Hit enter to search or ESC to close

ICLR 2020 Papers with Code

admin

We identified around 200 ICLR 2020 papers that have code or data published. We list all of them in the following table. Since the extraction step is done by machines, we may miss some papers. Let us know if more papers can be added to this table.

If you do not want to miss any interesting academic paper, you are welcome to sign up our free daily paper digest service to get updates on new papers published in your area every day. You are also welcome to follow us on Twitter and Linkedin to get updated with new conference digests.

Paper Digest Team
team@paperdigest.org

Title Authors Code
1 Graph Neural Networks Exponentially Lose Expressive Power for Node Classification Kenta Oono, Taiji Suzuki link
2 Estimating Gradients for Discrete Random Variables by Sampling without Replacement Wouter Kool, Herke van Hoof, Max Welling link
3 Intensity-Free Learning of Temporal Point Processes Oleksandr Shchur, Marin Bilo�, Stephan G�nnemann link
4 PC-DARTS: Partial Channel Connections for Memory-Efficient Architecture Search Yuhui Xu, Lingxi Xie, Xiaopeng Zhang, Xin Chen, Guo-Jun Qi, Qi Tian, Hongkai Xiong link
5 Enhancing Adversarial Defense by k-Winners-Take-All Chang Xiao, Peilin Zhong, Changxi Zheng link
6 Encoding word order in complex embeddings Benyou Wang, Donghao Zhao, Christina Lioma, Qiuchi Li, Peng Zhang, Jakob Grue Simonsen link
7 Ridge Regression: Structure, Cross-Validation, and Sketching Sifan Liu, Edgar Dobriban link
8 Influence-Based Multi-Agent Exploration Tonghan Wang*, Jianhao Wang*, Yi Wu, Chongjie Zhang link
9 Duration-of-Stay Storage Assignment under Uncertainty Michael Lingzhi Li, Elliott Wolf, Daniel Wintz link
10 The Logical Expressiveness of Graph Neural Networks Pablo Barcel�, Egor V. Kostylev, Mikael Monet, Jorge P�rez, Juan Reutter, Juan Pablo Silva link
11 Disentangling neural mechanisms for perceptual grouping Junkyung Kim, Drew Linsley, Kalpit Thakkar, Thomas Serre link
12 Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees Binghong Chen, Bo Dai, Qinjie Lin, Guo Ye, Han Liu, Le Song link
13 Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning Hengyuan Hu, Jakob N Foerster link
14 Network Deconvolution Chengxi Ye, Matthew Evanusa, Hua He, Anton Mitrokhin, Thomas Goldstein, James A. Yorke, Cornelia Fermuller, Yiannis Aloimonos link
15 NAS-Bench-102: Extending the Scope of Reproducible Neural Architecture Search Xuanyi Dong, Yi Yang link
16 Behaviour Suite for Reinforcement Learning Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepezvari, Satinder Singh, Benjamin Van Roy, Richard Sutton, David Silver, Hado Van Hasselt link
17 And the Bit Goes Down: Revisiting the Quantization of Neural Networks Pierre Stock, Armand Joulin, R�mi Gribonval, Benjamin Graham, Herv� J�gou link
18 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 link
19 Neural Tangents: Fast and Easy Infinite Neural Networks in Python Roman Novak, Lechao Xiao, Jiri Hron, Jaehoon Lee, Jascha Sohl-Dickstein, Samuel S. Schoenholz link
20 Differentiation of Blackbox Combinatorial Solvers Marin Vlastelica Pogancic, Anselm Paulus, Vit Musil, Georg Martius, Michal Rolinek link
21 Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization Michael Volpp, Lukas Froehlich, Kirsten Fischer, Andreas Doerr, Stefan Falkner, Frank Hutter, Christian Daniel link
22 Maximum Likelihood Constraint Inference for Inverse Reinforcement Learning Dexter R.R. Scobee, S. Shankar Sastry link
23 Spectral Embedding of Regularized Block Models Nathan De Lara, Thomas Bonald link
