104 Results

Tutorial
Mon 1:00 Representation Learning Without Labels
S. M. Ali Eslami, Irina Higgins, Danilo J. Rezende
Poster
Tue 7:00 Improving Generative Imagination in Object-Centric World Models
Zhixuan Lin, Yi-Fu Wu, Skand Peri, Bofeng Fu, Jindong Jiang, Sungjin Ahn
Poster
Tue 7:00 A Simple Framework for Contrastive Learning of Visual Representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey Hinton
Poster
Tue 7:00 On Variational Learning of Controllable Representations for Text without Supervision
Peng Xu, Jackie Chi Kit Cheung, Yanshuai Cao
Poster
Tue 7:00 ControlVAE: Controllable Variational Autoencoder
Huajie Shao, Shuochao Yao, Dachun Sun, Aston Zhang, Shengzhong Liu, Dongxin Liu, Jun Wang, Tarek Abdelzaher
Poster
Tue 7:00 Differentiating through the Fréchet Mean
Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge Belongie, Sernam Lim Lim, Christopher De Sa
Poster
Tue 7:00 Contrastive Multi-View Representation Learning on Graphs
Kaveh Hassani, Amir Hosein Khasahmadi
Poster
Tue 7:00 Nested Subspace Arrangement for Representation of Relational Data
Nozomi Hata, Shizuo Kaji, Akihiro Yoshida, Katsuki Fujisawa
Poster
Tue 7:00 Distance Metric Learning with Joint Representation Diversification
Xu Chu, Yang Lin, Yasha Wang, Xiting Wang, Hailong Yu, Xin Gao, Qi Tong
Poster
Tue 7:00 Simple and Deep Graph Convolutional Networks
Ming Chen, Zhewei Wei, Zengfeng Huang, Bolin Ding, Yaliang Li
Poster
Tue 7:00 A Free-Energy Principle for Representation Learning
Yansong Gao, Pratik Chaudhari
Poster
Tue 7:00 Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees
Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar
Poster
Tue 8:00 Parameterized Rate-Distortion Stochastic Encoder
Quan Hoang, Trung Le, Dinh Phung
Poster
Tue 8:00 Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
Baifeng Shi, Dinghuai Zhang, Qi Dai, Zhanxing Zhu, Yadong Mu, Jingdong Wang
Poster
Tue 8:00 DROCC: Deep Robust One-Class Classification
Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain
Poster
Tue 8:00 Representations for Stable Off-Policy Reinforcement Learning
Dibya Ghosh, Marc Bellemare
Poster
Tue 9:00 Retrieval Augmented Language Model Pre-Training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, Mingwei Chang
Poster
Tue 10:00 A Sample Complexity Separation between Non-Convex and Convex Meta-Learning
Nikunj Saunshi, Yi Zhang, Misha Khodak, Sanjeev Arora
Poster
Tue 10:00 Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning
Zhaohan Guo, Bernardo Avila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Remi Munos, Mohammad Gheshlaghi Azar
Poster
Tue 10:00 Automatic Shortcut Removal for Self-Supervised Representation Learning
Matthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen
Poster
Tue 10:00 Generative Pretraining From Pixels
Mark Chen, Alec Radford, Rewon Child, Jeffrey K Wu, Heewoo Jun, David Luan, Ilya Sutskever
Poster
Tue 10:00 Topological Autoencoders
Michael Moor, Max Horn, Bastian Rieck, Karsten Borgwardt
Poster
Tue 10:00 Revisiting Spatial Invariance with Low-Rank Local Connectivity
Gamaleldin Elsayed, Prajit Ramachandran, Jon Shlens, Simon Kornblith
Poster
Tue 11:00 Explainable and Discourse Topic-aware Neural Language Understanding
Yatin Chaudhary, Hinrich Schuetze, Pankaj Gupta
Poster
Tue 12:00 Weakly-Supervised Disentanglement Without Compromises
Francesco Locatello, Ben Poole, Gunnar Ratsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen
Poster
