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Dataset Distillation using Neural Feature Regression | 24 | neurips | 7 | 1 | 2023-06-16 22:57:54.176000 | https://github.com/yongchao97/FRePo | 28 | Dataset distillation using neural feature regression | https://scholar.google.com/scholar?cluster=15355176449784124932&hl=en&as_sdt=0,33 | 3 | 2,022 |
ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference Time | 7 | neurips | 2 | 0 | 2023-06-16 22:57:54.403000 | https://github.com/snap-stanford/zeroc | 19 | Zeroc: A neuro-symbolic model for zero-shot concept recognition and acquisition at inference time | https://scholar.google.com/scholar?cluster=3612242931318475489&hl=en&as_sdt=0,22 | 44 | 2,022 |
Risk-Driven Design of Perception Systems | 0 | neurips | 1 | 0 | 2023-06-16 22:57:54.614000 | https://github.com/sisl/riskdrivenperception | 3 | Risk-Driven Design of Perception Systems | https://scholar.google.com/scholar?cluster=3006168152104696613&hl=en&as_sdt=0,5 | 4 | 2,022 |
A Simple Approach to Automated Spectral Clustering | 2 | neurips | 0 | 1 | 2023-06-16 22:57:54.825000 | https://github.com/jicongfan/automated-spectral-clustering | 2 | A simple approach to automated spectral clustering | https://scholar.google.com/scholar?cluster=2848547418778533477&hl=en&as_sdt=0,36 | 1 | 2,022 |
Joint Entropy Search for Multi-Objective Bayesian Optimization | 6 | neurips | 1 | 0 | 2023-06-16 22:57:55.036000 | https://github.com/benmltu/jes | 12 | Joint entropy search for multi-objective bayesian optimization | https://scholar.google.com/scholar?cluster=15207167627489331903&hl=en&as_sdt=0,19 | 1 | 2,022 |
Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation | 1 | neurips | 0 | 1 | 2023-06-16 22:57:55.248000 | https://github.com/jpgard/subgroup-robustness-grows-on-trees | 1 | Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation | https://scholar.google.com/scholar?cluster=1553255834314203495&hl=en&as_sdt=0,47 | 1 | 2,022 |
LION: Latent Point Diffusion Models for 3D Shape Generation | 62 | neurips | 32 | 12 | 2023-06-16 22:57:55.460000 | https://github.com/nv-tlabs/LION | 548 | LION: Latent point diffusion models for 3D shape generation | https://scholar.google.com/scholar?cluster=11609382506929684644&hl=en&as_sdt=0,11 | 44 | 2,022 |
MultiGuard: Provably Robust Multi-label Classification against Adversarial Examples | 1 | neurips | 1 | 0 | 2023-06-16 22:57:55.672000 | https://github.com/quwenjie/multiguard | 2 | MultiGuard: Provably Robust Multi-label Classification against Adversarial Examples | https://scholar.google.com/scholar?cluster=16148192613023633792&hl=en&as_sdt=0,22 | 1 | 2,022 |
On Measuring Excess Capacity in Neural Networks | 4 | neurips | 0 | 0 | 2023-06-16 22:57:55.883000 | https://github.com/rkwitt/excess_capacity | 0 | On measuring excess capacity in neural networks | https://scholar.google.com/scholar?cluster=8286514853614308295&hl=en&as_sdt=0,23 | 2 | 2,022 |
Parameter-Efficient Masking Networks | 1 | neurips | 0 | 0 | 2023-06-16 22:57:56.094000 | https://github.com/yueb17/pemn | 14 | Parameter-Efficient Masking Networks | https://scholar.google.com/scholar?cluster=3375567812720133580&hl=en&as_sdt=0,5 | 2 | 2,022 |
End-to-end Symbolic Regression with Transformers | 32 | neurips | 6 | 4 | 2023-06-16 22:57:56.305000 | https://github.com/facebookresearch/symbolicregression | 39 | End-to-end symbolic regression with transformers | https://scholar.google.com/scholar?cluster=13569402473810241669&hl=en&as_sdt=0,44 | 4 | 2,022 |
EcoFormer: Energy-Saving Attention with Linear Complexity | 8 | neurips | 1 | 1 | 2023-06-16 22:57:56.516000 | https://github.com/ziplab/ecoformer | 60 | Ecoformer: Energy-saving attention with linear complexity | https://scholar.google.com/scholar?cluster=12196003903025483137&hl=en&as_sdt=0,48 | 5 | 2,022 |
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time | 13 | neurips | 7 | 6 | 2023-06-16 22:57:56.727000 | https://github.com/huaxiuyao/wild-time | 49 | Wild-time: A benchmark of in-the-wild distribution shift over time | https://scholar.google.com/scholar?cluster=12470744137018985399&hl=en&as_sdt=0,44 | 3 | 2,022 |
HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions | 57 | neurips | 35 | 2 | 2023-06-16 22:57:56.939000 | https://github.com/raoyongming/hornet | 277 | Hornet: Efficient high-order spatial interactions with recursive gated convolutions | https://scholar.google.com/scholar?cluster=12938213222665733645&hl=en&as_sdt=0,44 | 4 | 2,022 |
Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification | 3 | neurips | 0 | 0 | 2023-06-16 22:57:57.150000 | https://github.com/tsuchhiii/fixed-budget-bai | 1 | Minimax optimal algorithms for fixed-budget best arm identification | https://scholar.google.com/scholar?cluster=2208314113749435910&hl=en&as_sdt=0,34 | 1 | 2,022 |
Reduced Representation of Deformation Fields for Effective Non-rigid Shape Matching | 0 | neurips | 2 | 0 | 2023-06-16 22:57:57.360000 | https://github.com/sentient07/deformationbasis | 9 | Reduced Representation of Deformation Fields for Effective Non-rigid Shape Matching | https://scholar.google.com/scholar?cluster=6711357441182968462&hl=en&as_sdt=0,10 | 3 | 2,022 |
Automatic Differentiation of Programs with Discrete Randomness | 4 | neurips | 8 | 10 | 2023-06-16 22:57:57.571000 | https://github.com/gaurav-arya/stochasticad.jl | 144 | Automatic differentiation of programs with discrete randomness | https://scholar.google.com/scholar?cluster=4520468158435418424&hl=en&as_sdt=0,5 | 4 | 2,022 |
NS3: Neuro-symbolic Semantic Code Search | 4 | neurips | 0 | 0 | 2023-06-16 22:57:57.782000 | https://github.com/shushanarakelyan/modular_code_search | 3 | NS3: Neuro-symbolic semantic code search | https://scholar.google.com/scholar?cluster=12732470567380886921&hl=en&as_sdt=0,5 | 1 | 2,022 |
Revisiting Sparse Convolutional Model for Visual Recognition | 2 | neurips | 6 | 2 | 2023-06-16 22:57:57.994000 | https://github.com/delay-xili/sdnet | 111 | Revisiting sparse convolutional model for visual recognition | https://scholar.google.com/scholar?cluster=7681982241768438501&hl=en&as_sdt=0,7 | 9 | 2,022 |
BackdoorBench: A Comprehensive Benchmark of Backdoor Learning | 28 | neurips | 24 | 4 | 2023-06-16 22:57:58.206000 | https://github.com/sclbd/backdoorbench | 162 | Backdoorbench: A comprehensive benchmark of backdoor learning | https://scholar.google.com/scholar?cluster=13477998480458836443&hl=en&as_sdt=0,5 | 3 | 2,022 |
REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering | 12 | neurips | 1 | 0 | 2023-06-16 22:57:58.423000 | https://github.com/yzleroy/revive | 19 | Revive: Regional visual representation matters in knowledge-based visual question answering | https://scholar.google.com/scholar?cluster=15826539500910476875&hl=en&as_sdt=0,33 | 8 | 2,022 |
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation | 3 | neurips | 0 | 0 | 2023-06-16 22:57:58.634000 | https://github.com/peidehuang/gradient | 5 | Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation | https://scholar.google.com/scholar?cluster=13844074007413994501&hl=en&as_sdt=0,4 | 3 | 2,022 |
Symbolic Distillation for Learned TCP Congestion Control | 0 | neurips | 0 | 1 | 2023-06-16 22:57:58.846000 | https://github.com/vita-group/symbolicpcc | 6 | Symbolic Distillation for Learned TCP Congestion Control | https://scholar.google.com/scholar?cluster=13401562754080828114&hl=en&as_sdt=0,5 | 9 | 2,022 |
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees | 1 | neurips | 1 | 0 | 2023-06-16 22:57:59.056000 | https://github.com/d-tiapkin/optimistic-psrl-experiments | 0 | Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees | https://scholar.google.com/scholar?cluster=12169857257765503180&hl=en&as_sdt=0,6 | 1 | 2,022 |
Can Push-forward Generative Models Fit Multimodal Distributions? | 6 | neurips | 0 | 0 | 2023-06-16 22:57:59.278000 | https://github.com/antoinesalmona/push-forward-generative-models | 1 | Can Push-forward Generative Models Fit Multimodal Distributions? | https://scholar.google.com/scholar?cluster=15185434637554418912&hl=en&as_sdt=0,5 | 1 | 2,022 |
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination | 19 | neurips | 4 | 1 | 2023-06-16 22:57:59.493000 | https://github.com/zyzisastudyreallyhardguy/graph-group-discrimination | 43 | Rethinking and scaling up graph contrastive learning: An extremely efficient approach with group discrimination | https://scholar.google.com/scholar?cluster=13490371651179732416&hl=en&as_sdt=0,5 | 2 | 2,022 |