24 What Can Neural Networks Reason About? Keyulu Xu, Jingling Li, Mozhi Zhang, Simon S. Du, Ken-ichi Kawarabayashi, Stefanie Jegelka link
25 Training individually fair ML models with sensitive subspace robustness Mikhail Yurochkin, Amanda Bower, Yuekai Sun link
26 Learning from Rules Generalizing Labeled Exemplars Abhijeet Awasthi, Sabyasachi Ghosh, Rasna Goyal, Sunita Sarawagi link
27 Directional Message Passing for Molecular Graphs Johannes Klicpera, Janek Gro�, Stephan G�nnemann link
28 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 link
29 Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps Tri Dao, Nimit Sohoni, Albert Gu, Matthew Eichhorn, Amit Blonder, Megan Leszczynski, Atri Rudra link
30 Neural Arithmetic Units Andreas Madsen, Alexander Rosenberg Johansen link
31 Depth-Width Trade-offs for ReLU Networks via Sharkovsky’s Theorem Vaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas, Xiao Wang link
32 Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei, Bingzhe Wei, Kevin Chen-Chuan Chang, Yu Lei, Bo Yang link
33 BackPACK: Packing more into Backprop Felix Dangel, Frederik Kunstner, Philipp Hennig link
34 Data-dependent Gaussian Prior Objective for Language Generation Zuchao Li, Rui Wang, Kehai Chen, Masso Utiyama, Eiichiro Sumita, Zhuosheng Zhang, Hai Zhao link
35 Contrastive Learning of Structured World Models Thomas Kipf, Elise van der Pol, Max Welling link
36 Optimal Strategies Against Generative Attacks Roy Mor, Erez Peterfreund, Matan Gavish, Amir Globerson link
37 GraphZoom: A Multi-level Spectral Approach for Accurate and Scalable Graph Embedding Chenhui Deng, Zhiqiang Zhao, Yongyu Wang, Zhiru Zhang, Zhuo Feng link
38 Comparing Fine-tuning and Rewinding in Neural Network Pruning Alex Renda, Jonathan Frankle, Michael Carbin link
39 Understanding and Robustifying Differentiable Architecture Search Arber Zela, Thomas Elsken, Tonmoy Saikia, Yassine Marrakchi, Thomas Brox, Frank Hutter link
40 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 link
41 Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks Donghyun Na, Hae Beom Lee, Hayeon Lee, Saehoon Kim, Minseop Park, Eunho Yang, Sung Ju Hwang link
42 Reformer: The Efficient Transformer Nikita Kitaev, Lukasz Kaiser, Anselm Levskaya link
43 Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems Chris Reinke, Mayalen Etcheverry, Pierre-Yves Oudeyer link
44 Restricting the Flow: Information Bottlenecks for Attribution Karl Schulz, Leon Sixt, Federico Tombari, Tim Landgraf link
45 Building Deep Equivariant Capsule Networks Sairaam Venkatraman, S. Balasubramanian, R. Raghunatha Sarma link
46 SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference Lasse Espeholt, Rapha�l Marinier, Piotr Stanczyk, Ke Wang, Marcin Michalski? link
47 Sharing Knowledge in Multi-Task Deep Reinforcement Learning Carlo D’Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters link
48 Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data Sergei Popov, Stanislav Morozov, Artem Babenko link
49 Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification Yixiao Ge, Dapeng Chen, Hongsheng Li link
50 Federated Adversarial Domain Adaptation Xingchao Peng, Zijun Huang, Yizhe Zhu, Kate Saenko link
51 LAMAL: LAnguage Modeling Is All You Need for Lifelong Language Learning Fan-Keng Sun, Cheng-Hao Ho, Hung-Yi Lee link
52 Distance-Based Learning from Errors for Confidence Calibration Chen Xing, Sercan Arik, Zizhao Zhang, Tomas Pfister link
53 To Relieve Your Headache of Training an MRF, Take AdVIL Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu, Bo Zhang link
54 Linear Symmetric Quantization of Neural Networks for Low-precision Integer Hardware Xiandong Zhao, Ying Wang, Xuyi Cai, Cheng Liu, Lei Zhang link