Tue 12:00 Learning Portable Representations for High-Level Planning
Steve James, Benjamin Rosman, George Konidaris
Poster
Tue 13:00 An Explicitly Relational Neural Network Architecture
Murray Shanahan, Kyriacos Nikiforou, Antonia Creswell, Christos Kaplanis, David GT Barrett, Marta Garnelo
Poster
Tue 13:00 Graph Random Neural Features for Distance-Preserving Graph Representations
Daniele Zambon, Cesare Alippi, Lorenzo Livi
Poster
Tue 13:00 Latent Space Factorisation and Manipulation via Matrix Subspace Projection
Xiao Li, Chenghua Lin, Ruizhe Li, Chaozheng Wang, Frank Guerin
Poster
Tue 13:00 Learning with Good Feature Representations in Bandits and in RL with a Generative Model
Tor Lattimore, Csaba Szepesvari, Gellért Weisz
Poster
Tue 13:00 Generalization to New Actions in Reinforcement Learning
Ayush Jain, Andrew Szot, Joseph Lim
Poster
Tue 13:00 Uncertainty Estimation Using a Single Deep Deterministic Neural Network
Joost van Amersfoort, Lewis Smith, Yee Whye Teh, Yarin Gal
Poster
Tue 13:00 Constant Curvature Graph Convolutional Networks
Gregor Bachmann, Gary Becigneul, Octavian Ganea
Poster
Tue 14:00 Why bigger is not always better: on finite and infinite neural networks
Laurence Aitchison
Poster
Tue 15:00 Estimating Generalization under Distribution Shifts via Domain-Invariant Representations
Ching-Yao Chuang, Antonio Torralba, Stefanie Jegelka
Poster
Tue 15:00 Invariant Causal Prediction for Block MDPs
Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup
Poster
Tue 18:00 Learning De-biased Representations with Biased Representations
Hyojin Bahng, SANGHYUK CHUN, Sangdoo Yun, Jaegul Choo, Seong Joon Oh
Poster
Wed 5:00 Learnable Group Transform For Time-Series
Romain Cosentino, Behnaam Aazhang
Poster
Wed 5:00 Stabilizing Transformers for Reinforcement Learning
Emilio Parisotto, Francis Song, Jack Rae, Razvan Pascanu, Caglar Gulcehre, Siddhant Jayakumar, Max Jaderberg, Raphael Lopez Kaufman, Aidan Clark, Seb Noury, Matthew Botvinick, Nicolas Heess, Raia Hadsell
Poster
Wed 8:00 InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs
Zinan Lin, Kiran Thekumparampil, Giulia Fanti, Sewoong Oh
Poster
Wed 8:00 Learning and Evaluating Contextual Embedding of Source Code
Aditya Kanade, Petros Maniatis, Gogul Balakrishnan, Kensen Shi
Poster
Wed 8:00 Inductive Relation Prediction by Subgraph Reasoning
Komal Teru, Etienne Denis, Will Hamilton
Poster
Wed 10:00 Provable Representation Learning for Imitation Learning via Bi-level Optimization
Sanjeev Arora, Simon Du, Sham Kakade, Yuping Luo, Nikunj Saunshi
Poster
Wed 10:00 Evolutionary Topology Search for Tensor Network Decomposition
Chao Li, Zhun Sun
Poster
Wed 10:00 Self-supervised Label Augmentation via Input Transformations
Hankook Lee, Sung Ju Hwang, Jinwoo Shin
Poster
Wed 11:00 Robust Graph Representation Learning via Neural Sparsification
Cheng Zheng, Bo Zong, Wei Cheng, Dongjin Song, Jingchao Ni, Wenchao Yu, Haifeng Chen, Wei Wang
Poster
Wed 11:00 DeBayes: a Bayesian Method for Debiasing Network Embeddings
Maarten Buyl, Tijl De Bie
Poster
Wed 11:00 Option Discovery in the Absence of Rewards with Manifold Analysis
Amitay Bar, Ronen Talmon, Ron Meir
Poster
Wed 12:00 Equivariant Neural Rendering
Emilien Dupont, Miguel Angel Bautista Martin, Alex Colburn, Aditya Sankar, Josh Susskind, Qi Shan
Poster
Wed 12:00 Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning"
Saeed Amizadeh, Hamid Palangi, Alex Polozov, Yichen Huang, Kazuhito Koishida