Diverse Weight Averaging for Out-of-Distribution Generalization | 21 | neurips | 5 | 0 | 2023-06-16 22:57:59.704000 | https://github.com/alexrame/diwa | 16 | Diverse weight averaging for out-of-distribution generalization | https://scholar.google.com/scholar?cluster=5971058245242972538&hl=en&as_sdt=0,14 | 2 | 2,022 |
Posterior and Computational Uncertainty in Gaussian Processes | 2 | neurips | 0 | 0 | 2023-06-16 22:57:59.916000 | https://github.com/jonathanwenger/itergp | 24 | Posterior and Computational Uncertainty in Gaussian Processes | https://scholar.google.com/scholar?cluster=10582501668199508293&hl=en&as_sdt=0,10 | 2 | 2,022 |
Understanding the Evolution of Linear Regions in Deep Reinforcement Learning | 0 | neurips | 1 | 0 | 2023-06-16 22:58:00.127000 | https://github.com/setarehc/deep_rl_regions | 1 | Understanding the Evolution of Linear Regions in Deep Reinforcement Learning | https://scholar.google.com/scholar?cluster=11513659328041109175&hl=en&as_sdt=0,34 | 1 | 2,022 |
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis | 7 | neurips | 0 | 0 | 2023-06-16 22:58:00.338000 | https://github.com/rflperry/sparse_shift | 6 | Causal discovery in heterogeneous environments under the sparse mechanism shift hypothesis | https://scholar.google.com/scholar?cluster=13871332689539937340&hl=en&as_sdt=0,23 | 2 | 2,022 |
Towards Practical Control of Singular Values of Convolutional Layers | 2 | neurips | 1 | 0 | 2023-06-16 22:58:00.549000 | https://github.com/whiteteadragon/practical_svd_conv | 4 | Towards practical control of singular values of convolutional layers | https://scholar.google.com/scholar?cluster=1506769972607423712&hl=en&as_sdt=0,14 | 2 | 2,022 |
PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds | 12 | neurips | 9 | 3 | 2023-06-16 22:58:00.760000 | https://github.com/xiaoaoran/polarmix | 41 | PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds | https://scholar.google.com/scholar?cluster=2359394852358979496&hl=en&as_sdt=0,5 | 6 | 2,022 |
Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees | 1 | neurips | 1 | 3 | 2023-06-16 22:58:00.972000 | https://github.com/jjbrophy47/ibug | 20 | Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees | https://scholar.google.com/scholar?cluster=4132673829192129135&hl=en&as_sdt=0,33 | 5 | 2,022 |
AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos | 8 | neurips | 24 | 5 | 2023-06-16 22:58:01.183000 | https://github.com/tencentarc/animesr | 230 | AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos | https://scholar.google.com/scholar?cluster=3700240933025394368&hl=en&as_sdt=0,19 | 17 | 2,022 |
Fairness Transferability Subject to Bounded Distribution Shift | 13 | neurips | 0 | 0 | 2023-06-16 22:58:01.416000 | https://github.com/ucsc-real/fairness_transferability | 2 | Fairness transferability subject to bounded distribution shift | https://scholar.google.com/scholar?cluster=15393835531531070174&hl=en&as_sdt=0,44 | 0 | 2,022 |
Improving Self-Supervised Learning by Characterizing Idealized Representations | 11 | neurips | 3 | 1 | 2023-06-16 22:58:01.627000 | https://github.com/yanndubs/invariant-self-supervised-learning | 34 | Improving self-supervised learning by characterizing idealized representations | https://scholar.google.com/scholar?cluster=6601803486555515746&hl=en&as_sdt=0,1 | 1 | 2,022 |
On the difficulty of learning chaotic dynamics with RNNs | 4 | neurips | 0 | 0 | 2023-06-16 22:58:01.839000 | https://github.com/durstewitzlab/chaosrnn | 3 | On the difficulty of learning chaotic dynamics with RNNs | https://scholar.google.com/scholar?cluster=1853395383421685801&hl=en&as_sdt=0,39 | 1 | 2,022 |
SKFlow: Learning Optical Flow with Super Kernels | 10 | neurips | 1 | 0 | 2023-06-16 22:58:02.050000 | https://github.com/littlespray/SKFlow | 29 | SKFlow: Learning Optical Flow with Super Kernels | https://scholar.google.com/scholar?cluster=5401118479575242953&hl=en&as_sdt=0,33 | 2 | 2,022 |