55 Weakly Supervised Clustering by Exploiting Unique Class Count Mustafa Umit Oner, Hwee Kuan Lee, Wing-Kin Sung link
56 Scalable and Order-robust Continual Learning with Additive Parameter Decomposition Jaehong Yoon, Saehoon Kim, Eunho Yang, Sung Ju Hwang link
57 On Mutual Information Maximization for Representation Learning Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic link
58 Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation Suraj Nair, Chelsea Finn link
59 Multi-agent Reinforcement Learning for Networked System Control Tianshu Chu, Sandeep Chinchali, Sachin Katti link
60 FSPool: Learning Set Representations with Featurewise Sort Pooling Yan Zhang, Jonathon Hare, Adam Pr�gel-Bennett link
61 Dynamically Pruned Message Passing Networks for Large-scale Knowledge Graph Reasoning Xiaoran Xu, Wei Feng, Yunsheng Jiang, Xiaohui Xie, Zhiqing Sun, Zhi-Hong Deng link
62 Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks Tianyu Pang*, Kun Xu*, Jun Zhu link
63 Measuring Compositional Generalization: A Comprehensive Method on Realistic Data Daniel Keysers, Nathanael Sch�rli, 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 link
64 Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness Tianyu Pang, Kun Xu, Yinpeng Dong, Chao Du, Ning Chen, Jun Zhu link
65 Learning the Arrow of Time for Problems in Reinforcement Learning Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio link
66 Robust Local Features for Improving the Generalization of Adversarial Training Chuanbiao Song, Kun He, Jiadong Lin, Liwei Wang, John E. Hopcroft link
67 Analysis of Video Feature Learning in Two-Stream CNNs on the Example of Zebrafish Swim Bout Classification Bennet Breier, Arno Onken link
68 Learning Disentangled Representations for CounterFactual Regression Negar Hassanpour, Russell Greiner link
69 Logic and the 2-Simplicial Transformer James Clift, Dmitry Doryn, Daniel Murfet, James Wallbridge link
70 Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards Allan Zhou, Eric Jang, Daniel Kappler, Alex Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, Chelsea Finn link
71 Fooling Detection Alone is Not Enough: Adversarial Attack against Multiple Object Tracking Yunhan Jia, Yantao Lu, Junjie Shen, Qi Alfred Chen, Hao Chen, Zhenyu Zhong, Tao Wei link
72 Accelerating SGD with momentum for over-parameterized learning Chaoyue Liu, Mikhail Belkin link
73 Progressive Memory Banks for Incremental Domain Adaptation Nabiha Asghar, Lili Mou, Kira A. Selby, Kevin D. Pantasdo, Pascal Poupart, Xin Jiang link
74 Few-shot Text Classification with Distributional Signatures Yujia Bao, Menghua Wu, Shiyu Chang, Regina Barzilay link
75 Adversarial Policies: Attacking Deep Reinforcement Learning Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, Stuart Russell link
76 VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma link
77 GLAD: Learning Sparse Graph Recovery Harsh Shrivastava, Xinshi Chen, Binghong Chen, Guanghui Lan, Srinivas Aluru, Han Liu, Le Song link
78 Editable Neural Networks Anton Sinitsin, Vsevolod Plokhotnyuk, Dmitry Pyrkin, Sergei Popov, Artem Babenko link
79 LEARNING EXECUTION THROUGH NEURAL CODE FUSION Zhan Shi, Kevin Swersky, Daniel Tarlow, Parthasarathy Ranganathan, Milad Hashemi link
80 FasterSeg: Searching for Faster Real-time Semantic Segmentation Wuyang Chen, Xinyu Gong, Xianming Liu, Qian Zhang, Yuan Li, Zhangyang Wang link
81 Difference-Seeking Generative Adversarial Network–Unseen Sample Generation Yi Lin Sung, Sung-Hsien Hsieh, Soo-Chang Pei, Chun-Shien Lu link
