iclr2020.md

ICLR2020 Paper List

论文	作者	摘要	代码	引用数
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes	Yang You, Jing Li, Sashank J. Reddi, Jonathan Hseu, Sanjiv Kumar, Srinadh Bhojanapalli, Xiaodan Song, James Demmel, Kurt Keutzer, ChoJui Hsieh		code	-1
SELF: Learning to Filter Noisy Labels with Self-Ensembling	Duc Tam Nguyen, Chaithanya Kumar Mummadi, ThiPhuongNhung Ngo, Thi Hoai Phuong Nguyen, Laura Beggel, Thomas Brox		code	-1
Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation	Yu Chen, Lingfei Wu, Mohammed J. Zaki		code	-1
Sharing Knowledge in Multi-Task Deep Reinforcement Learning	Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters		code	-1
On the Weaknesses of Reinforcement Learning for Neural Machine Translation	Leshem Choshen, Lior Fox, Zohar Aizenbud, Omri Abend		code	-1
StructPool: Structured Graph Pooling via Conditional Random Fields	Hao Yuan, Shuiwang Ji		code	-1
Learning deep graph matching with channel-independent embedding and Hungarian attention	Tianshu Yu, Runzhong Wang, Junchi Yan, Baoxin Li		code	-1
Graph inference learning for semi-supervised classification	Chunyan Xu, Zhen Cui, Xiaobin Hong, Tong Zhang, Jian Yang, Wei Liu		code	-1
SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards	Siddharth Reddy, Anca D. Dragan, Sergey Levine		code	-1
Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data	Sergei Popov, Stanislav Morozov, Artem Babenko		code	-1
Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification	Yixiao Ge, Dapeng Chen, Hongsheng Li		code	-1
Automatically Discovering and Learning New Visual Categories with Ranking Statistics	Kai Han, SylvestreAlvise Rebuffi, Sébastien Ehrhardt, Andrea Vedaldi, Andrew Zisserman		code	-1
Maxmin Q-learning: Controlling the Estimation Bias of Q-learning	Qingfeng Lan, Yangchen Pan, Alona Fyshe, Martha White		code	-1
Federated Adversarial Domain Adaptation	Xingchao Peng, Zijun Huang, Yizhe Zhu, Kate Saenko		code	-1
Depth-Adaptive Transformer	Maha Elbayad, Jiatao Gu, Edouard Grave, Michael Auli		code	-1
DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures	Huanrui Yang, Wei Wen, Hai Li		code	-1
Evaluating The Search Phase of Neural Architecture Search	Kaicheng Yu, Christian Sciuto, Martin Jaggi, Claudiu Musat, Mathieu Salzmann		code	-1
Diverse Trajectory Forecasting with Determinantal Point Processes	Ye Yuan, Kris M. Kitani		code	-1
ProxSGD: Training Structured Neural Networks under Regularization and Constraints	Yang Yang, Yaxiong Yuan, Avraam Chatzimichailidis, Ruud J. G. van Sloun, Lei Lei, Symeon Chatzinotas		code	-1
LAMOL: LAnguage MOdeling for Lifelong Language Learning	FanKeng Sun, ChengHao Ho, HungYi Lee		code	-1
Learning Expensive Coordination: An Event-Based Deep RL Approach	Zhenyu Shi, Runsheng Yu, Xinrun Wang, Rundong Wang, Youzhi Zhang, Hanjiang Lai, Bo An		code	-1
Curvature Graph Network	Ze Ye, Kin Sum Liu, Tengfei Ma, Jie Gao, Chao Chen		code	-1
Distance-Based Learning from Errors for Confidence Calibration	Chen Xing, Sercan Ömer Arik, Zizhao Zhang, Tomas Pfister		code	-1
Deep Learning of Determinantal Point Processes via Proper Spectral Sub-gradient	Tianshu Yu, Yikang Li, Baoxin Li		code	-1
N-BEATS: Neural basis expansion analysis for interpretable time series forecasting	Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio		code	-1
Automated Relational Meta-learning	Huaxiu Yao, Xian Wu, Zhiqiang Tao, Yaliang Li, Bolin Ding, Ruirui Li, Zhenhui Li		code	-1
To Relieve Your Headache of Training an MRF, Take AdVIL	Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu, Bo Zhang		code	-1
Linear Symmetric Quantization of Neural Networks for Low-precision Integer Hardware	Xiandong Zhao, Ying Wang, Xuyi Cai, Cheng Liu, Lei Zhang		code	-1
Weakly Supervised Clustering by Exploiting Unique Class Count	Mustafa Umit Oner, Hwee Kuan Lee, WingKin Sung		code	-1
Scalable and Order-robust Continual Learning with Additive Parameter Decomposition	Jaehong Yoon, Saehoon Kim, Eunho Yang, Sung Ju Hwang		code	-1
Continual Learning with Adaptive Weights (CLAW)	Tameem Adel, Han Zhao, Richard E. Turner		code	-1
Transferable Perturbations of Deep Feature Distributions	Nathan Inkawhich, Kevin J. Liang, Lawrence Carin, Yiran Chen		code	-1
A Learning-based Iterative Method for Solving Vehicle Routing Problems	Hao Lu, Xingwen Zhang, Shuang Yang		code	-1
Poly-encoders: Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring	Samuel Humeau, Kurt Shuster, MarieAnne Lachaux, Jason Weston		code	-1
AutoQ: Automated Kernel-Wise Neural Network Quantization	Qian Lou, Feng Guo, Minje Kim, Lantao Liu, Lei Jiang		code	-1
Understanding Architectures Learnt by Cell-based Neural Architecture Search	Yao Shu, Wei Wang, Shaofeng Cai		code	-1
SVQN: Sequential Variational Soft Q-Learning Networks	Shiyu Huang, Hang Su, Jun Zhu, Ting Chen		code	-1
Ranking Policy Gradient	Kaixiang Lin, Jiayu Zhou		code	-1
On Mutual Information Maximization for Representation Learning	Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic		code	-1
Observational Overfitting in Reinforcement Learning	Xingyou Song, Yiding Jiang, Stephen Tu, Yilun Du, Behnam Neyshabur		code	-1
Enhancing Transformation-Based Defenses Against Adversarial Attacks with a Distribution Classifier	Connie Kou, Hwee Kuan Lee, EeChien Chang, Teck Khim Ng		code	-1
Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks	Yuhang Li, Xin Dong, Wei Wang		code	-1
Lazy-CFR: fast and near-optimal regret minimization for extensive games with imperfect information	Yichi Zhou, Tongzheng Ren, Jialian Li, Dong Yan, Jun Zhu		code	-1
Knowledge Consistency between Neural Networks and Beyond	Ruofan Liang, Tianlin Li, Longfei Li, Jing Wang, Quanshi Zhang		code	-1
Image-guided Neural Object Rendering	Justus Thies, Michael Zollhöfer, Christian Theobalt, Marc Stamminger, Matthias Nießner		code	-1
Implicit Bias of Gradient Descent based Adversarial Training on Separable Data	Yan Li, Ethan X. Fang, Huan Xu, Tuo Zhao		code	-1
TabFact: A Large-scale Dataset for Table-based Fact Verification	Wenhu Chen, Hongmin Wang, Jianshu Chen, Yunkai Zhang, Hong Wang, Shiyang Li, Xiyou Zhou, William Yang Wang		code	-1
ES-MAML: Simple Hessian-Free Meta Learning	Xingyou Song, Wenbo Gao, Yuxiang Yang, Krzysztof Choromanski, Aldo Pacchiano, Yunhao Tang		code	-1
Neural Stored-program Memory	Hung Le, Truyen Tran, Svetha Venkatesh		code	-1
Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation	Suraj Nair, Chelsea Finn		code	-1
Multi-agent Reinforcement Learning for Networked System Control	Tianshu Chu, Sandeep Chinchali, Sachin Katti		code	-1
FSPool: Learning Set Representations with Featurewise Sort Pooling	Yan Zhang, Jonathon S. Hare, Adam PrügelBennett		code	-1
Are Pre-trained Language Models Aware of Phrases? Simple but Strong Baselines for Grammar Induction	Taeuk Kim, Jihun Choi, Daniel Edmiston, Sanggoo Lee		code	-1
Dynamically Pruned Message Passing Networks for Large-scale Knowledge Graph Reasoning	Xiaoran Xu, Wei Feng, Yunsheng Jiang, Xiaohui Xie, Zhiqing Sun, ZhiHong Deng		code	-1
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks	Tianyu Pang, Kun Xu, Jun Zhu		code	-1
Theory and Evaluation Metrics for Learning Disentangled Representations	Kien Do, Truyen Tran		code	-1
Measuring Compositional Generalization: A Comprehensive Method on Realistic Data	Daniel Keysers, Nathanael Schärli, Nathan Scales, Hylke Buisman, Daniel Furrer, Sergii Kashubin, Nikola Momchev, Danila Sinopalnikov, Lukasz Stafiniak, Tibor Tihon, Dmitry Tsarkov, Xiao Wang, Marc van Zee, Olivier Bousquet		code	-1
Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness	Tianyu Pang, Kun Xu, Yinpeng Dong, Chao Du, Ning Chen, Jun Zhu		code	-1
The Implicit Bias of Depth: How Incremental Learning Drives Generalization	Daniel Gissin, Shai ShalevShwartz, Amit Daniely		code	-1
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget	Anirudh Goyal, Yoshua Bengio, Matthew M. Botvinick, Sergey Levine		code	-1
Learning the Arrow of Time for Problems in Reinforcement Learning	Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio		code	-1
Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives	Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine, Yoshua Bengio		code	-1
Robust Local Features for Improving the Generalization of Adversarial Training	Chuanbiao Song, Kun He, Jiadong Lin, Liwei Wang, John E. Hopcroft		code	-1
Analysis of Video Feature Learning in Two-Stream CNNs on the Example of Zebrafish Swim Bout Classification	Bennet Breier, Arno Onken		code	-1
Learning Disentangled Representations for CounterFactual Regression	Negar Hassanpour, Russell Greiner		code	-1
Exploration in Reinforcement Learning with Deep Covering Options	Yuu Jinnai, Jee Won Park, Marlos C. Machado, George Dimitri Konidaris		code	-1
Ae-OT: a New Generative Model based on Extended Semi-discrete Optimal transport	Dongsheng An, Yang Guo, Na Lei, Zhongxuan Luo, ShingTung Yau, Xianfeng Gu		code	-1
Logic and the 2-Simplicial Transformer	James Clift, Dmitry Doryn, Daniel Murfet, James Wallbridge		code	-1
Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards	Allan Zhou, Eric Jang, Daniel Kappler, Alexander Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, Chelsea Finn		code	-1
Fooling Detection Alone is Not Enough: Adversarial Attack against Multiple Object Tracking	Yunhan Jia, Yantao Lu, Junjie Shen, Qi Alfred Chen, Hao Chan, Zhenyu Zhong, Tao Wei		code	-1
DivideMix: Learning with Noisy Labels as Semi-supervised Learning	Junnan Li, Richard Socher, Steven C. H. Hoi		code	-1
Improving Adversarial Robustness Requires Revisiting Misclassified Examples	Yisen Wang, Difan Zou, Jinfeng Yi, James Bailey, Xingjun Ma, Quanquan Gu		code	-1
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control	H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W. Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin A. Riedmiller, Matthew M. Botvinick		code	-1
Interpretable Complex-Valued Neural Networks for Privacy Protection	Liyao Xiang, Hao Zhang, Haotian Ma, Yifan Zhang, Jie Ren, Quanshi Zhang		code	-1
Accelerating SGD with momentum for over-parameterized learning	Chaoyue Liu, Mikhail Belkin		code	-1
A critical analysis of self-supervision, or what we can learn from a single image	Yuki Markus Asano, Christian Rupprecht, Andrea Vedaldi		code	-1
Disentangling Factors of Variations Using Few Labels	Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem		code	-1
Functional vs. parametric equivalence of ReLU networks	Mary Phuong, Christoph H. Lampert		code	-1
Input Complexity and Out-of-distribution Detection with Likelihood-based Generative Models	Joan Serrà, David Álvarez, Vicenç Gómez, Olga Slizovskaia, José F. Núñez, Jordi Luque		code	-1
RTFM: Generalising to New Environment Dynamics via Reading	Victor Zhong, Tim Rocktäschel, Edward Grefenstette		code	-1
What graph neural networks cannot learn: depth vs width	Andreas Loukas		code	-1
Progressive Memory Banks for Incremental Domain Adaptation	Nabiha Asghar, Lili Mou, Kira A. Selby, Kevin D. Pantasdo, Pascal Poupart, Xin Jiang		code	-1
Automated curriculum generation through setter-solver interactions	Sébastien Racanière, Andrew K. Lampinen, Adam Santoro, David P. Reichert, Vlad Firoiu, Timothy P. Lillicrap		code	-1
On Identifiability in Transformers	Gino Brunner, Yang Liu, Damian Pascual, Oliver Richter, Massimiliano Ciaramita, Roger Wattenhofer		code	-1
Exploring Model-based Planning with Policy Networks	Tingwu Wang, Jimmy Ba		code	-1
Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling	Yuping Luo, Huazhe Xu, Tengyu Ma		code	-1
Geometric Insights into the Convergence of Nonlinear TD Learning	David Brandfonbrener, Joan Bruna		code	-1
Few-shot Text Classification with Distributional Signatures	Yujia Bao, Menghua Wu, Shiyu Chang, Regina Barzilay		code	-1
Escaping Saddle Points Faster with Stochastic Momentum	JunKun Wang, ChiHeng Lin, Jacob D. Abernethy		code	-1
Adversarial Policies: Attacking Deep Reinforcement Learning	Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, Stuart Russell		code	-1
VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation	Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma		code	-1
GLAD: Learning Sparse Graph Recovery	Harsh Shrivastava, Xinshi Chen, Binghong Chen, Guanghui Lan, Srinivas Aluru, Han Liu, Le Song		code	-1
Pruned Graph Scattering Transforms	Vassilis N. Ioannidis, Siheng Chen, Georgios B. Giannakis		code	-1
Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model	Wenhan Xiong, Jingfei Du, William Yang Wang, Veselin Stoyanov		code	-1
Can gradient clipping mitigate label noise?	Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar		code	-1
Editable Neural Networks	Anton Sinitsin, Vsevolod Plokhotnyuk, Dmitry V. Pyrkin, Sergei Popov, Artem Babenko		code	-1
Learning Execution through Neural Code fusion	Zhan Shi, Kevin Swersky, Daniel Tarlow, Parthasarathy Ranganathan, Milad Hashemi		code	-1
FasterSeg: Searching for Faster Real-time Semantic Segmentation	Wuyang Chen, Xinyu Gong, Xianming Liu, Qian Zhang, Yuan Li, Zhangyang Wang		code	-1
Difference-Seeking Generative Adversarial Network-Unseen Sample Generation	Yi Lin Sung, SungHsien Hsieh, SooChang Pei, ChunShien Lu		code	-1
Stochastic AUC Maximization with Deep Neural Networks	Mingrui Liu, Zhuoning Yuan, Yiming Ying, Tianbao Yang		code	-1
Semantically-Guided Representation Learning for Self-Supervised Monocular Depth	Vitor Guizilini, Rui Hou, Jie Li, Rares Ambrus, Adrien Gaidon		code	-1
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius	Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, ChoJui Hsieh, Liwei Wang		code	-1
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions	Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison W. Cottrell, Geoffrey E. Hinton		code	-1
GAT: Generative Adversarial Training for Adversarial Example Detection and Robust Classification	Xuwang Yin, Soheil Kolouri, Gustavo K. Rohde		code	-1
Variational Recurrent Models for Solving Partially Observable Control Tasks	Dongqi Han, Kenji Doya, Jun Tani		code	-1
Population-Guided Parallel Policy Search for Reinforcement Learning	Whiyoung Jung, Giseung Park, Youngchul Sung		code	-1
Compositional languages emerge in a neural iterated learning model	Yi Ren, Shangmin Guo, Matthieu Labeau, Shay B. Cohen, Simon Kirby		code	-1
Black-Box Adversarial Attack with Transferable Model-based Embedding	Zhichao Huang, Tong Zhang		code	-1
Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models	Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang		code	-1
Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP	Yuanhao Wang, Kefan Dong, Xiaoyu Chen, Liwei Wang		code	-1
Deep Network Classification by Scattering and Homotopy Dictionary Learning	John Zarka, Louis Thiry, Tomás Angles, Stéphane Mallat		code	-1
Data-Independent Neural Pruning via Coresets	Ben Mussay, Margarita Osadchy, Vladimir Braverman, Samson Zhou, Dan Feldman		code	-1
Bounds on Over-Parameterization for Guaranteed Existence of Descent Paths in Shallow ReLU Networks	Arsalan SharifNassab, Saber Salehkaleybar, S. Jamaloddin Golestani		code	-1
Novelty Detection Via Blurring	SungIk Choi, SaeYoung Chung		code	-1
Piecewise linear activations substantially shape the loss surfaces of neural networks	Fengxiang He, Bohan Wang, Dacheng Tao		code	-1
Relational State-Space Model for Stochastic Multi-Object Systems	Fan Yang, Ling Chen, Fan Zhou, Yusong Gao, Wei Cao		code	-1
Learning Efficient Parameter Server Synchronization Policies for Distributed SGD	Rong Zhu, Sheng Yang, Andreas Pfadler, Zhengping Qian, Jingren Zhou		code	-1
Action Semantics Network: Considering the Effects of Actions in Multiagent Systems	Weixun Wang, Tianpei Yang, Yong Liu, Jianye Hao, Xiaotian Hao, Yujing Hu, Yingfeng Chen, Changjie Fan, Yang Gao		code	-1
Vid2Game: Controllable Characters Extracted from Real-World Videos	Oran Gafni, Lior Wolf, Yaniv Taigman		code	-1
Self-Adversarial Learning with Comparative Discrimination for Text Generation	Wangchunshu Zhou, Tao Ge, Ke Xu, Furu Wei, Ming Zhou		code	-1
Robust training with ensemble consensus	Jisoo Lee, SaeYoung Chung		code	-1
Identifying through Flows for Recovering Latent Representations	Shen Li, Bryan Hooi, Gim Hee Lee		code	-1
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing	Jinyuan Jia, Xiaoyu Cao, Binghui Wang, Neil Zhenqiang Gong		code	-1
Optimistic Exploration even with a Pessimistic Initialisation	Tabish Rashid, Bei Peng, Wendelin Boehmer, Shimon Whiteson		code	-1
VL-BERT: Pre-training of Generic Visual-Linguistic Representations	Weijie Su, Xizhou Zhu, Yue Cao, Bin Li, Lewei Lu, Furu Wei, Jifeng Dai		code	-1
Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation	Hang Gao, Xizhou Zhu, Stephen Lin, Jifeng Dai		code	-1
Ensemble Distribution Distillation	Andrey Malinin, Bruno Mlodozeniec, Mark J. F. Gales		code	-1
Gap-Aware Mitigation of Gradient Staleness	Saar Barkai, Ido Hakimi, Assaf Schuster		code	-1
Counterfactuals uncover the modular structure of deep generative models	Michel Besserve, Arash Mehrjou, Rémy Sun, Bernhard Schölkopf		code	-1
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video	Miguel Jaques, Michael Burke, Timothy M. Hospedales		code	-1
An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality	Silviu Pitis, Harris Chan, Kiarash Jamali, Jimmy Ba		code	-1
A Constructive Prediction of the Generalization Error Across Scales	Jonathan S. Rosenfeld, Amir Rosenfeld, Yonatan Belinkov, Nir Shavit		code	-1
Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base	William W. Cohen, Haitian Sun, R. Alex Hofer, Matthew Siegler		code	-1
CLN2INV: Learning Loop Invariants with Continuous Logic Networks	Gabriel Ryan, Justin Wong, Jianan Yao, Ronghui Gu, Suman Jana		code	-1
NAS evaluation is frustratingly hard	Antoine Yang, Pedro M. Esperança, Fabio Maria Carlucci		code	-1
Efficient and Information-Preserving Future Frame Prediction and Beyond	Wei Yu, Yichao Lu, Steve Easterbrook, Sanja Fidler		code	-1
Order Learning and Its Application to Age Estimation	Kyungsun Lim, NyeongHo Shin, YoungYoon Lee, ChangSu Kim		code	-1
ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning	Weihao Yu, Zihang Jiang, Yanfei Dong, Jiashi Feng		code	-1
AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures	Michael S. Ryoo, A. J. Piergiovanni, Mingxing Tan, Anelia Angelova		code	-1
Adversarially Robust Representations with Smooth Encoders	A. Taylan Cemgil, Sumedh Ghaisas, Krishnamurthy (Dj) Dvijotham, Pushmeet Kohli		code	-1
From Variational to Deterministic Autoencoders	Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari, Michael J. Black, Bernhard Schölkopf		code	-1
Computation Reallocation for Object Detection	Feng Liang, Chen Lin, Ronghao Guo, Ming Sun, Wei Wu, Junjie Yan, Wanli Ouyang		code	-1
Finding and Visualizing Weaknesses of Deep Reinforcement Learning Agents	Christian Rupprecht, Cyril Ibrahim, Christopher J. Pal		code	-1
A Fair Comparison of Graph Neural Networks for Graph Classification	Federico Errica, Marco Podda, Davide Bacciu, Alessio Micheli		code	-1
Generalization bounds for deep convolutional neural networks	Philip M. Long, Hanie Sedghi		code	-1
SAdam: A Variant of Adam for Strongly Convex Functions	Guanghui Wang, Shiyin Lu, Quan Cheng, Weiwei Tu, Lijun Zhang		code	-1
Continual Learning with Bayesian Neural Networks for Non-Stationary Data	Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt, Stephan Günnemann		code	-1
Multiplicative Interactions and Where to Find Them	Siddhant M. Jayakumar, Wojciech M. Czarnecki, Jacob Menick, Jonathan Schwarz, Jack W. Rae, Simon Osindero, Yee Whye Teh, Tim Harley, Razvan Pascanu		code	-1
Few-Shot Learning on graphs via super-Classes based on Graph spectral Measures	Jatin Chauhan, Deepak Nathani, Manohar Kaul		code	-1
On Computation and Generalization of Generative Adversarial Imitation Learning	Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao		code	-1
A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning	Shahbaz Rezaei, Xin Liu		code	-1
Low-Resource Knowledge-Grounded Dialogue Generation	Xueliang Zhao, Wei Wu, Chongyang Tao, Can Xu, Dongyan Zhao, Rui Yan		code	-1
Deep 3D Pan via local adaptive "t-shaped" convolutions with global and local adaptive dilations	Juan Luis Gonzalez Bello, Munchurl Kim		code	-1
Tree-Structured Attention with Hierarchical Accumulation	XuanPhi Nguyen, Shafiq R. Joty, Steven C. H. Hoi, Richard Socher		code	-1
The asymptotic spectrum of the Hessian of DNN throughout training	Arthur Jacot, Franck Gabriel, Clément Hongler		code	-1
Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games	Zuyue Fu, Zhuoran Yang, Yongxin Chen, Zhaoran Wang		code	-1
In Search for a SAT-friendly Binarized Neural Network Architecture	Nina Narodytska, Hongce Zhang, Aarti Gupta, Toby Walsh		code	-1
Generative Ratio Matching Networks	Akash Srivastava, Kai Xu, Michael U. Gutmann, Charles Sutton		code	-1
Learning to Represent Programs with Property Signatures	Augustus Odena, Charles Sutton		code	-1
V4D: 4D Convolutional Neural Networks for Video-level Representation Learning	Shiwen Zhang, Sheng Guo, Weilin Huang, Matthew R. Scott, Limin Wang		code	-1
Option Discovery using Deep Skill Chaining	Akhil Bagaria, George Konidaris		code	-1
Quantifying the Cost of Reliable Photo Authentication via High-Performance Learned Lossy Representations	Pawel Korus, Nasir D. Memon		code	-1
On the Variance of the Adaptive Learning Rate and Beyond	Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han		code	-1
Dynamical Distance Learning for Semi-Supervised and Unsupervised Skill Discovery	Kristian Hartikainen, Xinyang Geng, Tuomas Haarnoja, Sergey Levine		code	-1
A Theoretical Analysis of the Number of Shots in Few-Shot Learning	Tianshi Cao, Marc T. Law, Sanja Fidler		code	-1
Unsupervised Model Selection for Variational Disentangled Representation Learning	Sunny Duan, Loic Matthey, Andre Saraiva, Nick Watters, Chris Burgess, Alexander Lerchner, Irina Higgins		code	-1
Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection	Michael Tsang, Dehua Cheng, Hanpeng Liu, Xue Feng, Eric Zhou, Yan Liu		code	-1
Understanding the Limitations of Variational Mutual Information Estimators	Jiaming Song, Stefano Ermon		code	-1
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations	Martin Engelcke, Adam R. Kosiorek, Oiwi Parker Jones, Ingmar Posner		code	-1
Language GANs Falling Short	Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin		code	-1
Stochastic Conditional Generative Networks with Basis Decomposition	Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu		code	-1
Learned Step Size quantization	Steven K. Esser, Jeffrey L. McKinstry, Deepika Bablani, Rathinakumar Appuswamy, Dharmendra S. Modha		code	-1
On the "steerability" of generative adversarial networks	Ali Jahanian, Lucy Chai, Phillip Isola		code	-1
Reinforced active learning for image segmentation	Arantxa Casanova, Pedro O. Pinheiro, Negar Rostamzadeh, Christopher J. Pal		code	-1