End-to-end Stochastic Optimization with Energy-based Model | 0 | neurips | 0 | 0 | 2023-06-16 22:58:02.261000 | https://github.com/Lingkai-Kong/SO-EBM | 8 | End-to-End Stochastic Optimization with Energy-Based Model | https://scholar.google.com/scholar?cluster=7358543026013028300&hl=en&as_sdt=0,44 | 2 | 2,022 |
Wasserstein $K$-means for clustering probability distributions | 6 | neurips | 0 | 0 | 2023-06-16 22:58:02.474000 | https://github.com/yubo02/wasserstein-k-means-for-clustering-probability-distributions | 6 | Wasserstein -means for clustering probability distributions | https://scholar.googleusercontent.com/scholar?q=cache:S92oB8p7PW0J:scholar.google.com/+Wasserstein+%24K%24-means+for+clustering+probability+distributions&hl=en&as_sdt=0,5 | 1 | 2,022 |
MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields | 44 | neurips | 50 | 22 | 2023-06-16 22:58:02.685000 | https://github.com/ACEsuit/mace | 161 | MACE: Higher order equivariant message passing neural networks for fast and accurate force fields | https://scholar.google.com/scholar?cluster=14632576704960076515&hl=en&as_sdt=0,33 | 17 | 2,022 |
Tenrec: A Large-scale Multipurpose Benchmark Dataset for Recommender Systems | 0 | neurips | 20 | 13 | 2023-06-16 22:58:02.896000 | https://github.com/yuangh-x/2022-nips-tenrec | 125 | Tenrec: A Large-scale Multipurpose Benchmark Dataset for Recommender Systems | https://scholar.google.com/scholar?cluster=17000003816321898501&hl=en&as_sdt=0,50 | 2 | 2,022 |
S2P: State-conditioned Image Synthesis for Data Augmentation in Offline Reinforcement Learning | 2 | neurips | 1 | 2 | 2023-06-16 22:58:03.107000 | https://github.com/dsshim0125/s2p | 2 | S2P: State-conditioned Image Synthesis for Data Augmentation in Offline Reinforcement Learning | https://scholar.google.com/scholar?cluster=10891821671072337532&hl=en&as_sdt=0,6 | 1 | 2,022 |
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold | 9 | neurips | 0 | 0 | 2023-06-16 22:58:03.318000 | https://github.com/cjyaras/normalized-neural-collapse | 1 | Neural collapse with normalized features: A geometric analysis over the riemannian manifold | https://scholar.google.com/scholar?cluster=184799387067688052&hl=en&as_sdt=0,5 | 1 | 2,022 |
Conformalized Fairness via Quantile Regression | 1 | neurips | 1 | 0 | 2023-06-16 22:58:03.529000 | https://github.com/lei-ding07/conformal_quantile_fairness | 4 | Conformalized Fairness via Quantile Regression | https://scholar.google.com/scholar?cluster=13625755204473996808&hl=en&as_sdt=0,23 | 1 | 2,022 |
Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces | 1 | neurips | 0 | 0 | 2023-06-16 22:58:03.740000 | https://github.com/leoiv/baxus | 6 | Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces | https://scholar.google.com/scholar?cluster=16209973749760389058&hl=en&as_sdt=0,5 | 1 | 2,022 |
Evolution of Neural Tangent Kernels under Benign and Adversarial Training | 5 | neurips | 0 | 0 | 2023-06-16 22:58:03.951000 | https://github.com/yolky/adversarial_ntk_evolution | 3 | Evolution of neural tangent kernels under benign and adversarial training | https://scholar.google.com/scholar?cluster=10465513161130337378&hl=en&as_sdt=0,34 | 1 | 2,022 |
Zero-Sum Stochastic Stackelberg Games | 1 | neurips | 1 | 0 | 2023-06-16 22:58:04.162000 | https://github.com/sadie-zhao/zero-sum-stochastic-stackelberg-games-neurips | 9 | Zero-Sum Stochastic Stackelberg Games | https://scholar.google.com/scholar?cluster=16214046013626830778&hl=en&as_sdt=0,5 | 2 | 2,022 |
Evaluating Out-of-Distribution Performance on Document Image Classifiers | 0 | neurips | 0 | 0 | 2023-06-16 22:58:04.402000 | https://github.com/gxlarson/rvl-cdip-ood | 3 | Evaluating Out-of-Distribution Performance on Document Image Classifiers | https://scholar.google.com/scholar?cluster=6783517671736097904&hl=en&as_sdt=0,39 | 1 | 2,022 |
Spatial Mixture-of-Experts | 1 | neurips | 0 | 0 | 2023-06-16 22:58:04.613000 | https://github.com/spcl/smoe | 6 | Spatial Mixture-of-Experts | https://scholar.google.com/scholar?cluster=14828485216186842836&hl=en&as_sdt=0,44 | 7 | 2,022 |