82 Stochastic AUC Maximization with Deep Neural Networks Mingrui Liu, Zhuoning Yuan, Yiming Ying, Tianbao Yang link
83 MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang link
84 Adversarial Example Detection and Classification with Asymmetrical Adversarial Training Xuwang Yin, Soheil Kolouri, Gustavo K Rohde link
85 Variational Recurrent Models for Solving Partially Observable Control Tasks Dongqi Han, Kenji Doya, Jun Tani link
86 Black-Box Adversarial Attack with Transferable Model-based Embedding Zhichao Huang, Tong Zhang link
87 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 link
88 Gap-Aware Mitigation of Gradient Staleness Saar Barkai, Ido Hakimi, Assaf Schuster link
89 Counterfactuals uncover the modular structure of deep generative models Michel Besserve, Arash Mehrjou, Remy Sun, Bernhard Schoelkopf link
90 NAS evaluation is frustratingly hard Antoine Yang, Pedro M. Esperan�a, Fabio M. Carlucci link
91 Efficient and Information-Preserving Future Frame Prediction and Beyond Wei Yu, Yichao Lu, Steve Easterbrook, Sanja Fidler link
92 A Fair Comparison of Graph Neural Networks for Graph Classification Federico Errica, Marco Podda, Davide Bacciu, Alessio Micheli link
93 SAdam: A Variant of Adam for Strongly Convex Functions Guanghui Wang, Shiyin Lu, Quan Cheng, Weiwei Tu, Lijun Zhang link
94 FEW-SHOT LEARNING ON GRAPHS VIA SUPER-CLASSES BASED ON GRAPH SPECTRAL MEASURES Jatin Chauhan, Deepak Nathani, Manohar Kaul link
95 A TARGET-AGNOSTIC ATTACK ON DEEP MODELS: EXPLOITING SECURITY VULNERABILITIES OF TRANSFER LEARNING Shahbaz Rezaei, Xin Liu link
96 Generative Ratio Matching Networks Akash Srivastava, Kai Xu, Michael U. Gutmann, Charles Sutton link
97 Option Discovery using Deep Skill Chaining Akhil Bagaria, George Konidaris link
98 On the Variance of the Adaptive Learning Rate and Beyond Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Jiawei Han link
99 Language GANs Falling Short Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin link
100 Sign Bits Are All You Need for Black-Box Attacks Abdullah Al-Dujaili, Una-May O’Reilly link
101 Deep Semi-Supervised Anomaly Detection Lukas Ruff, Robert A. Vandermeulen, Nico G�rnitz, Alexander Binder, Emmanuel M�ller, Klaus-Robert M�ller, Marius Kloft link
102 Adaptive Structural Fingerprints for Graph Attention Networks Kai Zhang, Yaokang Zhu, Jun Wang, Jie Zhang link
103 Pure and Spurious Critical Points: a Geometric Study of Linear Networks Matthew Trager, Kathl�n Kohn, Joan Bruna link
104 Neural Text Generation With Unlikelihood Training Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, Jason Weston link
105 Dynamic Time Lag Regression: Predicting What & When Mandar Chandorkar, Cyril Furtlehner, Bala Poduval, Enrico Camporeale, Michele Sebag link
106 Overlearning Reveals Sensitive Attributes Congzheng Song, Vitaly Shmatikov link
107 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, Pierre-Antoine Manzagol, Hugo Larochelle link
108 Learning Space Partitions for Nearest Neighbor Search Yihe Dong, Piotr Indyk, Ilya Razenshteyn, Tal Wagner link
109 Toward Amortized Ranking-Critical Training For Collaborative Filtering Sam Lobel, Chunyuan Li, Jianfeng Gao, Lawrence Carin link
110 The function of contextual illusions Drew Linsley, Junkyung Kim, Alekh Ashok, Thomas Serre link
111 Fast is better than free: Revisiting adversarial training Eric Wong, Leslie Rice, J. Zico Kolter link
112 Four Things Everyone Should Know to Improve Batch Normalization Cecilia Summers, Michael J. Dinneen link
113 Learning to Learn by Zeroth-Order Oracle Yangjun Ruan, Yuanhao Xiong, Sashank Reddi, Sanjiv Kumar, Cho-Jui Hsieh link