Sign Bits Are All You Need for Black-Box Attacks	Abdullah AlDujaili, UnaMay O'Reilly		code	-1
Deep Semi-Supervised Anomaly Detection	Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, KlausRobert Müller, Marius Kloft		code	-1
Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints	Mengtian Li, Ersin Yumer, Deva Ramanan		code	-1
Minimizing FLOPs to Learn Efficient Sparse Representations	Biswajit Paria, ChihKuan Yeh, Ian EnHsu Yen, Ning Xu, Pradeep Ravikumar, Barnabás Póczos		code	-1
Reanalysis of Variance Reduced Temporal Difference Learning	Tengyu Xu, Zhe Wang, Yi Zhou, Yingbin Liang		code	-1
Imitation Learning via Off-Policy Distribution Matching	Ilya Kostrikov, Ofir Nachum, Jonathan Tompson		code	-1
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML	Aniruddh Raghu, Maithra Raghu, Samy Bengio, Oriol Vinyals		code	-1
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space	AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán AspuruGuzik		code	-1
Improved Sample Complexities for Deep Neural Networks and Robust Classification via an All-Layer Margin	Colin Wei, Tengyu Ma		code	-1
Identity Crisis: Memorization and Generalization Under Extreme Overparameterization	Chiyuan Zhang, Samy Bengio, Moritz Hardt, Michael C. Mozer, Yoram Singer		code	-1
ReMixMatch: Semi-Supervised Learning with Distribution Matching and Augmentation Anchoring	David Berthelot, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Kihyuk Sohn, Han Zhang, Colin Raffel		code	-1
Adaptive Structural Fingerprints for Graph Attention Networks	Kai Zhang, Yaokang Zhu, Jun Wang, Jie Zhang		code	-1
CAQL: Continuous Action Q-Learning	Moonkyung Ryu, Yinlam Chow, Ross Anderson, Christian Tjandraatmadja, Craig Boutilier		code	-1
Learning Heuristics for Quantified Boolean Formulas through Reinforcement Learning	Gil Lederman, Markus N. Rabe, Sanjit Seshia, Edward A. Lee		code	-1
Pure and Spurious Critical Points: a Geometric Study of Linear Networks	Matthew Trager, Kathlén Kohn, Joan Bruna		code	-1
Neural Text Generation With Unlikelihood Training	Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, Jason Weston		code	-1
Semi-Supervised Generative Modeling for Controllable Speech Synthesis	Raza Habib, Soroosh Mariooryad, Matt Shannon, Eric Battenberg, R. J. SkerryRyan, Daisy Stanton, David Kao, Tom Bagby		code	-1
Dynamic Time Lag Regression: Predicting What & When	Mandar Chandorkar, Cyril Furtlehner, Bala Poduval, Enrico Camporeale, Michèle Sebag		code	-1
Scalable Model Compression by Entropy Penalized Reparameterization	Deniz Oktay, Johannes Ballé, Saurabh Singh, Abhinav Shrivastava		code	-1
AMRL: Aggregated Memory For Reinforcement Learning	Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann		code	-1
Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform	Jun Li, Fuxin Li, Sinisa Todorovic		code	-1
Unpaired Point Cloud Completion on Real Scans using Adversarial Training	Xuelin Chen, Baoquan Chen, Niloy J. Mitra		code	-1
Adjustable Real-time Style Transfer	Mohammad Babaeizadeh, Golnaz Ghiasi		code	-1
Stochastic Weight Averaging in Parallel: Large-Batch Training That Generalizes Well	Vipul Gupta, Santiago Akle Serrano, Dennis DeCoste		code	-1
Short and Sparse Deconvolution - A Geometric Approach	Yenson Lau, Qing Qu, HanWen Kuo, Pengcheng Zhou, Yuqian Zhang, John Wright		code	-1
Selection via Proxy: Efficient Data Selection for Deep Learning	Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis, Percy Liang, Jure Leskovec, Matei Zaharia		code	-1
Global Relational Models of Source Code	Vincent J. Hellendoorn, Charles Sutton, Rishabh Singh, Petros Maniatis, David Bieber		code	-1
Detecting Extrapolation with Local Ensembles	David Madras, James Atwood, Alexander D'Amour		code	-1
Learning to Link	MariaFlorina Balcan, Travis Dick, Manuel Lang		code	-1
Adversarially robust transfer learning	Ali Shafahi, Parsa Saadatpanah, Chen Zhu, Amin Ghiasi, Christoph Studer, David W. Jacobs, Tom Goldstein		code	-1
Overlearning Reveals Sensitive Attributes	Congzheng Song, Vitaly Shmatikov		code	-1
Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness	Pu Zhao, PinYu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin		code	-1
Differentially Private Meta-Learning	Jeffrey Li, Mikhail Khodak, Sebastian Caldas, Ameet Talwalkar		code	-1
One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum Evaluation	Matthew Shunshi Zhang, Bradly C. Stadie		code	-1
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples	Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Utku Evci, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, PierreAntoine Manzagol, Hugo Larochelle		code	-1
Are Transformers universal approximators of sequence-to-sequence functions?	Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar		code	-1
Pre-training Tasks for Embedding-based Large-scale Retrieval	WeiCheng Chang, Felix X. Yu, YinWen Chang, Yiming Yang, Sanjiv Kumar		code	-1
Deep Imitative Models for Flexible Inference, Planning, and Control	Nicholas Rhinehart, Rowan McAllister, Sergey Levine		code	-1
CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning	Jiachen Yang, Alireza Nakhaei, David Isele, Kikuo Fujimura, Hongyuan Zha		code	-1
Robust And Interpretable Blind Image Denoising Via Bias-Free Convolutional Neural Networks	Sreyas Mohan, Zahra Kadkhodaie, Eero P. Simoncelli, Carlos FernandezGranda		code	-1
Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets	Mingrui Liu, Youssef Mroueh, Jerret Ross, Wei Zhang, Xiaodong Cui, Payel Das, Tianbao Yang		code	-1
DeepV2D: Video to Depth with Differentiable Structure from Motion	Zachary Teed, Jia Deng		code	-1
Learning Space Partitions for Nearest Neighbor Search	Yihe Dong, Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner		code	-1
Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP	Haonan Yu, Sergey Edunov, Yuandong Tian, Ari S. Morcos		code	-1
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack	Minhao Cheng, Simranjit Singh, Patrick H. Chen, PinYu Chen, Sijia Liu, ChoJui Hsieh		code	-1
RaCT: Toward Amortized Ranking-Critical Training For Collaborative Filtering	Sam Lobel, Chunyuan Li, Jianfeng Gao, Lawrence Carin		code	-1
Intrinsic Motivation for Encouraging Synergistic Behavior	Rohan Chitnis, Shubham Tulsiani, Saurabh Gupta, Abhinav Gupta		code	-1
Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation	Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh		code	-1
Recurrent neural circuits for contour detection	Drew Linsley, Junkyung Kim, Alekh Ashok, Thomas Serre		code	-1
Locality and Compositionality in Zero-Shot Learning	Tristan Sylvain, Linda Petrini, R. Devon Hjelm		code	-1
Understanding Knowledge Distillation in Non-autoregressive Machine Translation	Chunting Zhou, Jiatao Gu, Graham Neubig		code	-1
Thieves on Sesame Street! Model Extraction of BERT-based APIs	Kalpesh Krishna, Gaurav Singh Tomar, Ankur P. Parikh, Nicolas Papernot, Mohit Iyyer		code	-1
Fast is better than free: Revisiting adversarial training	Eric Wong, Leslie Rice, J. Zico Kolter		code	-1
DBA: Distributed Backdoor Attacks against Federated Learning	Chulin Xie, Keli Huang, PinYu Chen, Bo Li		code	-1
DeFINE: Deep Factorized Input Token Embeddings for Neural Sequence Modeling	Sachin Mehta, Rik KoncelKedziorski, Mohammad Rastegari, Hannaneh Hajishirzi		code	-1
Sampling-Free Learning of Bayesian Quantized Neural Networks	Jiahao Su, Milan Cvitkovic, Furong Huang		code	-1
Learning to solve the credit assignment problem	Benjamin James Lansdell, Prashanth Ravi Prakash, Konrad Paul Körding		code	-1
Four Things Everyone Should Know to Improve Batch Normalization	Cecilia Summers, Michael J. Dinneen		code	-1
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving	Yurong You, Yan Wang, WeiLun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger		code	-1
SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum	Jianyu Wang, Vinayak Tantia, Nicolas Ballas, Michael G. Rabbat		code	-1
MetaPix: Few-Shot Video Retargeting	Jessica Lee, Deva Ramanan, Rohit Girdhar		code	-1
Learning to Learn by Zeroth-Order Oracle	Yangjun Ruan, Yuanhao Xiong, Sashank J. Reddi, Sanjiv Kumar, ChoJui Hsieh		code	-1
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames	Erik Wijmans, Abhishek Kadian, Ari Morcos, Stefan Lee, Irfan Essa, Devi Parikh, Manolis Savva, Dhruv Batra		code	-1
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction	Sangdon Park, Osbert Bastani, Nikolai Matni, Insup Lee		code	-1
Precision Gating: Improving Neural Network Efficiency with Dynamic Dual-Precision Activations	Yichi Zhang, Ritchie Zhao, Weizhe Hua, Nayun Xu, G. Edward Suh, Zhiru Zhang		code	-1
Oblique Decision Trees from Derivatives of ReLU Networks	GuangHe Lee, Tommi S. Jaakkola		code	-1
Span Recovery for Deep Neural Networks with Applications to Input Obfuscation	Rajesh Jayaram, David P. Woodruff, Qiuyi Zhang		code	-1
Improving Neural Language Generation with Spectrum Control	Lingxiao Wang, Jing Huang, Kevin Huang, Ziniu Hu, Guangtao Wang, Quanquan Gu		code	-1
Learn to Explain Efficiently via Neural Logic Inductive Learning	Yuan Yang, Le Song		code	-1
Improved memory in recurrent neural networks with sequential non-normal dynamics	A. Emin Orhan, Xaq Pitkow		code	-1
Neural Module Networks for Reasoning over Text	Nitish Gupta, Kevin Lin, Dan Roth, Sameer Singh, Matt Gardner		code	-1
Higher-Order Function Networks for Learning Composable 3D Object Representations	Eric Mitchell, Selim Engin, Volkan Isler, Daniel D. Lee		code	-1
Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling	Hao Zhang, Bo Chen, Long Tian, Zhengjue Wang, Mingyuan Zhou		code	-1
Towards Fast Adaptation of Neural Architectures with Meta Learning	Dongze Lian, Yin Zheng, Yintao Xu, Yanxiong Lu, Leyu Lin, Peilin Zhao, Junzhou Huang, Shenghua Gao		code	-1
Graph Constrained Reinforcement Learning for Natural Language Action Spaces	Prithviraj Ammanabrolu, Matthew J. Hausknecht		code	-1
Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control	Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui		code	-1
Augmenting Non-Collaborative Dialog Systems with Explicit Semantic and Strategic Dialog History	Yiheng Zhou, Yulia Tsvetkov, Alan W. Black, Zhou Yu		code	-1
BERTScore: Evaluating Text Generation with BERT	Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, Yoav Artzi		code	-1
Neural Execution of Graph Algorithms	Petar Velickovic, Rex Ying, Matilde Padovano, Raia Hadsell, Charles Blundell		code	-1
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses	Uyeong Jang, Susmit Jha, Somesh Jha		code	-1
FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary	Yingzhen Yang, Jiahui Yu, Nebojsa Jojic, Jun Huan, Thomas S. Huang		code	-1
Capsules with Inverted Dot-Product Attention Routing	YaoHung Hubert Tsai, Nitish Srivastava, Hanlin Goh, Ruslan Salakhutdinov		code	-1
Composition-based Multi-Relational Graph Convolutional Networks	Shikhar Vashishth, Soumya Sanyal, Vikram Nitin, Partha P. Talukdar		code	-1
Gradient-Based Neural DAG Learning	Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon LacosteJulien		code	-1
The Local Elasticity of Neural Networks	Hangfeng He, Weijie J. Su		code	-1
Composing Task-Agnostic Policies with Deep Reinforcement Learning	Ahmed Hussain Qureshi, Jacob J. Johnson, Yuzhe Qin, Taylor Henderson, Byron Boots, Michael C. Yip		code	-1
Convergence of Gradient Methods on Bilinear Zero-Sum Games	Guojun Zhang, Yaoliang Yu		code	-1