Poster
Wed 13:00 Fast Adaptation to New Environments via Policy-Dynamics Value Functions
Roberta Raileanu, Max Goldstein, Arthur Szlam, Facebook Rob Fergus
Poster
Wed 14:00 Let's Agree to Agree: Neural Networks Share Classification Order on Real Datasets
Guy Hacohen, Leshem Choshen, Daphna Weinshall
Poster
Thu 6:00 Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks
Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein
Poster
Thu 6:00 Universal Equivariant Multilayer Perceptrons
Siamak Ravanbakhsh
Poster
Thu 6:00 Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
Tongzhou Wang, Phillip Isola
Poster
Thu 6:00 Continuous Graph Neural Networks
Louis-Pascal Xhonneux, Meng Qu, Jian Tang
Poster
Thu 6:00 Mapping natural-language problems to formal-language solutions using structured neural representations
Kezhen Chen, Qiuyuan Huang, Hamid Palangi, Paul Smolensky, Ken Forbus, Jianfeng Gao
Poster
Thu 6:00 Latent Variable Modelling with Hyperbolic Normalizing Flows
Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, Will Hamilton
Poster
Thu 6:00 Adaptive Adversarial Multi-task Representation Learning
YUREN MAO, Weiwei Liu, Xuemin Lin
Poster
Thu 6:00 Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space
Yingyi Ma, Vignesh Ganapathiraman, Yaoliang Yu, Xinhua Zhang
Poster
Thu 7:00 Semi-Supervised StyleGAN for Disentanglement Learning
Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit Patel, Anima Anandkumar
Poster
Thu 7:00 Educating Text Autoencoders: Latent Representation Guidance via Denoising
Tianxiao Shen, Jonas Mueller, Regina Barzilay, Tommi Jaakkola
Poster
Thu 7:00 Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning
Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford
Poster
Thu 9:00 When Does Self-Supervision Help Graph Convolutional Networks?
Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
Poster
Thu 9:00 Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
Tim Liang, Dapeng Hu, Jiashi Feng
Poster
Thu 9:00 Energy-Based Processes for Exchangeable Data
Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans
Poster
Thu 9:00 CURL: Contrastive Unsupervised Representations for Reinforcement Learning
Michael Laskin, Aravind Srinivas, Pieter Abbeel
Poster
Thu 12:00 Online Continual Learning from Imbalanced Data
Aristotelis Chrysakis, Marie-Francine Moens
Poster
Thu 12:00 Data-Efficient Image Recognition with Contrastive Predictive Coding
Olivier Henaff
Poster
Thu 12:00 Learning Flat Latent Manifolds with VAEs
Nutan Chen, Alexej Klushyn, Francesco Ferroni, Justin Bayer, Patrick van der Smagt
Poster
Thu 12:00 Predictive Coding for Locally-Linear Control
Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung Bui
Poster
Thu 12:00 Topologically Densified Distributions
Christoph Hofer, Florian Graf, Marc Niethammer, Roland Kwitt
Poster
Thu 13:00 Stochastic Latent Residual Video Prediction
Jean-Yves Franceschi, Edouard Delasalles, Mickael Chen, Sylvain Lamprier, Patrick Gallinari
Poster
Thu 13:00 A Generative Model for Molecular Distance Geometry
Gregor Simm, Jose Miguel Hernandez-Lobato
Poster
Thu 13:00 Graph Filtration Learning
Christoph Hofer, Florian Graf, Bastian Rieck, Marc Niethammer, Roland Kwitt
Poster
Thu 14:00 Probing Emergent Semantics in Predictive Agents via Question Answering
Abhishek Das, Federico Carnevale, Hamza Merzic, Laura Rimell, Rosalia Schneider, Josh Abramson, Alden Hung, Arun Ahuja, Stephen Clark, Greg Wayne, Feilx Hill