Hilbert Distillation for Cross-Dimensionality Networks | 0 | neurips | 0 | 0 | 2023-06-16 22:58:04.824000 | https://github.com/EagleMIT/Hilbert-Distillation | 2 | Hilbert Distillation for Cross-Dimensionality Networks | https://scholar.google.com/scholar?cluster=12406023256328088160&hl=en&as_sdt=0,14 | 1 | 2,022 |
LIFT: Language-Interfaced Fine-Tuning for Non-language Machine Learning Tasks | 13 | neurips | 6 | 4 | 2023-06-16 22:58:05.035000 | https://github.com/uw-madison-lee-lab/languageinterfacedfinetuning | 74 | Lift: Language-interfaced fine-tuning for non-language machine learning tasks | https://scholar.google.com/scholar?cluster=15884163467852791519&hl=en&as_sdt=0,44 | 5 | 2,022 |
Template based Graph Neural Network with Optimal Transport Distances | 2 | neurips | 0 | 2 | 2023-06-16 22:58:05.247000 | https://github.com/cedricvincentcuaz/TFGW | 1 | Template based graph neural network with optimal transport distances | https://scholar.google.com/scholar?cluster=10849560620712329134&hl=en&as_sdt=0,5 | 2 | 2,022 |
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations | 2 | neurips | 1 | 0 | 2023-06-16 22:58:05.458000 | https://github.com/dem123456789/gal-gradient-assisted-learning-for-decentralized-multi-organization-collaborations | 5 | GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations | https://scholar.google.com/scholar?cluster=14405130347379679970&hl=en&as_sdt=0,5 | 2 | 2,022 |
Direct Advantage Estimation | 3 | neurips | 1 | 0 | 2023-06-16 22:58:05.670000 | https://github.com/hrpan/dae | 4 | Direct advantage estimation | https://scholar.google.com/scholar?cluster=723226367131333982&hl=en&as_sdt=0,19 | 3 | 2,022 |
Honor of Kings Arena: an Environment for Generalization in Competitive Reinforcement Learning | 5 | neurips | 58 | 8 | 2023-06-16 22:58:05.880000 | https://github.com/tencent-ailab/hok_env | 438 | Honor of kings arena: an environment for generalization in competitive reinforcement learning | https://scholar.google.com/scholar?cluster=547818193126660523&hl=en&as_sdt=0,5 | 12 | 2,022 |
TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets | 1 | neurips | 3 | 0 | 2023-06-16 22:58:06.091000 | https://github.com/google-research/tabnas | 6 | TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets | https://scholar.google.com/scholar?cluster=8517070308098238947&hl=en&as_sdt=0,5 | 4 | 2,022 |
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification | 0 | neurips | 0 | 0 | 2023-06-16 22:58:06.304000 | https://github.com/roxie62/embed-and-emulate | 5 | Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification | https://scholar.google.com/scholar?cluster=8584482491663793021&hl=en&as_sdt=0,43 | 1 | 2,022 |
Dict-TTS: Learning to Pronounce with Prior Dictionary Knowledge for Text-to-Speech | 3 | neurips | 9 | 1 | 2023-06-16 22:58:06.516000 | https://github.com/zain-jiang/dict-tts | 120 | Dict-tts: Learning to pronounce with prior dictionary knowledge for text-to-speech | https://scholar.google.com/scholar?cluster=18386504940057315518&hl=en&as_sdt=0,5 | 7 | 2,022 |
Task-Agnostic Graph Explanations | 9 | neurips | 239 | 19 | 2023-06-16 22:58:06.726000 | https://github.com/divelab/DIG | 1,503 | Task-agnostic graph explanations | https://scholar.google.com/scholar?cluster=17298628046382170776&hl=en&as_sdt=0,5 | 33 | 2,022 |
Embrace the Gap: VAEs Perform Independent Mechanism Analysis | 4 | neurips | 0 | 0 | 2023-06-16 22:58:06.938000 | https://github.com/rpatrik96/ima-vae | 19 | Embrace the Gap: VAEs Perform Independent Mechanism Analysis | https://scholar.google.com/scholar?cluster=2566376193853302421&hl=en&as_sdt=0,14 | 3 | 2,022 |
Improved Feature Distillation via Projector Ensemble | 4 | neurips | 3 | 0 | 2023-06-16 22:58:07.150000 | https://github.com/chenyd7/pefd | 18 | Improved Feature Distillation via Projector Ensemble | https://scholar.google.com/scholar?cluster=7163318270535099201&hl=en&as_sdt=0,45 | 1 | 2,022 |
Introspective Learning : A Two-Stage approach for Inference in Neural Networks | 6 | neurips | 1 | 0 | 2023-06-16 22:58:07.362000 | https://github.com/olivesgatech/introspective-learning | 4 | Introspective learning: A two-stage approach for inference in neural networks | https://scholar.google.com/scholar?cluster=16860968089703315753&hl=en&as_sdt=0,5 | 5 | 2,022 |