114 Decentralized Distributed PPO: Mastering PointGoal Navigation Erik Wijmans, Abhishek Kadian, Ari Morcos, Stefan Lee, Irfan Essa, Devi Parikh, Manolis Savva, Dhruv Batra link
115 Precision Gating: Improving Neural Network Efficiency with Dynamic Dual-Precision Activations Yichi Zhang, Ritchie Zhao, Weizhe Hua, Nayun Xu, Edward Suh, Zhiru Zhang link
116 Span Recovery for Deep Neural Networks with Applications to Input Obfuscation Rajesh Jayaram, David P. Woodruff, Qiuyi Zhang link
117 Learn to Explain Efficiently via Neural Logic Inductive Learning Yuan Yang, Le Song link
118 Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling Hao Zhang, Bo Chen, Long Tian, Zhengjue Wang, Mingyuan Zhou link
119 Composition-based Multi-Relational Graph Convolutional Networks Shikhar Vashishth, Soumya Sanyal, Vikram Nitin, Partha Talukdar link
120 Gradient-Based Neural DAG Learning S�bastien Lachapelle, Philippe Brouillard, Tristan Deleu, Simon Lacoste-Julien link
121 Composing Task-Agnostic Policies with Deep Reinforcement Learning Ahmed H. Qureshi, Jacob J. Johnson, Yuzhe Qin, Taylor Henderson, Byron Boots, Michael C. Yip link
122 Convergence Behaviour of Some Gradient-Based Methods on Bilinear Zero-Sum Games Guojun Zhang, Yaoliang Yu link
123 Learning from Explanations with Neural Module Execution Tree Yujia Qin, Ziqi Wang, Wenxuan Zhou, Jun Yan, Qinyuan Ye, Xiang Ren, Leonardo Neves, Zhiyuan Liu link
124 Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality Saurabh Khanna, Vincent Y. F. Tan link
125 TOWARDS STABILIZING BATCH STATISTICS IN BACKWARD PROPAGATION OF BATCH NORMALIZATION Junjie Yan, Ruosi Wan, Xiangyu Zhang, Wei Zhang, Yichen Wei, Jian Sun link
126 Transformer-XH: Multi-hop question answering with eXtra Hop attention Chen Zhao, Chenyan Xiong, Corby Rosset, Xia Song, Paul Bennett, Saurabh Tiwary link
127 A Closer Look at the Optimization Landscapes of Generative Adversarial Networks Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien link
128 Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators Reinhard Heckel and Mahdi Soltanolkotabi link
129 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 Aguera y Arcas link
130 Inductive representation learning on temporal graphs da Xu, chuanwei ruan, evren korpeoglu, sushant kumar, kannan achan link
131 Learning representations for binary-classification without backpropagation Mathias Lechner link
132 HiLLoC: lossless image compression with hierarchical latent variable models James Townsend, Thomas Bird, Julius Kunze, David Barber link
133 Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation Xinjie Fan, Yizhe Zhang, Zhendong Wang, Mingyuan Zhou link
134 PairNorm: Tackling Oversmoothing in GNNs Lingxiao Zhao, Leman Akoglu link
135 Unsupervised Clustering using Pseudo-semi-supervised Learning Divam Gupta, Ramachandran Ramjee, Nipun Kwatra, Muthian Sivathanu link
136 Quantum Algorithms for Deep Convolutional Neural Networks Iordanis Kerenidis, Jonas Landman, Anupam Prakash link
137 Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers Junjie LIU, Zhe XU, Runbin SHI, Ray C. C. Cheung, Hayden K.H. So link
138 GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation Chence Shi*, Minkai Xu*, Zhaocheng Zhu, Weinan Zhang, Ming Zhang, Jian Tang link
139 Graph Convolutional Reinforcement Learning Jiechuan Jiang, Chen Dun, Tiejun Huang, Zongqing Lu link
140 Multi-Agent Interactions Modeling with Correlated Policies Minghuan Liu, Ming Zhou, Weinan Zhang, Yuzheng Zhuang, Jun Wang, Wulong Liu, Yong Yu link
141 Implementing Inductive bias for different navigation tasks through diverse RNN attrractors Tie XU, Omri Barak link