Discovering Motor Programs by Recomposing Demonstrations	Tanmay Shankar, Shubham Tulsiani, Lerrel Pinto, Abhinav Gupta		code	-1
Learning from Explanations with Neural Execution Tree	Ziqi Wang, Yujia Qin, Wenxuan Zhou, Jun Yan, Qinyuan Ye, Leonardo Neves, Zhiyuan Liu, Xiang Ren		code	-1
Jelly Bean World: A Testbed for Never-Ending Learning	Emmanouil Antonios Platanios, Abulhair Saparov, Tom M. Mitchell		code	-1
Coherent Gradients: An Approach to Understanding Generalization in Gradient Descent-based Optimization	Satrajit Chatterjee		code	-1
Probabilistic Connection Importance Inference and Lossless Compression of Deep Neural Networks	Xin Xing, Long Sha, Pengyu Hong, Zuofeng Shang, Jun S. Liu		code	-1
MEMO: A Deep Network for Flexible Combination of Episodic Memories	Andrea Banino, Adrià Puigdomènech Badia, Raphael Köster, Martin J. Chadwick, Vinícius Flores Zambaldi, Demis Hassabis, Caswell Barry, Matthew M. Botvinick, Dharshan Kumaran, Charles Blundell		code	-1
Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality	Saurabh Khanna, Vincent Y. F. Tan		code	-1
Bayesian Meta Sampling for Fast Uncertainty Adaptation	Zhenyi Wang, Yang Zhao, Ping Yu, Ruiyi Zhang, Changyou Chen		code	-1
Non-Autoregressive Dialog State Tracking	Hung Le, Richard Socher, Steven C. H. Hoi		code	-1
Extreme Tensoring for Low-Memory Preconditioning	Xinyi Chen, Naman Agarwal, Elad Hazan, Cyril Zhang, Yi Zhang		code	-1
RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients?	Anil Kag, Ziming Zhang, Venkatesh Saligrama		code	-1
The Early Phase of Neural Network Training	Jonathan Frankle, David J. Schwab, Ari S. Morcos		code	-1
NeurQuRI: Neural Question Requirement Inspector for Answerability Prediction in Machine Reading Comprehension	Seohyun Back, Sai Chetan Chinthakindi, Akhil Kedia, Haejun Lee, Jaegul Choo		code	-1
Towards Stabilizing Batch Statistics in Backward Propagation of Batch Normalization	Junjie Yan, Ruosi Wan, Xiangyu Zhang, Wei Zhang, Yichen Wei, Jian Sun		code	-1
Single Episode Policy Transfer in Reinforcement Learning	Jiachen Yang, Brenden K. Petersen, Hongyuan Zha, Daniel M. Faissol		code	-1
Generalization through Memorization: Nearest Neighbor Language Models	Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, Mike Lewis		code	-1
Transformer-XH: Multi-Evidence Reasoning with eXtra Hop Attention	Chen Zhao, Chenyan Xiong, Corby Rosset, Xia Song, Paul N. Bennett, Saurabh Tiwary		code	-1
Synthesizing Programmatic Policies that Inductively Generalize	Jeevana Priya Inala, Osbert Bastani, Zenna Tavares, Armando SolarLezama		code	-1
Decoding As Dynamic Programming For Recurrent Autoregressive Models	Najam Zaidi, Trevor Cohn, Gholamreza Haffari		code	-1
Deep Double Descent: Where Bigger Models and More Data Hurt	Preetum Nakkiran, Gal Kaplun, Yamini Bansal, Tristan Yang, Boaz Barak, Ilya Sutskever		code	-1
Intriguing Properties of Adversarial Training at Scale	Cihang Xie, Alan L. Yuille		code	-1
Shifted and Squeezed 8-bit Floating Point format for Low-Precision Training of Deep Neural Networks	Léopold Cambier, Anahita Bhiwandiwalla, Ting Gong, Oguz H. Elibol, Mehran Nekuii, Hanlin Tang		code	-1
Distributed Bandit Learning: Near-Optimal Regret with Efficient Communication	Yuanhao Wang, Jiachen Hu, Xiaoyu Chen, Liwei Wang		code	-1
Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks	Timothy Tadros, Giri P. Krishnan, Ramyaa Ramyaa, Maxim Bazhenov		code	-1
A Closer Look at the Optimization Landscapes of Generative Adversarial Networks	Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon LacosteJulien		code	-1
On the Global Convergence of Training Deep Linear ResNets	Difan Zou, Philip M. Long, Quanquan Gu		code	-1
Towards a Deep Network Architecture for Structured Smoothness	Haroun Habeeb, Oluwasanmi Koyejo		code	-1
Revisiting Self-Training for Neural Sequence Generation	Junxian He, Jiatao Gu, Jiajun Shen, Marc'Aurelio Ranzato		code	-1
Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators	Reinhard Heckel, Mahdi Soltanolkotabi		code	-1
Variational Autoencoders for Highly Multivariate Spatial Point Processes Intensities	Baichuan Yuan, Xiaowei Wang, Jianxin Ma, Chang Zhou, Andrea L. Bertozzi, Hongxia Yang		code	-1
Model-Augmented Actor-Critic: Backpropagating through Paths	Ignasi Clavera, Yao Fu, Pieter Abbeel		code	-1
LambdaNet: Probabilistic Type Inference using Graph Neural Networks	Jiayi Wei, Maruth Goyal, Greg Durrett, Isil Dillig		code	-1
From Inference to Generation: End-to-end Fully Self-supervised Generation of Human Face from Speech	HyeongSeok Choi, Changdae Park, Kyogu Lee		code	-1
Learning from Unlabelled Videos Using Contrastive Predictive Neural 3D Mapping	Adam W. Harley, Shrinidhi Kowshika Lakshmikanth, Fangyu Li, Xian Zhou, HsiaoYu Fish Tung, Katerina Fragkiadaki		code	-1
Decoupling Representation and Classifier for Long-Tailed Recognition	Bingyi Kang, Saining Xie, Marcus Rohrbach, Zhicheng Yan, Albert Gordo, Jiashi Feng, Yannis Kalantidis		code	-1
Robust Reinforcement Learning for Continuous Control with Model Misspecification	Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Yuanyuan Shi, Jackie Kay, Todd Hester, Timothy A. Mann, Martin A. Riedmiller		code	-1
Cross-lingual Alignment vs Joint Training: A Comparative Study and A Simple Unified Framework	Zirui Wang, Jiateng Xie, Ruochen Xu, Yiming Yang, Graham Neubig, Jaime G. Carbonell		code	-1
Training Recurrent Neural Networks Online by Learning Explicit State Variables	Somjit Nath, Vincent Liu, Alan Chan, Xin Li, Adam White, Martha White		code	-1
Uncertainty-guided Continual Learning with Bayesian Neural Networks	Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach		code	-1
Curriculum Loss: Robust Learning and Generalization against Label Corruption	Yueming Lyu, Ivor W. Tsang		code	-1
Picking Winning Tickets Before Training by Preserving Gradient Flow	Chaoqi Wang, Guodong Zhang, Roger B. Grosse		code	-1
Generative Models for Effective ML on Private, Decentralized Datasets	Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Agüera y Arcas		code	-1
Inductive representation learning on temporal graphs	Da Xu, Chuanwei Ruan, Evren Körpeoglu, Sushant Kumar, Kannan Achan		code	-1
BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning	Yeming Wen, Dustin Tran, Jimmy Ba		code	-1
Towards neural networks that provably know when they don't know	Alexander Meinke, Matthias Hein		code	-1
Iterative energy-based projection on a normal data manifold for anomaly localization	David Dehaene, Oriel Frigo, Sébastien Combrexelle, Pierre Eline		code	-1
Towards Stable and Efficient Training of Verifiably Robust Neural Networks	Huan Zhang, Hongge Chen, Chaowei Xiao, Sven Gowal, Robert Stanforth, Bo Li, Duane S. Boning, ChoJui Hsieh		code	-1
Frequency-based Search-control in Dyna	Yangchen Pan, Jincheng Mei, Amirmassoud Farahmand		code	-1
Learning representations for binary-classification without backpropagation	Mathias Lechner		code	-1
Polylogarithmic width suffices for gradient descent to achieve arbitrarily small test error with shallow ReLU networks	Ziwei Ji, Matus Telgarsky		code	-1
Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics	Sungyong Seo, Chuizheng Meng, Yan Liu		code	-1
HiLLoC: lossless image compression with hierarchical latent variable models	James Townsend, Thomas Bird, Julius Kunze, David Barber		code	-1
IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks	Michael Luo, Jiahao Yao, Richard Liaw, Eric Liang, Ion Stoica		code	-1
On Bonus Based Exploration Methods In The Arcade Learning Environment	Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare		code	-1
Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation	Xinjie Fan, Yizhe Zhang, Zhendong Wang, Mingyuan Zhou		code	-1
Smoothness and Stability in GANs	Casey Chu, Kentaro Minami, Kenji Fukumizu		code	-1
SNOW: Subscribing to Knowledge via Channel Pooling for Transfer & Lifelong Learning of Convolutional Neural Networks	Chungkuk Yoo, Bumsoo Kang, Minsik Cho		code	-1
Empirical Studies on the Properties of Linear Regions in Deep Neural Networks	Xiao Zhang, Dongrui Wu		code	-1
Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning	Ali Mousavi, Lihong Li, Qiang Liu, Denny Zhou		code	-1
PairNorm: Tackling Oversmoothing in GNNs	Lingxiao Zhao, Leman Akoglu		code	-1
Unsupervised Clustering using Pseudo-semi-supervised Learning	Divam Gupta, Ramachandran Ramjee, Nipun Kwatra, Muthian Sivathanu		code	-1
Simple and Effective Regularization Methods for Training on Noisily Labeled Data with Generalization Guarantee	Wei Hu, Zhiyuan Li, Dingli Yu		code	-1
Controlling generative models with continuous factors of variations	Antoine Plumerault, Hervé Le Borgne, Céline Hudelot		code	-1
Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control	Yaofeng Desmond Zhong, Biswadip Dey, Amit Chakraborty		code	-1
Understanding l4-based Dictionary Learning: Interpretation, Stability, and Robustness	Yuexiang Zhai, Hermish Mehta, Zhengyuan Zhou, Yi Ma		code	-1
Quantum Algorithms for Deep Convolutional Neural Networks	Iordanis Kerenidis, Jonas Landman, Anupam Prakash		code	-1
Self-Supervised Learning of Appliance Usage	ChenYu Hsu, Abbas Zeitoun, GuangHe Lee, Dina Katabi, Tommi S. Jaakkola		code	-1
Deep Graph Matching Consensus	Matthias Fey, Jan Eric Lenssen, Christopher Morris, Jonathan Masci, Nils M. Kriege		code	-1
Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks	Yu Bai, Jason D. Lee		code	-1
Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers	Junjie Liu, Zhe Xu, Runbin Shi, Ray C. C. Cheung, Hayden KwokHay So		code	-1
Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference	TingKuei Hu, Tianlong Chen, Haotao Wang, Zhangyang Wang		code	-1
Neural Policy Gradient Methods: Global Optimality and Rates of Convergence	Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang		code	-1
Double Neural Counterfactual Regret Minimization	Hui Li, Kailiang Hu, Shaohua Zhang, Yuan Qi, Le Song		code	-1
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation	Chence Shi, Minkai Xu, Zhaocheng Zhu, Weinan Zhang, Ming Zhang, Jian Tang		code	-1
The Gambler's Problem and Beyond	Baoxiang Wang, Shuai Li, Jiajin Li, Siu On Chan		code	-1
Multilingual Alignment of Contextual Word Representations	Steven Cao, Nikita Kitaev, Dan Klein		code	-1
The Curious Case of Neural Text Degeneration	Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, Yejin Choi		code	-1
Graph Convolutional Reinforcement Learning	Jiechuan Jiang, Chen Dun, Tiejun Huang, Zongqing Lu		code	-1
Meta-Learning Deep Energy-Based Memory Models	Sergey Bartunov, Jack W. Rae, Simon Osindero, Timothy P. Lillicrap		code	-1
Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning	Akanksha Atrey, Kaleigh Clary, David D. Jensen		code	-1
Fast Neural Network Adaptation via Parameter Remapping and Architecture Search	Jiemin Fang, Yuzhu Sun, Kangjian Peng, Qian Zhang, Yuan Li, Wenyu Liu, Xinggang Wang		code	-1
Guiding Program Synthesis by Learning to Generate Examples	Larissa Laich, Pavol Bielik, Martin T. Vechev		code	-1
SNODE: Spectral Discretization of Neural ODEs for System Identification	Alessio Quaglino, Marco Gallieri, Jonathan Masci, Jan Koutník		code	-1
Generalized Convolutional Forest Networks for Domain Generalization and Visual Recognition	Jongbin Ryu, Gitaek Kwon, MingHsuan Yang, Jongwoo Lim		code	-1
Once-for-All: Train One Network and Specialize it for Efficient Deployment	Han Cai, Chuang Gan, Tianzhe Wang, Zhekai Zhang, Song Han		code	-1