Bayesian Active Learning with Fully Bayesian Gaussian Processes | 5 | neurips | 1 | 0 | 2023-06-16 22:58:07.574000 | https://github.com/CoRiis/active-learning-fbgp | 3 | Bayesian active learning with fully Bayesian Gaussian processes | https://scholar.google.com/scholar?cluster=7248161076733979181&hl=en&as_sdt=0,39 | 1 | 2,022 |
In Defense of the Unitary Scalarization for Deep Multi-Task Learning | 25 | neurips | 1 | 0 | 2023-06-16 22:58:07.786000 | https://github.com/yobibyte/unitary-scalarization-dmtl | 12 | In defense of the unitary scalarization for deep multi-task learning | https://scholar.google.com/scholar?cluster=11217111018249719675&hl=en&as_sdt=0,5 | 2 | 2,022 |
Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction | 0 | neurips | 1 | 0 | 2023-06-16 22:58:07.998000 | https://github.com/uoft-ecosystem/tempo | 13 | Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction | https://scholar.google.com/scholar?cluster=4376824659528049474&hl=en&as_sdt=0,14 | 1 | 2,022 |
AD-DROP: Attribution-Driven Dropout for Robust Language Model Fine-Tuning | 0 | neurips | 1 | 0 | 2023-06-16 22:58:08.224000 | https://github.com/taoyang225/ad-drop | 17 | AD-DROP: Attribution-Driven Dropout for Robust Language Model Fine-Tuning | https://scholar.google.com/scholar?cluster=15838069514720957159&hl=en&as_sdt=0,5 | 1 | 2,022 |
Reinforced Genetic Algorithm for Structure-based Drug Design | 7 | neurips | 5 | 1 | 2023-06-16 22:58:08.438000 | https://github.com/futianfan/reinforced-genetic-algorithm | 43 | Reinforced genetic algorithm for structure-based drug design | https://scholar.google.com/scholar?cluster=7318600000502726060&hl=en&as_sdt=0,5 | 1 | 2,022 |
A Variational Edge Partition Model for Supervised Graph Representation Learning | 0 | neurips | 0 | 0 | 2023-06-16 22:58:08.649000 | https://github.com/yh-utmsb/vepm | 3 | A Variational Edge Partition Model for Supervised Graph Representation Learning | https://scholar.google.com/scholar?cluster=13490644048075543667&hl=en&as_sdt=0,5 | 2 | 2,022 |
Learning Optimal Flows for Non-Equilibrium Importance Sampling | 1 | neurips | 0 | 0 | 2023-06-16 22:58:08.861000 | https://github.com/yucaoyc/neis | 2 | Learning optimal flows for non-equilibrium importance sampling | https://scholar.google.com/scholar?cluster=4036926059814968086&hl=en&as_sdt=0,5 | 1 | 2,022 |
NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks | 7 | neurips | 3 | 0 | 2023-06-16 22:58:09.073000 | https://github.com/rtu715/nas-bench-360 | 41 | NAS-bench-360: Benchmarking neural architecture search on diverse tasks | https://scholar.google.com/scholar?cluster=16735333097872491854&hl=en&as_sdt=0,5 | 4 | 2,022 |
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations | 6 | neurips | 1 | 0 | 2023-06-16 22:58:09.285000 | https://github.com/tychovdo/lila | 15 | Invariance learning in deep neural networks with differentiable Laplace approximations | https://scholar.google.com/scholar?cluster=1429247926698502662&hl=en&as_sdt=0,14 | 1 | 2,022 |
QueryPose: Sparse Multi-Person Pose Regression via Spatial-Aware Part-Level Query | 1 | neurips | 6 | 0 | 2023-06-16 22:58:09.497000 | https://github.com/buptxyb666/querypose | 18 | QueryPose: Sparse Multi-Person Pose Regression via Spatial-Aware Part-Level Query | https://scholar.google.com/scholar?cluster=15275535778333612126&hl=en&as_sdt=0,10 | 6 | 2,022 |
EAGER: Asking and Answering Questions for Automatic Reward Shaping in Language-guided RL | 3 | neurips | 0 | 0 | 2023-06-16 22:58:09.714000 | https://github.com/flowersteam/eager | 8 | Eager: Asking and answering questions for automatic reward shaping in language-guided rl | https://scholar.google.com/scholar?cluster=15918390192447267703&hl=en&as_sdt=0,5 | 2 | 2,022 |
OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters | 3 | neurips | 1 | 0 | 2023-06-16 22:58:09.926000 | https://github.com/ellisalicante/openfilter | 4 | OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters | https://scholar.google.com/scholar?cluster=5342281461625207848&hl=en&as_sdt=0,10 | 1 | 2,022 |