142 Plug and Play Language Model: A simple baseline for controlled language generation Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, Rosanne Liu link
143 Pad� Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks Alejandro Molina, Patrick Schramowski, Kristian Kersting link
144 Explain Your Move: Understanding Agent Actions Using Focused Feature Saliency Piyush Gupta, Nikaash Puri, Sukriti Verma, Dhruv Kayastha, Shripad Deshmukh, Balaji Krishnamurthy, Sameer Singh link
145 Meta Dropout: Learning to Perturb Latent Features for Generalization Hae Beom Lee, Taewook Nam, Eunho Yang, Sung Ju Hwang link
146 Learning transport cost from subset correspondence Ruishan Liu, Akshay Balsubramani, James Zou link
147 Variance Reduction With Sparse Gradients Melih Elibol, Lihua Lei, Michael I. Jordan link
148 Weakly Supervised Disentanglement with Guarantees Rui Shu, Yining Chen, Abhishek Kumar, Stefano Ermon, Ben Poole link
149 Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks Jiadong Lin, Chuanbiao Song, Kun He, Liwei Wang, John E. Hopcroft link
150 Fantastic Generalization Measures and Where to Find Them Yiding Jiang*, Behnam Neyshabur*, Dilip Krishnan, Hossein Mobahi, Samy Bengio link
151 Tensor Decompositions for Temporal Knowledge Base Completion Timoth�e Lacroix, Guillaume Obozinski, Nicolas Usunier link
152 Hyper-SAGNN: a self-attention based graph neural network for hypergraphs Ruochi Zhang, Yuesong Zou, Jian Ma link
153 DropEdge: Towards Deep Graph Convolutional Networks on Node Classification Yu Rong, Wenbing Huang, Tingyang Xu, Junzhou Huang link
154 Masked Based Unsupervised Content Transfer Ron Mokady, Sagie Benaim, Lior Wolf, Amit Bermano link
155 U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation Junho Kim, Minjae Kim, Hyeonwoo Kang, Kwang Hee Lee link
156 Learning Robust Representations via Multi-View Information Bottleneck Marco Federici, Anjan Dutta, Patrick Forr�, Nate Kushman, Zeynep Akata link
157 Robust anomaly detection and backdoor attack detection via differential privacy Min Du, Ruoxi Jia, Dawn Song link
158 Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel Xin Qiu, Elliot Meyerson, Risto Miikkulainen link
159 B-Spline CNNs on Lie groups Erik J Bekkers link
160 Efficient Probabilistic Logic Reasoning with Graph Neural Networks Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, Le Song link
161 GraphSAINT: Graph Sampling Based Inductive Learning Method Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor Prasanna link
162 Projection Based Constrained Policy Optimization Tsung-Yen Yang, Justinian Rosca, Karthik Narasimhan, Peter J. Ramadge link
163 Training Generative Adversarial Networks from Incomplete Observations using Factorised Discriminators Daniel Stoller, Sebastian Ewert, Simon Dixon link
164 Decentralized Deep Learning with Arbitrary Communication Compression Anastasia Koloskova*, Tao Lin*, Sebastian U Stich, Martin Jaggi link
165 On the Relationship between Self-Attention and Convolutional Layers Jean-Baptiste Cordonnier, Andreas Loukas, Martin Jaggi link
166 Learning-Augmented Data Stream Algorithms Tanqiu Jiang, Yi Li, Honghao Lin, Yisong Ruan, David P. Woodruff link
167 Structured Object-Aware Physics Prediction for Video Modeling and Planning Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting link
168 Incorporating BERT into Neural Machine Translation Jinhua Zhu, Yingce Xia, Lijun Wu, Di He, Tao Qin, Wengang Zhou, Houqiang Li, Tieyan Liu link
169 Meta-learning curiosity algorithms Ferran Alet*, Martin F. Schneider*, Tomas Lozano-Perez, Leslie Pack Kaelbling link
170 Lookahead: A Far-sighted Alternative of Magnitude-based Pruning Sejun Park*, Jaeho Lee*, Sangwoo Mo, Jinwoo Shin link