Multi-Agent Interactions Modeling with Correlated Policies	Minghuan Liu, Ming Zhou, Weinan Zhang, Yuzheng Zhuang, Jun Wang, Wulong Liu, Yong Yu		code	-1
PCMC-Net: Feature-based Pairwise Choice Markov Chains	Alix Lhéritier		code	-1
Implementing Inductive bias for different navigation tasks through diverse RNN attrractors	Tie Xu, Omri Barak		code	-1
Query2box: Reasoning over Knowledge Graphs in Vector Space Using Box Embeddings	Hongyu Ren, Weihua Hu, Jure Leskovec		code	-1
Rethinking the Hyperparameters for Fine-tuning	Hao Li, Pratik Chaudhari, Hao Yang, Michael Lam, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto		code	-1
Plug and Play Language Models: A Simple Approach to Controlled Text Generation	Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, Rosanne Liu		code	-1
Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks	Wei Hu, Lechao Xiao, Jeffrey Pennington		code	-1
RGBD-GAN: Unsupervised 3D Representation Learning From Natural Image Datasets via RGBD Image Synthesis	Atsuhiro Noguchi, Tatsuya Harada		code	-1
Towards Verified Robustness under Text Deletion Interventions	Johannes Welbl, PoSen Huang, Robert Stanforth, Sven Gowal, Krishnamurthy (Dj) Dvijotham, Martin Szummer, Pushmeet Kohli		code	-1
Jacobian Adversarially Regularized Networks for Robustness	Alvin Chan, Yi Tay, YewSoon Ong, Jie Fu		code	-1
Thinking While Moving: Deep Reinforcement Learning with Concurrent Control	Ted Xiao, Eric Jang, Dmitry Kalashnikov, Sergey Levine, Julian Ibarz, Karol Hausman, Alexander Herzog		code	-1
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning	Qian Long, Zihan Zhou, Abhinav Gupta, Fei Fang, Yi Wu, Xiaolong Wang		code	-1
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators	Kevin Clark, MinhThang Luong, Quoc V. Le, Christopher D. Manning		code	-1
Environmental drivers of systematicity and generalization in a situated agent	Felix Hill, Andrew K. Lampinen, Rosalia Schneider, Stephen Clark, Matthew M. Botvinick, James L. McClelland, Adam Santoro		code	-1
Abstract Diagrammatic Reasoning with Multiplex Graph Networks	Duo Wang, Mateja Jamnik, Pietro Liò		code	-1
A Baseline for Few-Shot Image Classification	Guneet Singh Dhillon, Pratik Chaudhari, Avinash Ravichandran, Stefano Soatto		code	-1
Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering	Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, Richard Socher, Caiming Xiong		code	-1
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks	Alejandro Molina, Patrick Schramowski, Kristian Kersting		code	-1
A Framework for robustness Certification of Smoothed Classifiers using F-Divergences	Krishnamurthy (Dj) Dvijotham, Jamie Hayes, Borja Balle, J. Zico Kolter, Chongli Qin, András György, Kai Xiao, Sven Gowal, Pushmeet Kohli		code	-1
Contrastive Representation Distillation	Yonglong Tian, Dilip Krishnan, Phillip Isola		code	-1
Certified Defenses for Adversarial Patches	Pingyeh Chiang, Renkun Ni, Ahmed Abdelkader, Chen Zhu, Christoph Studer, Tom Goldstein		code	-1
Sample Efficient Policy Gradient Methods with Recursive Variance Reduction	Pan Xu, Felicia Gao, Quanquan Gu		code	-1
Deep Symbolic Superoptimization Without Human Knowledge	Hui Shi, Yang Zhang, Xinyun Chen, Yuandong Tian, Jishen Zhao		code	-1
Explain Your Move: Understanding Agent Actions Using Specific and Relevant Feature Attribution	Nikaash Puri, Sukriti Verma, Piyush Gupta, Dhruv Kayastha, Shripad Deshmukh, Balaji Krishnamurthy, Sameer Singh		code	-1
Universal Approximation with Certified Networks	Maximilian Baader, Matthew Mirman, Martin T. Vechev		code	-1
Measuring and Improving the Use of Graph Information in Graph Neural Networks	Yifan Hou, Jie Zhang, James Cheng, Kaili Ma, Richard T. B. Ma, Hongzhi Chen, MingChang Yang		code	-1
State-only Imitation with Transition Dynamics Mismatch	Tanmay Gangwani, Jian Peng		code	-1
Adversarial AutoAugment	Xinyu Zhang, Qiang Wang, Jian Zhang, Zhao Zhong		code	-1
Meta Dropout: Learning to Perturb Latent Features for Generalization	Haebeom Lee, Taewook Nam, Eunho Yang, Sung Ju Hwang		code	-1
Rényi Fair Inference	Sina Baharlouei, Maher Nouiehed, Ahmad Beirami, Meisam Razaviyayn		code	-1
Learning transport cost from subset correspondence	Ruishan Liu, Akshay Balsubramani, James Zou		code	-1
BlockSwap: Fisher-guided Block Substitution for Network Compression on a Budget	Jack Turner, Elliot J. Crowley, Michael F. P. O'Boyle, Amos J. Storkey, Gavin Gray		code	-1
Variance Reduction With Sparse Gradients	Melih Elibol, Lihua Lei, Michael I. Jordan		code	-1
Abductive Commonsense Reasoning	Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, Keisuke Sakaguchi, Ari Holtzman, Hannah Rashkin, Doug Downey, Wentau Yih, Yejin Choi		code	-1
Discrepancy Ratio: Evaluating Model Performance When Even Experts Disagree on the Truth	Igor Lovchinsky, Alon Daks, Israel Malkin, Pouya Samangouei, Ardavan Saeedi, Yang Liu, Swami Sankaranarayanan, Tomer Gafner, Ben Sternlieb, Patrick Maher, Nathan Silberman		code	-1
Weakly Supervised Disentanglement with Guarantees	Rui Shu, Yining Chen, Abhishek Kumar, Stefano Ermon, Ben Poole		code	-1
Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks	Jiadong Lin, Chuanbiao Song, Kun He, Liwei Wang, John E. Hopcroft		code	-1
Fantastic Generalization Measures and Where to Find Them	Yiding Jiang, Behnam Neyshabur, Hossein Mobahi, Dilip Krishnan, Samy Bengio		code	-1
Robustness Verification for Transformers	Zhouxing Shi, Huan Zhang, KaiWei Chang, Minlie Huang, ChoJui Hsieh		code	-1
Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning	Kimin Lee, Kibok Lee, Jinwoo Shin, Honglak Lee		code	-1
Tensor Decompositions for Temporal Knowledge Base Completion	Timothée Lacroix, Guillaume Obozinski, Nicolas Usunier		code	-1
On Universal Equivariant Set Networks	Nimrod Segol, Yaron Lipman		code	-1
Provable robustness against all adversarial $l_p$-perturbations for $p\geq 1$	Francesco Croce, Matthias Hein		code	-1
Don't Use Large Mini-batches, Use Local SGD	Tao Lin, Sebastian U. Stich, Kumar Kshitij Patel, Martin Jaggi		code	-1
Kernel of CycleGAN as a principal homogeneous space	Nikita Moriakov, Jonas Adler, Jonas Teuwen		code	-1
Distributionally Robust Neural Networks	Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, Percy Liang		code	-1
On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach	Yuanhao Wang, Guodong Zhang, Jimmy Ba		code	-1
A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning	Soochan Lee, Junsoo Ha, Dongsu Zhang, Gunhee Kim		code	-1
Hyper-SAGNN: a self-attention based graph neural network for hypergraphs	Ruochi Zhang, Yuesong Zou, Jian Ma		code	-1
Neural Epitome Search for Architecture-Agnostic Network Compression	Daquan Zhou, Xiaojie Jin, Qibin Hou, Kaixin Wang, Jianchao Yang, Jiashi Feng		code	-1
On the Equivalence between Positional Node Embeddings and Structural Graph Representations	Balasubramaniam Srinivasan, Bruno Ribeiro		code	-1
Probability Calibration for Knowledge Graph Embedding Models	Pedro Tabacof, Luca Costabello		code	-1
Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks	Joonyoung Yi, Juhyuk Lee, Kwang Joon Kim, Sung Ju Hwang, Eunho Yang		code	-1
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification	Yu Rong, Wenbing Huang, Tingyang Xu, Junzhou Huang		code	-1
Masked Based Unsupervised Content Transfer	Ron Mokady, Sagie Benaim, Lior Wolf, Amit Bermano		code	-1
U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation	Junho Kim, Minjae Kim, Hyeonwoo Kang, Kwanghee Lee		code	-1
Inductive and Unsupervised Representation Learning on Graph Structured Objects	Lichen Wang, Bo Zong, Qianqian Ma, Wei Cheng, Jingchao Ni, Wenchao Yu, Yanchi Liu, Dongjin Song, Haifeng Chen, Yun Fu		code	-1
Batch-shaping for learning conditional channel gated networks	Babak Ehteshami Bejnordi, Tijmen Blankevoort, Max Welling		code	-1
Learning Robust Representations via Multi-View Information Bottleneck	Marco Federici, Anjan Dutta, Patrick Forré, Nate Kushman, Zeynep Akata		code	-1
Deep probabilistic subsampling for task-adaptive compressed sensing	Iris A. M. Huijben, Bastiaan S. Veeling, Ruud J. G. van Sloun		code	-1
Robust anomaly detection and backdoor attack detection via differential privacy	Min Du, Ruoxi Jia, Dawn Song		code	-1
Learning to Guide Random Search	Ozan Sener, Vladlen Koltun		code	-1
Lagrangian Fluid Simulation with Continuous Convolutions	Benjamin Ummenhofer, Lukas Prantl, Nils Thuerey, Vladlen Koltun		code	-1
Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs	Aditya Paliwal, Felix Gimeno, Vinod Nair, Yujia Li, Miles Lubin, Pushmeet Kohli, Oriol Vinyals		code	-1
Compressive Transformers for Long-Range Sequence Modelling	Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, Chloe Hillier, Timothy P. Lillicrap		code	-1
A Stochastic Derivative Free Optimization Method with Momentum	Eduard Gorbunov, Adel Bibi, Ozan Sener, El Houcine Bergou, Peter Richtárik		code	-1
Understanding and Improving Information Transfer in Multi-Task Learning	Sen Wu, Hongyang R. Zhang, Christopher Ré		code	-1
Learning To Explore Using Active Neural SLAM	Devendra Singh Chaplot, Dhiraj Gandhi, Saurabh Gupta, Abhinav Gupta, Ruslan Salakhutdinov		code	-1
EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness Against Adversarial Attacks	Sanchari Sen, Balaraman Ravindran, Anand Raghunathan		code	-1
Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel	Xin Qiu, Elliot Meyerson, Risto Miikkulainen		code	-1
B-Spline CNNs on Lie groups	Erik J. Bekkers		code	-1
Neural Outlier Rejection for Self-Supervised Keypoint Learning	Jiexiong Tang, Hanme Kim, Vitor Guizilini, Sudeep Pillai, Rares Ambrus		code	-1
Reducing Transformer Depth on Demand with Structured Dropout	Angela Fan, Edouard Grave, Armand Joulin		code	-1
Cross-Lingual Ability of Multilingual BERT: An Empirical Study	Karthikeyan K, Zihan Wang, Stephen Mayhew, Dan Roth		code	-1
SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition	Zhixuan Lin, YiFu Wu, Skand Vishwanath Peri, Weihao Sun, Gautam Singh, Fei Deng, Jindong Jiang, Sungjin Ahn		code	-1
RIDE: Rewarding Impact-Driven Exploration for Procedurally-Generated Environments	Roberta Raileanu, Tim Rocktäschel		code	-1
Low-dimensional statistical manifold embedding of directed graphs	Thorben Funke, Tian Guo, Alen Lancic, Nino AntulovFantulin		code	-1
Efficient Probabilistic Logic Reasoning with Graph Neural Networks	Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, Le Song		code	-1
GraphSAINT: Graph Sampling Based Inductive Learning Method	Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna		code	-1
You Only Train Once: Loss-Conditional Training of Deep Networks	Alexey Dosovitskiy, Josip Djolonga		code	-1
Projection-Based Constrained Policy Optimization	TsungYen Yang, Justinian Rosca, Karthik Narasimhan, Peter J. Ramadge		code	-1
Infinite-Horizon Differentiable Model Predictive Control	Sebastian East, Marco Gallieri, Jonathan Masci, Jan Koutník, Mark Cannon		code	-1
Combining Q-Learning and Search with Amortized Value Estimates	Jessica B. Hamrick, Victor Bapst, Alvaro SanchezGonzalez, Tobias Pfaff, Theophane Weber, Lars Buesing, Peter W. Battaglia		code	-1
Training Generative Adversarial Networks from Incomplete Observations using Factorised Discriminators	Daniel Stoller, Sebastian Ewert, Simon Dixon		code	-1
Decentralized Deep Learning with Arbitrary Communication Compression	Anastasia Koloskova, Tao Lin, Sebastian U. Stich, Martin Jaggi		code	-1
Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control	TsuiWei Weng, Krishnamurthy (Dj) Dvijotham, Jonathan Uesato, Kai Xiao, Sven Gowal, Robert Stanforth, Pushmeet Kohli		code	-1