Improving Policy Learning via Language Dynamics Distillation | 2 | neurips | 0 | 0 | 2023-06-16 22:58:10.138000 | https://github.com/vzhong/language-dynamics-distillation | 7 | Improving Policy Learning via Language Dynamics Distillation | https://scholar.google.com/scholar?cluster=6541543257718525054&hl=en&as_sdt=0,33 | 1 | 2,022 |
The Neural Testbed: Evaluating Joint Predictions | 6 | neurips | 13 | 2 | 2023-06-16 22:58:10.350000 | https://github.com/deepmind/neural_testbed | 181 | The neural testbed: Evaluating joint predictions | https://scholar.google.com/scholar?cluster=9820249592356438993&hl=en&as_sdt=0,34 | 12 | 2,022 |
Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization | 0 | neurips | 0 | 1 | 2023-06-16 22:58:10.562000 | https://github.com/rehg-lab/dope_selfsup | 9 | Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization | https://scholar.google.com/scholar?cluster=15982502156616388651&hl=en&as_sdt=0,37 | 2 | 2,022 |
Teacher Forcing Recovers Reward Functions for Text Generation | 4 | neurips | 1 | 1 | 2023-06-16 22:58:10.773000 | https://github.com/manga-uofa/lmreward | 16 | Teacher Forcing Recovers Reward Functions for Text Generation | https://scholar.google.com/scholar?cluster=8015164160931191027&hl=en&as_sdt=0,26 | 3 | 2,022 |
Masked Autoencoding for Scalable and Generalizable Decision Making | 6 | neurips | 1 | 0 | 2023-06-16 22:58:10.986000 | https://github.com/fangchenliu/maskdp_public | 24 | Masked Autoencoding for Scalable and Generalizable Decision Making | https://scholar.google.com/scholar?cluster=5876325032505210747&hl=en&as_sdt=0,33 | 1 | 2,022 |
Distributional Reward Estimation for Effective Multi-agent Deep Reinforcement Learning | 0 | neurips | 1 | 1 | 2023-06-16 22:58:11.197000 | https://github.com/jf-hu/dre-marl | 3 | Distributional Reward Estimation for Effective Multi-Agent Deep Reinforcement Learning | https://scholar.google.com/scholar?cluster=4608771757173948810&hl=en&as_sdt=0,44 | 1 | 2,022 |
ELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler | 2 | neurips | 5 | 1 | 2023-06-16 22:58:11.420000 | https://github.com/neurasearch/neurips-2022-submission-3358 | 18 | ELASTIC: numerical reasoning with adaptive symbolic compiler | https://scholar.google.com/scholar?cluster=6782406897046377184&hl=en&as_sdt=0,47 | 1 | 2,022 |
Training Spiking Neural Networks with Local Tandem Learning | 6 | neurips | 0 | 0 | 2023-06-16 22:58:11.632000 | https://github.com/aries231/local_tandem_learning_rule | 4 | Training Spiking Neural Networks with Local Tandem Learning | https://scholar.google.com/scholar?cluster=213134529644040528&hl=en&as_sdt=0,33 | 1 | 2,022 |
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting | 17 | neurips | 4 | 1 | 2023-06-16 22:58:11.844000 | https://github.com/tianzhou2011/FiLM | 59 | Film: Frequency improved legendre memory model for long-term time series forecasting | https://scholar.google.com/scholar?cluster=13865604697725904904&hl=en&as_sdt=0,14 | 1 | 2,022 |
Scalable Neural Video Representations with Learnable Positional Features | 10 | neurips | 3 | 0 | 2023-06-16 22:58:12.056000 | https://github.com/subin-kim-cv/NVP | 54 | Scalable neural video representations with learnable positional features | https://scholar.google.com/scholar?cluster=418170278424044647&hl=en&as_sdt=0,5 | 5 | 2,022 |
Data Augmentation MCMC for Bayesian Inference from Privatized Data | 7 | neurips | 0 | 0 | 2023-06-16 22:58:12.269000 | https://github.com/nianqiaoju/dataaugmentation-mcmc-differentialprivacy | 1 | Data augmentation MCMC for bayesian inference from privatized data | https://scholar.google.com/scholar?cluster=15062825802466844692&hl=en&as_sdt=0,45 | 3 | 2,022 |
Verification and search algorithms for causal DAGs | 3 | neurips | 0 | 0 | 2023-06-16 22:58:12.481000 | https://github.com/cxjdavin/verification-and-search-algorithms-for-causal-dags | 1 | Verification and search algorithms for causal DAGs | https://scholar.google.com/scholar?cluster=5973326212150461189&hl=en&as_sdt=0,49 | 1 | 2,022 |
Learning Equivariant Segmentation with Instance-Unique Querying | 12 | neurips | 0 | 4 | 2023-06-16 22:58:12.693000 | https://github.com/jamesliang819/instance_unique_querying | 20 | Learning Equivariant Segmentation with Instance-Unique Querying | https://scholar.google.com/scholar?cluster=258748143190805226&hl=en&as_sdt=0,5 | 2 | 2,022 |