Poster
Thu 14:00 Variational Autoencoders with Riemannian Brownian Motion Priors
Dimitris Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg
Poster
Thu 17:00 Representation Learning via Adversarially-Contrastive Optimal Transport
Anoop Cherian, Shuchin Aeron
Workshop
Thu 23:40 Graph Representation Learning and Beyond (GRL+)
Petar Veličković, Michael M. Bronstein, Andreea Deac, Will Hamilton, Jessica Hamrick, Milad Hashemi, Stefanie Jegelka, Jure Leskovec, Renjie Liao, Federico Monti, Yizhou Sun, Kevin Swersky, Zhitao Ying, Marinka Žitnik
Workshop
Fri 0:15 Invited Talk: Representation learning on sequential data with latent priors
Jan Chorowski
Workshop
Fri 0:40 Invited Talk: Contrastive Predictive Coding for audio representation learning
Aäron van den Oord
Workshop
Fri 1:30 Adversarial representation learning for private speech generation
David Ericsson
Workshop
Fri 2:00 Analysis of Predictive Coding Models for Phonemic Representation Learning in Small Datasets
María Andrea Cruz Blandón
Workshop
Fri 2:15 COALA: Co-Aligned Autoencoders for Learning Semantically Enriched Audio Representations
Xavier Favory
Workshop
Fri 4:30 Original Research: Get Rid of Suspended Animation: Deep Diffusive Neural Network for Graph Representation Learning
Jiawei Zhang
Workshop
Fri 6:00 ICML 2020 Workshop on Computational Biology
Delasa Aghamirzaie, Alexander Anderson, Elham Azizi, Abdoulaye Baniré Diallo, Cassandra Burdziak, Jill Gallaher, Anshul Kundaje, Dana Pe'er, Sandhya Prabhakaran, Amine Remita, Mark Robertson-Tessi, Wesley Tansey, Julia Vogt, Yubin Xie
Workshop
Fri 6:15 Using Self-Supervised Learning of Birdsong for Downstream Industrial Audio Classification
Patty Ryan
Workshop
Fri 6:30 Theoretical Foundations of Reinforcement Learning
Emma Brunskill, Thodoris Lykouris, Max Simchowitz, Wen Sun, Mengdi Wang
Workshop
Fri 6:45 COVID-19 Applications: Navigating the Dynamics of Financial Embeddings over Time
Antonia Gogoglou
Workshop
Fri 8:20 Unsupervised Object Keypoint Learning using Local Spatial Predictability
Anand Gopalakrishnan
Workshop
Fri 8:35 Paper spotlight: Deep Representation Learning and Clustering of Traffic Scenarios
Nick Harmening, Stephan Günnemann, Marin Biloš
Workshop
Fri 8:35 Paper Q&A session 1
Workshop
Fri 8:40 Self-supervised Pitch Detection by Inverse Audio Synthesis
JesseEngel Engel
Workshop
Fri 13:45 [Session 1] P#11 Modeling Brain Microarchitecture with Deep Representation Learning
Workshop
Fri 14:15 Paper Q&A session 2
Workshop
Fri 14:20 Representation learning and exploration in reinforcement learning - Akshay Krishnamurthy
Akshay Krishnamurthy
Workshop
Fri 15:50 Hierarchical Decomposition and Generation of Scenes with Compositional Objects
Fei Deng
Workshop
Sat 5:50 Bridge Between Perception and Reasoning: Graph Neural Networks & Beyond
Jian Tang, Le Song, Jure Leskovec, Renjie Liao, Yujia Li, Sanja Fidler, Richard Zemel, Russ Salakhutdinov
Workshop
Sat 7:15 Invited Talk: Lifelong Learning: Towards Broad and Robust AI by Irina Rish
Irina Rish
Workshop
(#40 / Sess. 2) HNHN: Hypergraph Networks with Hyperedge Neurons
Yihe Dong
Workshop
(#12 / Sess. 1) Deep Graph Contrastive Representation Learning
Yanqiao Zhu
Workshop
(#94 / Sess. 2) Are Hyperbolic Representations in Graphs Created Equal?
Max Kochurov
Workshop
(#26 / Sess. 2) Message Passing Query Embedding
Daniel Daza
Workshop
(#31 / Sess. 2) Generalized Multi-Relational Graph Convolution Network
Donghan Yu