Gradient $\ell_1$ Regularization for Quantization Robustness	Milad Alizadeh, Arash Behboodi, Mart van Baalen, Christos Louizos, Tijmen Blankevoort, Max Welling		code	-1
SpikeGrad: An ANN-equivalent Computation Model for Implementing Backpropagation with Spikes	Johannes C. Thiele, Olivier Bichler, Antoine Dupret		code	-1
On the Relationship between Self-Attention and Convolutional Layers	JeanBaptiste Cordonnier, Andreas Loukas, Martin Jaggi		code	-1
Learning-Augmented Data Stream Algorithms	Tanqiu Jiang, Yi Li, Honghao Lin, Yisong Ruan, David P. Woodruff		code	-1
Structured Object-Aware Physics Prediction for Video Modeling and Planning	Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting		code	-1
Incorporating BERT into Neural Machine Translation	Jinhua Zhu, Yingce Xia, Lijun Wu, Di He, Tao Qin, Wengang Zhou, Houqiang Li, TieYan Liu		code	-1
MMA Training: Direct Input Space Margin Maximization through Adversarial Training	Gavin Weiguang Ding, Yash Sharma, Kry Yik Chau Lui, Ruitong Huang		code	-1
Infinite-horizon Off-Policy Policy Evaluation with Multiple Behavior Policies	Xinyun Chen, Lu Wang, Yizhe Hang, Heng Ge, Hongyuan Zha		code	-1
vq-wav2vec: Self-Supervised Learning of Discrete Speech Representations	Alexei Baevski, Steffen Schneider, Michael Auli		code	-1
Meta-learning curiosity algorithms	Ferran Alet, Martin F. Schneider, Tomás LozanoPérez, Leslie Pack Kaelbling		code	-1
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems	Çaglar Gülçehre, Tom Le Paine, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil C. Rabinowitz, Duncan Williams, Gabriel BarthMaron, Ziyu Wang, Nando de Freitas, Worlds Team		code	-1
VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning	Luisa M. Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson		code	-1
Lookahead: A Far-sighted Alternative of Magnitude-based Pruning	Sejun Park, Jaeho Lee, Sangwoo Mo, Jinwoo Shin		code	-1
Spike-based causal inference for weight alignment	Jordan Guerguiev, Konrad P. Körding, Blake A. Richards		code	-1
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients	Shell Xu Hu, Pablo Garcia Moreno, Yang Xiao, Xi Shen, Guillaume Obozinski, Neil D. Lawrence, Andreas C. Damianou		code	-1
Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning	Noah Y. Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, Thomas Lampe, Roland Hafner, Nicolas Heess, Martin A. Riedmiller		code	-1
Understanding the Limitations of Conditional Generative Models	Ethan Fetaya, JörnHenrik Jacobsen, Will Grathwohl, Richard S. Zemel		code	-1
Demystifying Inter-Class Disentanglement	Aviv Gabbay, Yedid Hoshen		code	-1
Mixed-curvature Variational Autoencoders	Ondrej Skopek, OctavianEugen Ganea, Gary Bécigneul		code	-1
BinaryDuo: Reducing Gradient Mismatch in Binary Activation Network by Coupling Binary Activations	Hyungjun Kim, Kyungsu Kim, Jinseok Kim, JaeJoon Kim		code	-1
Model-based reinforcement learning for biological sequence design	Christof Angermüller, David Dohan, David Belanger, Ramya Deshpande, Kevin Murphy, Lucy J. Colwell		code	-1
BayesOpt Adversarial Attack	Binxin Ru, Adam D. Cobb, Arno Blaas, Yarin Gal		code	-1
Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies	Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Honglak Lee		code	-1
Hypermodels for Exploration	Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Ian Osband, Zheng Wen, Benjamin Van Roy		code	-1
RaPP: Novelty Detection with Reconstruction along Projection Pathway	Ki Hyun Kim, Sangwoo Shim, Yongsub Lim, Jongseob Jeon, Jeongwoo Choi, Byungchan Kim, Andre S. Yoon		code	-1
Dynamics-Aware Embeddings	William F. Whitney, Rajat Agarwal, Kyunghyun Cho, Abhinav Gupta		code	-1
Functional Regularisation for Continual Learning with Gaussian Processes	Michalis K. Titsias, Jonathan Schwarz, Alexander G. de G. Matthews, Razvan Pascanu, Yee Whye Teh		code	-1
You CAN Teach an Old Dog New Tricks! On Training Knowledge Graph Embeddings	Daniel Ruffinelli, Samuel Broscheit, Rainer Gemulla		code	-1
AdvectiveNet: An Eulerian-Lagrangian Fluidic Reservoir for Point Cloud Processing	Xingzhe He, Helen Lu Cao, Bo Zhu		code	-1
Never Give Up: Learning Directed Exploration Strategies	Adrià Puigdomènech Badia, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Bilal Piot, Steven Kapturowski, Olivier Tieleman, Martín Arjovsky, Alexander Pritzel, Andrew Bolt, Charles Blundell		code	-1
Fair Resource Allocation in Federated Learning	Tian Li, Maziar Sanjabi, Ahmad Beirami, Virginia Smith		code	-1
Smooth markets: A basic mechanism for organizing gradient-based learners	David Balduzzi, Wojciech M. Czarnecki, Tom Anthony, Ian M. Gemp, Edward Hughes, Joel Z. Leibo, Georgios Piliouras, Thore Graepel		code	-1
StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding	Wei Wang, Bin Bi, Ming Yan, Chen Wu, Jiangnan Xia, Zuyi Bao, Liwei Peng, Luo Si		code	-1
Training binary neural networks with real-to-binary convolutions	Brais Martínez, Jing Yang, Adrian Bulat, Georgios Tzimiropoulos		code	-1
Permutation Equivariant Models for Compositional Generalization in Language	Jonathan Gordon, David LopezPaz, Marco Baroni, Diane Bouchacourt		code	-1
Continual learning with hypernetworks	Johannes von Oswald, Christian Henning, João Sacramento, Benjamin F. Grewe		code	-1
Phase Transitions for the Information Bottleneck in Representation Learning	Tailin Wu, Ian S. Fischer		code	-1
Variational Template Machine for Data-to-Text Generation	Rong Ye, Wenxian Shi, Hao Zhou, Zhongyu Wei, Lei Li		code	-1
Memory-Based Graph Networks	Amir Hosein Khas Ahmadi, Kaveh Hassani, Parsa Moradi, Leo Lee, Quaid Morris		code	-1
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty	Dan Hendrycks, Norman Mu, Ekin Dogus Cubuk, Barret Zoph, Justin Gilmer, Balaji Lakshminarayanan		code	-1
AtomNAS: Fine-Grained End-to-End Neural Architecture Search	Jieru Mei, Yingwei Li, Xiaochen Lian, Xiaojie Jin, Linjie Yang, Alan L. Yuille, Jianchao Yang		code	-1
Residual Energy-Based Models for Text Generation	Yuntian Deng, Anton Bakhtin, Myle Ott, Arthur Szlam, Marc'Aurelio Ranzato		code	-1
A closer look at the approximation capabilities of neural networks	Kai Fong Ernest Chong		code	-1
Deep Audio Priors Emerge From Harmonic Convolutional Networks	Zhoutong Zhang, Yunyun Wang, Chuang Gan, Jiajun Wu, Joshua B. Tenenbaum, Antonio Torralba, William T. Freeman		code	-1
Expected Information Maximization: Using the I-Projection for Mixture Density Estimation	Philipp Becker, Oleg Arenz, Gerhard Neumann		code	-1
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms	Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal		code	-1
On the interaction between supervision and self-play in emergent communication	Ryan Lowe, Abhinav Gupta, Jakob N. Foerster, Douwe Kiela, Joelle Pineau		code	-1
Dynamic Model Pruning with Feedback	Tao Lin, Sebastian U. Stich, Luis Barba, Daniil Dmitriev, Martin Jaggi		code	-1
Latent Normalizing Flows for Many-to-Many Cross-Domain Mappings	Shweta Mahajan, Iryna Gurevych, Stefan Roth		code	-1
Transferring Optimality Across Data Distributions via Homotopy Methods	Matilde Gargiani, Andrea Zanelli, Quoc TranDinh, Moritz Diehl, Frank Hutter		code	-1
Regularizing activations in neural networks via distribution matching with the Wasserstein metric	Taejong Joo, Donggu Kang, Byunghoon Kim		code	-1
Mutual Information Gradient Estimation for Representation Learning	Liangjian Wen, Yiji Zhou, Lirong He, Mingyuan Zhou, Zenglin Xu		code	-1
Lite Transformer with Long-Short Range Attention	Zhanghao Wu, Zhijian Liu, Ji Lin, Yujun Lin, Song Han		code	-1
A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case	Greg Ongie, Rebecca Willett, Daniel Soudry, Nathan Srebro		code	-1
Adversarial Lipschitz Regularization	Dávid Terjék		code	-1
Compositional Language Continual Learning	Yuanpeng Li, Liang Zhao, Kenneth Church, Mohamed Elhoseiny		code	-1
End to End Trainable Active Contours via Differentiable Rendering	Shir Gur, Tal Shaharabany, Lior Wolf		code	-1
Provable Filter Pruning for Efficient Neural Networks	Lucas Liebenwein, Cenk Baykal, Harry Lang, Dan Feldman, Daniela Rus		code	-1
Effect of Activation Functions on the Training of Overparametrized Neural Nets	Abhishek Panigrahi, Abhishek Shetty, Navin Goyal		code	-1
Lipschitz constant estimation of Neural Networks via sparse polynomial optimization	Fabian Latorre Gómez, Paul Rolland, Volkan Cevher		code	-1
State Alignment-based Imitation Learning	Fangchen Liu, Zhan Ling, Tongzhou Mu, Hao Su		code	-1
Learning to Group: A Bottom-Up Framework for 3D Part Discovery in Unseen Categories	Tiange Luo, Kaichun Mo, Zhiao Huang, Jiarui Xu, Siyu Hu, Liwei Wang, Hao Su		code	-1
Discriminative Particle Filter Reinforcement Learning for Complex Partial observations	Xiao Ma, Péter Karkus, David Hsu, Wee Sun Lee, Nan Ye		code	-1
Unrestricted Adversarial Examples via Semantic Manipulation	Anand Bhattad, Min Jin Chong, Kaizhao Liang, Bo Li, David A. Forsyth		code	-1
Classification-Based Anomaly Detection for General Data	Liron Bergman, Yedid Hoshen		code	-1
Scale-Equivariant Steerable Networks	Ivan Sosnovik, Michal Szmaja, Arnold W. M. Smeulders		code	-1
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning	Jian Li, Xuanyuan Luo, Mingda Qiao		code	-1
Consistency Regularization for Generative Adversarial Networks	Han Zhang, Zizhao Zhang, Augustus Odena, Honglak Lee		code	-1
Differentiable learning of numerical rules in knowledge graphs	PoWei Wang, Daria Stepanova, Csaba Domokos, J. Zico Kolter		code	-1
Learning to Move with Affordance Maps	William Qi, Ravi Teja Mullapudi, Saurabh Gupta, Deva Ramanan		code	-1
Neural tangent kernels, transportation mappings, and universal approximation	Ziwei Ji, Matus Telgarsky, Ruicheng Xian		code	-1
SCALOR: Generative World Models with Scalable Object Representations	Jindong Jiang, Sepehr Janghorbani, Gerard de Melo, Sungjin Ahn		code	-1
Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks	Tribhuvanesh Orekondy, Bernt Schiele, Mario Fritz		code	-1
Domain Adaptive Multibranch Networks	Róger BermúdezChacón, Mathieu Salzmann, Pascal Fua		code	-1
DiffTaichi: Differentiable Programming for Physical Simulation	Yuanming Hu, Luke Anderson, TzuMao Li, Qi Sun, Nathan Carr, Jonathan RaganKelley, Frédo Durand		code	-1
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning	Arsenii Ashukha, Alexander Lyzhov, Dmitry Molchanov, Dmitry P. Vetrov		code	-1
Episodic Reinforcement Learning with Associative Memory	Guangxiang Zhu, Zichuan Lin, Guangwen Yang, Chongjie Zhang		code	-1
Sub-policy Adaptation for Hierarchical Reinforcement Learning	Alexander C. Li, Carlos Florensa, Ignasi Clavera, Pieter Abbeel		code	-1
Critical initialisation in continuous approximations of binary neural networks	George Stamatescu, Federica Gerace, Carlo Lucibello, Ian G. Fuss, Langford B. White		code	-1
Deep Orientation Uncertainty Learning based on a Bingham Loss	Igor Gilitschenski, Roshni Sahoo, Wilko Schwarting, Alexander Amini, Sertac Karaman, Daniela Rus		code	-1
Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring in Data	David W. Romero, Mark Hoogendoorn		code	-1
Mixed Precision DNNs: All you need is a good parametrization	Stefan Uhlich, Lukas Mauch, Fabien Cardinaux, Kazuki Yoshiyama, Javier Alonso García, Stephen Tiedemann, Thomas Kemp, Akira Nakamura		code	-1
Information Geometry of Orthogonal Initializations and Training	Piotr Aleksander Sokól, Il Memming Park		code	-1