Make Some Noise: Reliable and Efficient Single-Step Adversarial Training | 10 | neurips | 2 | 1 | 2023-06-16 22:58:12.904000 | https://github.com/pdejorge/n-fgsm | 18 | Make some noise: Reliable and efficient single-step adversarial training | https://scholar.google.com/scholar?cluster=4411689672191629194&hl=en&as_sdt=0,31 | 1 | 2,022 |
Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal | 6 | neurips | 1 | 4 | 2023-06-16 22:58:13.116000 | https://github.com/shiyuchengtju/par | 6 | Decision-based black-box attack against vision transformers via patch-wise adversarial removal | https://scholar.google.com/scholar?cluster=10811327262491458953&hl=en&as_sdt=0,5 | 1 | 2,022 |
Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations | 1 | neurips | 0 | 0 | 2023-06-16 22:58:13.327000 | https://github.com/Laborieux-Axel/holomorphic_eqprop | 6 | Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations | https://scholar.google.com/scholar?cluster=2660045405208851732&hl=en&as_sdt=0,47 | 1 | 2,022 |
LST: Ladder Side-Tuning for Parameter and Memory Efficient Transfer Learning | 27 | neurips | 5 | 3 | 2023-06-16 22:58:13.545000 | https://github.com/ylsung/ladder-side-tuning | 150 | Lst: Ladder side-tuning for parameter and memory efficient transfer learning | https://scholar.google.com/scholar?cluster=5847102735661395022&hl=en&as_sdt=0,5 | 2 | 2,022 |
Amortized Inference for Causal Structure Learning | 5 | neurips | 4 | 0 | 2023-06-16 22:58:13.756000 | https://github.com/larslorch/avici | 30 | Amortized inference for causal structure learning | https://scholar.google.com/scholar?cluster=12367761673759456964&hl=en&as_sdt=0,33 | 1 | 2,022 |
Selective compression learning of latent representations for variable-rate image compression | 1 | neurips | 0 | 0 | 2023-06-16 22:58:13.968000 | https://github.com/jooyoungleeetri/scr | 17 | Selective compression learning of latent representations for variable-rate image compression | https://scholar.google.com/scholar?cluster=13909155481844367559&hl=en&as_sdt=0,11 | 1 | 2,022 |
Multi-LexSum: Real-world Summaries of Civil Rights Lawsuits at Multiple Granularities | 13 | neurips | 0 | 0 | 2023-06-16 22:58:14.181000 | https://github.com/multilexsum/dataset | 15 | Multi-LexSum: Real-World Summaries of Civil Rights Lawsuits at Multiple Granularities | https://scholar.google.com/scholar?cluster=5062559571179489712&hl=en&as_sdt=0,33 | 0 | 2,022 |
Local Bayesian optimization via maximizing probability of descent | 1 | neurips | 0 | 0 | 2023-06-16 22:58:14.425000 | https://github.com/kayween/local-bo-mpd | 6 | Local Bayesian optimization via maximizing probability of descent | https://scholar.google.com/scholar?cluster=3485637555120117353&hl=en&as_sdt=0,44 | 3 | 2,022 |
Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copyright Protection | 14 | neurips | 2 | 1 | 2023-06-16 22:58:14.636000 | https://github.com/thuyimingli/untargeted_backdoor_watermark | 36 | Untargeted backdoor watermark: Towards harmless and stealthy dataset copyright protection | https://scholar.google.com/scholar?cluster=741958679609205316&hl=en&as_sdt=0,18 | 4 | 2,022 |
Learning Symmetric Rules with SATNet | 1 | neurips | 0 | 0 | 2023-06-16 22:58:14.849000 | https://github.com/Lim-Sangho/SymSATNet | 0 | Learning Symmetric Rules with SATNet | https://scholar.google.com/scholar?cluster=13706901058852825985&hl=en&as_sdt=0,5 | 2 | 2,022 |
Langevin Autoencoders for Learning Deep Latent Variable Models | 0 | neurips | 1 | 0 | 2023-06-16 22:58:15.061000 | https://github.com/ishohei220/lae | 5 | Langevin Autoencoders for Learning Deep Latent Variable Models | https://scholar.google.com/scholar?cluster=4451193403290607763&hl=en&as_sdt=0,5 | 1 | 2,022 |
Fault-Aware Neural Code Rankers | 12 | neurips | 5 | 1 | 2023-06-16 22:58:15.272000 | https://github.com/microsoft/coderanker | 22 | Fault-aware neural code rankers | https://scholar.google.com/scholar?cluster=11520887599770538288&hl=en&as_sdt=0,5 | 4 | 2,022 |
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