021 |
MALI: A memory efficient and reverse accurate integrator for Neural ODEs | 38 | iclr | 6 | 1 | 2023-06-18 09:25:09.592000 | https://github.com/juntang-zhuang/TorchDiffEqPack | 39 | Mali: A memory efficient and reverse accurate integrator for neural odes | https://scholar.google.com/scholar?cluster=12010857032543034567&hl=en&as_sdt=0,5 | 1 | 2,021 |
Contrastive Syn-to-Real Generalization | 38 | iclr | 4 | 2 | 2023-06-18 09:25:09.796000 | https://github.com/NVlabs/CSG | 30 | Contrastive syn-to-real generalization | https://scholar.google.com/scholar?cluster=14950252501736329080&hl=en&as_sdt=0,5 | 6 | 2,021 |
Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting | 35 | iclr | 3 | 1 | 2023-06-18 09:25:10 | https://github.com/SaynaEbrahimi/Remembering-for-the-Right-Reasons | 30 | Remembering for the right reasons: Explanations reduce catastrophic forgetting | https://scholar.google.com/scholar?cluster=10259250203808159056&hl=en&as_sdt=0,1 | 4 | 2,021 |
High-Capacity Expert Binary Networks | 46 | iclr | 3 | 0 | 2023-06-18 09:25:10.205000 | https://github.com/1adrianb/expert-binary-networks | 22 | High-capacity expert binary networks | https://scholar.google.com/scholar?cluster=12665350713453943927&hl=en&as_sdt=0,14 | 2 | 2,021 |
Learning What To Do by Simulating the Past | 2 | iclr | 7 | 0 | 2023-06-18 09:25:10.408000 | https://github.com/HumanCompatibleAI/deep-rlsp | 24 | Learning what to do by simulating the past | https://scholar.google.com/scholar?cluster=15331293852960399558&hl=en&as_sdt=0,50 | 8 | 2,021 |
Progressive Skeletonization: Trimming more fat from a network at initialization | 49 | iclr | 1 | 0 | 2023-06-18 09:25:10.612000 | https://github.com/naver/force | 12 | Progressive skeletonization: Trimming more fat from a network at initialization | https://scholar.google.com/scholar?cluster=5929326556429040468&hl=en&as_sdt=0,33 | 5 | 2,021 |
Learning Manifold Patch-Based Representations of Man-Made Shapes | 21 | iclr | 6 | 0 | 2023-06-18 09:25:10.829000 | https://github.com/dmsm/LearningPatches | 25 | Learning manifold patch-based representations of man-made shapes | https://scholar.google.com/scholar?cluster=9102520552228338739&hl=en&as_sdt=0,5 | 4 | 2,021 |
Aligning AI With Shared Human Values | 100 | iclr | 24 | 2 | 2023-06-18 09:25:11.033000 | https://github.com/hendrycks/ethics | 131 | Aligning ai with shared human values | https://scholar.google.com/scholar?cluster=3779881846531532351&hl=en&as_sdt=0,34 | 6 | 2,021 |
Measuring Massive Multitask Language Understanding | 161 | iclr | 40 | 5 | 2023-06-18 09:25:11.240000 | https://github.com/hendrycks/test | 335 | Measuring massive multitask language understanding | https://scholar.google.com/scholar?cluster=17727716530891149102&hl=en&as_sdt=0,5 | 12 | 2,021 |
Towards Robust Neural Networks via Close-loop Control | 13 | iclr | 3 | 0 | 2023-06-18 09:25:11.445000 | https://github.com/zhuotongchen/Towards-Robust-Neural-Networks-via-Close-loop-Control | 12 | Towards robust neural networks via close-loop control | https://scholar.google.com/scholar?cluster=3798545379660922122&hl=en&as_sdt=0,5 | 1 | 2,021 |
Subsets and Splits