Extreme Classification via Adversarial Softmax Approximation	Robert Bamler, Stephan Mandt		code	-1
Learning Nearly Decomposable Value Functions Via Communication Minimization	Tonghan Wang, Jianhao Wang, Chongyi Zheng, Chongjie Zhang		code	-1
Robust Subspace Recovery Layer for Unsupervised Anomaly Detection	ChiehHsin Lai, Dongmian Zou, Gilad Lerman		code	-1
Learning to Coordinate Manipulation Skills via Skill Behavior Diversification	Youngwoon Lee, Jingyun Yang, Joseph J. Lim		code	-1
NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search	Arber Zela, Julien Siems, Frank Hutter		code	-1
Conservative Uncertainty Estimation By Fitting Prior Networks	Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard E. Turner		code	-1
Understanding Generalization in Recurrent Neural Networks	Zhuozhuo Tu, Fengxiang He, Dacheng Tao		code	-1
The Shape of Data: Intrinsic Distance for Data Distributions	Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Ivan V. Oseledets, Emmanuel Müller		code	-1
How to 0wn the NAS in Your Spare Time	Sanghyun Hong, Michael Davinroy, Yigitcan Kaya, Dana DachmanSoled, Tudor Dumitras		code	-1
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation	Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy		code	-1
Breaking Certified Defenses: Semantic Adversarial Examples with Spoofed robustness Certificates	Amin Ghiasi, Ali Shafahi, Tom Goldstein		code	-1
Query-efficient Meta Attack to Deep Neural Networks	Jiawei Du, Hu Zhang, Joey Tianyi Zhou, Yi Yang, Jiashi Feng		code	-1
Massively Multilingual Sparse Word Representations	Gábor Berend		code	-1
Monotonic Multihead Attention	Xutai Ma, Juan Miguel Pino, James Cross, Liezl Puzon, Jiatao Gu		code	-1
Gradients as Features for Deep Representation Learning	Fangzhou Mu, Yingyu Liang, Yin Li		code	-1
Pay Attention to Features, Transfer Learn Faster CNNs	Kafeng Wang, Xitong Gao, Yiren Zhao, Xingjian Li, Dejing Dou, ChengZhong Xu		code	-1
Program Guided Agent	ShaoHua Sun, TeLin Wu, Joseph J. Lim		code	-1
Sparse Coding with Gated Learned ISTA	Kailun Wu, Yiwen Guo, Ziang Li, Changshui Zhang		code	-1
Graph Neural Networks Exponentially Lose Expressive Power for Node Classification	Kenta Oono, Taiji Suzuki		code	-1
Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells	Gengchen Mai, Krzysztof Janowicz, Bo Yan, Rui Zhu, Ling Cai, Ni Lao		code	-1
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization	FanYun Sun, Jordan Hoffmann, Vikas Verma, Jian Tang		code	-1
On Robustness of Neural Ordinary Differential Equations	Hanshu Yan, Jiawei Du, Vincent Y. F. Tan, Jiashi Feng		code	-1
Defending Against Physically Realizable Attacks on Image Classification	Tong Wu, Liang Tong, Yevgeniy Vorobeychik		code	-1
Estimating Gradients for Discrete Random Variables by Sampling without Replacement	Wouter Kool, Herke van Hoof, Max Welling		code	-1
Learning to Control PDEs with Differentiable Physics	Philipp Holl, Nils Thuerey, Vladlen Koltun		code	-1
Intensity-Free Learning of Temporal Point Processes	Oleksandr Shchur, Marin Bilos, Stephan Günnemann		code	-1
A Signal Propagation Perspective for Pruning Neural Networks at Initialization	Namhoon Lee, Thalaiyasingam Ajanthan, Stephen Gould, Philip H. S. Torr		code	-1
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets	Dongxian Wu, Yisen Wang, ShuTao Xia, James Bailey, Xingjun Ma		code	-1
White Noise Analysis of Neural Networks	Ali Borji, Sikun Lin		code	-1
Neural Machine Translation with Universal Visual Representation	Zhuosheng Zhang, Kehai Chen, Rui Wang, Masao Utiyama, Eiichiro Sumita, Zuchao Li, Hai Zhao		code	-1
Tranquil Clouds: Neural Networks for Learning Temporally Coherent Features in Point Clouds	Lukas Prantl, Nuttapong Chentanez, Stefan Jeschke, Nils Thuerey		code	-1
PC-DARTS: Partial Channel Connections for Memory-Efficient Architecture Search	Yuhui Xu, Lingxi Xie, Xiaopeng Zhang, Xin Chen, GuoJun Qi, Qi Tian, Hongkai Xiong		code	-1
Online and stochastic optimization beyond Lipschitz continuity: A Riemannian approach	Kimon Antonakopoulos, Elena Veronica Belmega, Panayotis Mertikopoulos		code	-1
Enhancing Adversarial Defense by k-Winners-Take-All	Chang Xiao, Peilin Zhong, Changxi Zheng		code	-1
Encoding word order in complex embeddings	Benyou Wang, Donghao Zhao, Christina Lioma, Qiuchi Li, Peng Zhang, Jakob Grue Simonsen		code	-1
DDSP: Differentiable Digital Signal Processing	Jesse H. Engel, Lamtharn Hantrakul, Chenjie Gu, Adam Roberts		code	-1
Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation	HungYu Tseng, HsinYing Lee, JiaBin Huang, MingHsuan Yang		code	-1
Ridge Regression: Structure, Cross-Validation, and Sketching	Sifan Liu, Edgar Dobriban		code	-1
Finite Depth and Width Corrections to the Neural Tangent Kernel	Boris Hanin, Mihai Nica		code	-1
Meta-Learning without Memorization	Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn		code	-1
Influence-Based Multi-Agent Exploration	Tonghan Wang, Jianhao Wang, Yi Wu, Chongjie Zhang		code	-1
Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs	Elizabeth Dinella, Hanjun Dai, Ziyang Li, Mayur Naik, Le Song, Ke Wang		code	-1
Sliced Cramer Synaptic Consolidation for Preserving Deeply Learned Representations	Soheil Kolouri, Nicholas A. Ketz, Andrea Soltoggio, Praveen K. Pilly		code	-1
How much Position Information Do Convolutional Neural Networks Encode?	Md. Amirul Islam, Sen Jia, Neil D. B. Bruce		code	-1
Hamiltonian Generative Networks	Peter Toth, Danilo J. Rezende, Andrew Jaegle, Sébastien Racanière, Aleksandar Botev, Irina Higgins		code	-1
CoPhy: Counterfactual Learning of Physical Dynamics	Fabien Baradel, Natalia Neverova, Julien Mille, Greg Mori, Christian Wolf		code	-1
Estimating counterfactual treatment outcomes over time through adversarially balanced representations	Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar		code	-1
Gradientless Descent: High-Dimensional Zeroth-Order Optimization	Daniel Golovin, John Karro, Greg Kochanski, Chansoo Lee, Xingyou Song, Qiuyi (Richard) Zhang		code	-1
Conditional Learning of Fair Representations	Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon		code	-1
Inductive Matrix Completion Based on Graph Neural Networks	Muhan Zhang, Yixin Chen		code	-1
Duration-of-Stay Storage Assignment under Uncertainty	Michael Lingzhi Li, Elliott Wolf, Daniel Wintz		code	-1
Emergence of functional and structural properties of the head direction system by optimization of recurrent neural networks	Christopher J. Cueva, Peter Y. Wang, Matthew Chin, XueXin Wei		code	-1
Deep neuroethology of a virtual rodent	Josh Merel, Diego Aldarondo, Jesse Marshall, Yuval Tassa, Greg Wayne, Bence Olveczky		code	-1
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation	Ziyang Tang, Yihao Feng, Lihong Li, Dengyong Zhou, Qiang Liu		code	-1
Learning Compositional Koopman Operators for Model-Based Control	Yunzhu Li, Hao He, Jiajun Wu, Dina Katabi, Antonio Torralba		code	-1
CLEVRER: Collision Events for Video Representation and Reasoning	Kexin Yi, Chuang Gan, Yunzhu Li, Pushmeet Kohli, Jiajun Wu, Antonio Torralba, Joshua B. Tenenbaum		code	-1
The Logical Expressiveness of Graph Neural Networks	Pablo Barceló, Egor V. Kostylev, Mikaël Monet, Jorge Pérez, Juan L. Reutter, Juan Pablo Silva		code	-1
The Break-Even Point on Optimization Trajectories of Deep Neural Networks	Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort, Devansh Arpit, Jacek Tabor, Kyunghyun Cho, Krzysztof J. Geras		code	-1
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations	Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut		code	-1
Disentangling neural mechanisms for perceptual grouping	Junkyung Kim, Drew Linsley, Kalpit Thakkar, Thomas Serre		code	-1
Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees	Binghong Chen, Bo Dai, Qinjie Lin, Guo Ye, Han Liu, Le Song		code	-1
Symplectic Recurrent Neural Networks	Zhengdao Chen, Jianyu Zhang, Martín Arjovsky, Léon Bottou		code	-1
Asymptotics of Wide Networks from Feynman Diagrams	Ethan Dyer, Guy GurAri		code	-1
Learning The Difference That Makes A Difference With Counterfactually-Augmented Data	Divyansh Kaushik, Eduard H. Hovy, Zachary Chase Lipton		code	-1
Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?	Simon S. Du, Sham M. Kakade, Ruosong Wang, Lin F. Yang		code	-1
Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning	Hengyuan Hu, Jakob N. Foerster		code	-1
Network Deconvolution	Chengxi Ye, Matthew Evanusa, Hua He, Anton Mitrokhin, Tom Goldstein, James A. Yorke, Cornelia Fermüller, Yiannis Aloimonos		code	-1
Neural Symbolic Reader: Scalable Integration of Distributed and Symbolic Representations for Reading Comprehension	Xinyun Chen, Chen Liang, Adams Wei Yu, Denny Zhou, Dawn Song, Quoc V. Le		code	-1
Real or Not Real, that is the Question	Yuanbo Xiangli, Yubin Deng, Bo Dai, Chen Change Loy, Dahua Lin		code	-1
Dream to Control: Learning Behaviors by Latent Imagination	Danijar Hafner, Timothy P. Lillicrap, Jimmy Ba, Mohammad Norouzi		code	-1
A Probabilistic Formulation of Unsupervised Text Style Transfer	Junxian He, Xinyi Wang, Graham Neubig, Taylor BergKirkpatrick		code	-1
Emergent Tool Use From Multi-Agent Autocurricula	Bowen Baker, Ingmar Kanitscheider, Todor M. Markov, Yi Wu, Glenn Powell, Bob McGrew, Igor Mordatch		code	-1
NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search	Xuanyi Dong, Yi Yang		code	-1
Strategies for Pre-training Graph Neural Networks	Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay S. Pande, Jure Leskovec		code	-1
Behaviour Suite for Reinforcement Learning	Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepesvári, Satinder Singh, Benjamin Van Roy, Richard S. Sutton, David Silver, Hado van Hasselt		code	-1
FreeLB: Enhanced Adversarial Training for Natural Language Understanding	Chen Zhu, Yu Cheng, Zhe Gan, Siqi Sun, Tom Goldstein, Jingjing Liu		code	-1
Kernelized Wasserstein Natural Gradient	Michael Arbel, Arthur Gretton, Wuchen Li, Guido Montúfar		code	-1
And the Bit Goes Down: Revisiting the Quantization of Neural Networks	Pierre Stock, Armand Joulin, Rémi Gribonval, Benjamin Graham, Hervé Jégou		code	-1
A Latent Morphology Model for Open-Vocabulary Neural Machine Translation	Duygu Ataman, Wilker Aziz, Alexandra Birch		code	-1
Understanding Why Neural Networks Generalize Well Through GSNR of Parameters	Jinlong Liu, Yunzhi Bai, Guoqing Jiang, Ting Chen, Huayan Wang		code	-1
Model Based Reinforcement Learning for Atari	Lukasz Kaiser, Mohammad Babaeizadeh, Piotr Milos, Blazej Osinski, Roy H. Campbell, Konrad Czechowski, Dumitru Erhan, Chelsea Finn, Piotr Kozakowski, Sergey Levine, Afroz Mohiuddin, Ryan Sepassi, George Tucker, Henryk Michalewski		code	-1
Disagreement-Regularized Imitation Learning	Kianté Brantley, Wen Sun, Mikael Henaff		code	-1
Stable Rank Normalization for Improved Generalization in Neural Networks and GANs	Amartya Sanyal, Philip H. S. Torr, Puneet K. Dokania		code	-1
Measuring the Reliability of Reinforcement Learning Algorithms	Stephanie C. Y. Chan, Samuel Fishman, Anoop Korattikara, John F. Canny, Sergio Guadarrama		code	-1
Sequential Latent Knowledge Selection for Knowledge-Grounded Dialogue	Byeongchang Kim, Jaewoo Ahn, Gunhee Kim		code	-1
Neural Tangents: Fast and Easy Infinite Neural Networks in Python	Roman Novak, Lechao Xiao, Jiri Hron, Jaehoon Lee, Alexander A. Alemi, Jascha SohlDickstein, Samuel S. Schoenholz		code	-1