171 Spike-based causal inference for weight alignment Jordan Guerguiev, Konrad Kording, Blake Richards link
172 Empirical Bayes Transductive Meta-Learning with Synthetic Gradients Xu Hu, Pablo Moreno, Yang Xiao, Xi Shen, Guillaume Obozinski, Neil Lawrence link
173 Demystifying Inter-Class Disentanglement Aviv Gabbay, Yedid Hoshen link
174 Mixed-curvature Variational Autoencoders Ondrej Skopek, Gary B�cigneul, Octavian-Eugen Ganea link
175 BinaryDuo: Reducing Gradient Mismatch in Binary Activation Network by Coupling Binary Activations Hyungjun Kim, Kyungsu Kim, Jinseok Kim, Jae-Joon Kim link
176 BayesOpt Adversarial Attack Binxin Ru, Adam Cobb, Arno Blaas, Yarin Gal link
177 RaPP: Novelty Detection with Reconstruction along Projection Pathway Ki Hyun Kim, Sangwoo Shim, Yongsub Lim, Jongseob Jeon, Jeongwoo Choi, Byungchan Kim, Andre S. Yoon link
178 Dynamics-Aware Embeddings William Whitney, Rajat Agarwal, Kyunghyun Cho, Abhinav Gupta link
179 AdvectiveNet: An Eulerian-Lagrangian Fluidic Reservoir for Point Cloud Processing Xingzhe He, Helen Lu Cao, Bo Zhu link
180 AtomNAS: Fine-Grained End-to-End Neural Architecture Search Jieru Mei, Yingwei Li, Xiaochen Lian, Xiaojie Jin, Linjie Yang, Alan Yuille, Jianchao Yang link
181 Deep Audio Priors Emerge From Harmonic Convolutional Networks Zhoutong Zhang, Yunyun Wang, Chuang Gan, Jiajun Wu, Joshua B. Tenenbaum, Antonio Torralba, William T. Freeman link
182 Expected Information Maximization: Using the I-Projection for Mixture Density Estimation Philipp Becker, Oleg Arenz, Gerhard Neumann link
183 A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sebastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher Pal link
184 Latent Normalizing Flows for Many-to-Many Cross Domain Mappings Shweta Mahajan, Iryna Gurevych, Stefan Roth link
185 Adversarial Lipschitz Regularization D�vid Terj�k link
186 Compositional Continual Language Learning Yuanpeng Li, Liang Zhao, Kenneth Church, Mohamed Elhoseiny link
187 HOW THE CHOICE OF ACTIVATION AFFECTS TRAINING OF OVERPARAMETRIZED NEURAL NETS Abhishek Panigrahi, Abhishek Shetty, Navin Goyal link
188 Lipschitz constant estimation for Neural Networks via sparse polynomial optimization Fabian Latorre, Paul Rolland, Volkan Cevher link
189 Unrestricted Adversarial Examples via Semantic Manipulation Anand Bhattad, Min Jin Chong, Kaizhao Liang, Bo Li, David Forsyth link
190 Differentiable Programming for Physical Simulation Yuanming Hu, Luke Anderson, Tzu-Mao Li, Qi Sun, Nathan Carr, Jonathan Ragan-Kelley, Fredo Durand link
191 Sub-policy Adaptation for Hierarchical Reinforcement Learning Alexander Li, Carlos Florensa, Ignasi Clavera, Pieter Abbeel link
192 Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Ocurring in Data David W. Romero Guzm�n, Mark Hoogendoorn link
193 Information Geometry of Orthogonal Initializations and Training Piotr Aleksander Sok�l, Il Memming Park link
194 Extreme Classification via Adversarial Softmax Approximation Robert Bamler, Stephan Mandt link
195 NAS-BENCH-1SHOT1: BENCHMARKING AND DISSECTING ONE-SHOT NEURAL ARCHITECTURE SEARCH Arber Zela, Julien Siems, Frank Hutter link
196 The Shape of Data: Intrinsic Distance for Data Distributions Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alex Bronstein, Ivan Oseledets, Emmanuel Mueller link
197 Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy link
198 Massively Multilingual Sparse Word Representations G�bor Berend link
199 Learning The Difference That Makes A Difference With Counterfactually-Augmented Data Divyansh Kaushik, Eduard Hovy, Zachary Lipton link