Self-labelling via simultaneous clustering and representation learning	Yuki Markus Asano, Christian Rupprecht, Andrea Vedaldi		code	-1
The intriguing role of module criticality in the generalization of deep networks	Niladri S. Chatterji, Behnam Neyshabur, Hanie Sedghi		code	-1
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks	Sanjeev Arora, Simon S. Du, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang, Dingli Yu		code	-1
Differentiation of Blackbox Combinatorial Solvers	Marin Vlastelica Pogancic, Anselm Paulus, Vít Musil, Georg Martius, Michal Rolínek		code	-1
Scaling Autoregressive Video Models	Dirk Weissenborn, Oscar Täckström, Jakob Uszkoreit		code	-1
The Ingredients of Real World Robotic Reinforcement Learning	Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine		code	-1
Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization	Michael Volpp, Lukas P. Fröhlich, Kirsten Fischer, Andreas Doerr, Stefan Falkner, Frank Hutter, Christian Daniel		code	-1
Maximum Likelihood Constraint Inference for Inverse Reinforcement Learning	Dexter R. R. Scobee, S. Shankar Sastry		code	-1
Spectral Embedding of Regularized Block Models	Nathan de Lara, Thomas Bonald		code	-1
Towards Hierarchical Importance Attribution: Explaining Compositional Semantics for Neural Sequence Models	Xisen Jin, Zhongyu Wei, Junyi Du, Xiangyang Xue, Xiang Ren		code	-1
word2ket: Space-efficient Word Embeddings inspired by Quantum Entanglement	Aliakbar Panahi, Seyran Saeedi, Tomasz Arodz		code	-1
What Can Neural Networks Reason About?	Keyulu Xu, Jingling Li, Mozhi Zhang, Simon S. Du, Kenichi Kawarabayashi, Stefanie Jegelka		code	-1
Training individually fair ML models with sensitive subspace robustness	Mikhail Yurochkin, Amanda Bower, Yuekai Sun		code	-1
Learning from Rules Generalizing Labeled Exemplars	Abhijeet Awasthi, Sabyasachi Ghosh, Rasna Goyal, Sunita Sarawagi		code	-1
Directional Message Passing for Molecular Graphs	Johannes Klicpera, Janek Groß, Stephan Günnemann		code	-1
Explanation by Progressive Exaggeration	Sumedha Singla, Brian Pollack, Junxiang Chen, Kayhan Batmanghelich		code	-1
Compression based bound for non-compressed network: unified generalization error analysis of large compressible deep neural network	Taiji Suzuki, Hiroshi Abe, Tomoaki Nishimura		code	-1
At Stability's Edge: How to Adjust Hyperparameters to Preserve Minima Selection in Asynchronous Training of Neural Networks?	Niv Giladi, Mor Shpigel Nacson, Elad Hoffer, Daniel Soudry		code	-1
Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)	Peter Sorrenson, Carsten Rother, Ullrich Köthe		code	-1
Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps	Tri Dao, Nimit Sharad Sohoni, Albert Gu, Matthew Eichhorn, Amit Blonder, Megan Leszczynski, Atri Rudra, Christopher Ré		code	-1
Improving Generalization in Meta Reinforcement Learning using Learned Objectives	Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber		code	-1
Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks	Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin		code	-1
Truth or backpropaganda? An empirical investigation of deep learning theory	Micah Goldblum, Jonas Geiping, Avi Schwarzschild, Michael Moeller, Tom Goldstein		code	-1
Neural Arithmetic Units	Andreas Madsen, Alexander Rosenberg Johansen		code	-1
DeepSphere: a graph-based spherical CNN	Michaël Defferrard, Martino Milani, Frédérick Gusset, Nathanaël Perraudin		code	-1
SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models	Yucen Luo, Alex Beatson, Mohammad Norouzi, Jun Zhu, David Duvenaud, Ryan P. Adams, Ricky T. Q. Chen		code	-1
Deep Learning For Symbolic Mathematics	Guillaume Lample, François Charton		code	-1
Making Sense of Reinforcement Learning and Probabilistic Inference	Brendan O'Donoghue, Ian Osband, Catalin Ionescu		code	-1
Unbiased Contrastive Divergence Algorithm for Training Energy-Based Latent Variable Models	Yixuan Qiu, Lingsong Zhang, Xiao Wang		code	-1
A Mutual Information Maximization Perspective of Language Representation Learning	Lingpeng Kong, Cyprien de Masson d'Autume, Lei Yu, Wang Ling, Zihang Dai, Dani Yogatama		code	-1
Energy-based models for atomic-resolution protein conformations	Yilun Du, Joshua Meier, Jerry Ma, Rob Fergus, Alexander Rives		code	-1
Depth-Width Trade-offs for ReLU Networks via Sharkovsky's Theorem	Vaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas, Xiao Wang		code	-1
Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint	Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Denny Wu, Tianzong Zhang		code	-1
Reconstructing continuous distributions of 3D protein structure from cryo-EM images	Ellen D. Zhong, Tristan Bepler, Joseph H. Davis, Bonnie Berger		code	-1
Progressive Learning and Disentanglement of Hierarchical Representations	Zhiyuan Li, Jaideep Vitthal Murkute, Prashnna Kumar Gyawali, Linwei Wang		code	-1
An Exponential Learning Rate Schedule for Deep Learning	Zhiyuan Li, Sanjeev Arora		code	-1
Geom-GCN: Geometric Graph Convolutional Networks	Hongbin Pei, Bingzhe Wei, Kevin ChenChuan Chang, Yu Lei, Bo Yang		code	-1
CATER: A diagnostic dataset for Compositional Actions & TEmporal Reasoning	Rohit Girdhar, Deva Ramanan		code	-1
BackPACK: Packing more into Backprop	Felix Dangel, Frederik Kunstner, Philipp Hennig		code	-1
GenDICE: Generalized Offline Estimation of Stationary Values	Ruiyi Zhang, Bo Dai, Lihong Li, Dale Schuurmans		code	-1
Principled Weight Initialization for Hypernetworks	Oscar Chang, Lampros Flokas, Hod Lipson		code	-1
On the Convergence of FedAvg on Non-IID Data	Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, Zhihua Zhang		code	-1
Data-dependent Gaussian Prior Objective for Language Generation	Zuchao Li, Rui Wang, Kehai Chen, Masao Utiyama, Eiichiro Sumita, Zhuosheng Zhang, Hai Zhao		code	-1
Contrastive Learning of Structured World Models	Thomas N. Kipf, Elise van der Pol, Max Welling		code	-1
Neural Network Branching for Neural Network Verification	Jingyue Lu, M. Pawan Kumar		code	-1
Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity	Jingzhao Zhang, Tianxing He, Suvrit Sra, Ali Jadbabaie		code	-1
Posterior sampling for multi-agent reinforcement learning: solving extensive games with imperfect information	Yichi Zhou, Jialian Li, Jun Zhu		code	-1
Mogrifier LSTM	Gábor Melis, Tomás Kociský, Phil Blunsom		code	-1
Learning Hierarchical Discrete Linguistic Units from Visually-Grounded Speech	David Harwath, WeiNing Hsu, James R. Glass		code	-1
Mirror-Generative Neural Machine Translation	Zaixiang Zheng, Hao Zhou, Shujian Huang, Lei Li, XinYu Dai, Jiajun Chen		code	-1
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning	Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, Andrew Gordon Wilson		code	-1
Your classifier is secretly an energy based model and you should treat it like one	Will Grathwohl, KuanChieh Wang, JörnHenrik Jacobsen, David Duvenaud, Mohammad Norouzi, Kevin Swersky		code	-1
Dynamics-Aware Unsupervised Discovery of Skills	Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, Karol Hausman		code	-1
Optimal Strategies Against Generative Attacks	Roy Mor, Erez Peterfreund, Matan Gavish, Amir Globerson		code	-1
GraphZoom: A Multi-level Spectral Approach for Accurate and Scalable Graph Embedding	Chenhui Deng, Zhiqiang Zhao, Yongyu Wang, Zhiru Zhang, Zhuo Feng		code	-1
Harnessing Structures for Value-Based Planning and Reinforcement Learning	Yuzhe Yang, Guo Zhang, Zhi Xu, Dina Katabi		code	-1
Comparing Rewinding and Fine-tuning in Neural Network Pruning	Alex Renda, Jonathan Frankle, Michael Carbin		code	-1
Meta-Q-Learning	Rasool Fakoor, Pratik Chaudhari, Stefano Soatto, Alexander J. Smola		code	-1
Mathematical Reasoning in Latent Space	Dennis Lee, Christian Szegedy, Markus N. Rabe, Sarah M. Loos, Kshitij Bansal		code	-1
A Theory of Usable Information under Computational Constraints	Yilun Xu, Shengjia Zhao, Jiaming Song, Russell Stewart, Stefano Ermon		code	-1
Geometric Analysis of Nonconvex Optimization Landscapes for Overcomplete Learning	Qing Qu, Yuexiang Zhai, Xiao Li, Yuqian Zhang, Zhihui Zhu		code	-1
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds	Jordan T. Ash, Chicheng Zhang, Akshay Krishnamurthy, John Langford, Alekh Agarwal		code	-1
Understanding and Robustifying Differentiable Architecture Search	Arber Zela, Thomas Elsken, Tonmoy Saikia, Yassine Marrakchi, Thomas Brox, Frank Hutter		code	-1
A Closer Look at Deep Policy Gradients	Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry		code	-1
Implementation Matters in Deep RL: A Case Study on PPO and TRPO	Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry		code	-1
Fast Task Inference with Variational Intrinsic Successor Features	Steven Hansen, Will Dabney, André Barreto, David WardeFarley, Tom Van de Wiele, Volodymyr Mnih		code	-1
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks	Haebeom Lee, Hayeon Lee, Donghyun Na, Saehoon Kim, Minseop Park, Eunho Yang, Sung Ju Hwang		code	-1
RNA Secondary Structure Prediction By Learning Unrolled Algorithms	Xinshi Chen, Yu Li, Ramzan Umarov, Xin Gao, Le Song		code	-1
Watch the Unobserved: A Simple Approach to Parallelizing Monte Carlo Tree Search	Anji Liu, Jianshu Chen, Mingze Yu, Yu Zhai, Xuewen Zhou, Ji Liu		code	-1
Target-Embedding Autoencoders for Supervised Representation Learning	Daniel Jarrett, Mihaela van der Schaar		code	-1
Reformer: The Efficient Transformer	Nikita Kitaev, Lukasz Kaiser, Anselm Levskaya		code	-1
Rotation-invariant clustering of neuronal responses in primary visual cortex	Ivan Ustyuzhaninov, Santiago A. Cadena, Emmanouil Froudarakis, Paul G. Fahey, Edgar Y. Walker, Erick Cobos, Jacob Reimer, Fabian H. Sinz, Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker		code	-1
Causal Discovery with Reinforcement Learning	Shengyu Zhu, Ignavier Ng, Zhitang Chen		code	-1
Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems	Chris Reinke, Mayalen Etcheverry, PierreYves Oudeyer		code	-1
Restricting the Flow: Information Bottlenecks for Attribution	Karl Schulz, Leon Sixt, Federico Tombari, Tim Landgraf		code	-1
Building Deep Equivariant Capsule Networks	Sai Raam Venkataraman, S. Balasubramanian, R. Raghunatha Sarma		code	-1
A Generalized Training Approach for Multiagent Learning	Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Pérolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Rémi Munos		code	-1
High Fidelity Speech Synthesis with Adversarial Networks	Mikolaj Binkowski, Jeff Donahue, Sander Dieleman, Aidan Clark, Erich Elsen, Norman Casagrande, Luis C. Cobo, Karen Simonyan		code	-1
SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference	Lasse Espeholt, Raphaël Marinier, Piotr Stanczyk, Ke Wang, Marcin Michalski		code	-1
Meta-Learning with Warped Gradient Descent	Sebastian Flennerhag, Andrei A. Rusu, Razvan Pascanu, Francesco Visin, Hujun Yin, Raia Hadsell		code	-1
Convolutional Conditional Neural Processes	Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong, James Requeima, Yann Dubois, Richard E. Turner		code	-1
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks	Kaifeng Lyu, Jian Li		code	-1
Adversarial Training and Provable Defenses: Bridging the Gap	Mislav Balunovic, Martin T. Vechev		code	-1
Differentiable Reasoning over a Virtual Knowledge Base	Bhuwan Dhingra, Manzil Zaheer, Vidhisha Balachandran, Graham Neubig, Ruslan Salakhutdinov, William W. Cohen		code	-1
Federated Learning with Matched Averaging	Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris S. Papailiopoulos, Yasaman Khazaeni		code	-1