Papers
Learning Disentangled Representations and Group Structure of Dynamical Environments
Robin Quessard, Thomas Barrett, William Clements
Learning Disentangled Representations of Videos with Missing Data
Armand Comas, Chi Zhang, Zlatan Feric et al.
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction
Yaodong Yu, Kwan Ho Ryan Chan, Chong You et al.
Learning Dynamic Belief Graphs to Generalize on Text-Based Games
Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté et al.
Learning efficient task-dependent representations with synaptic plasticity
Colin Bredenberg, Eero P. Simoncelli, Cristina Savin
Learning Feature Sparse Principal Subspace
Lai Tian, Feiping Nie, Rong Wang et al.
Learning from Aggregate Observations
Yivan Zhang, Nontawat Charoenphakdee, Zhenguo Wu et al.
Learning from Failure: De-biasing Classifier from Biased Classifier
Junhyun Nam, Hyuntak Cha, Sungsoo Ahn et al.
Learning from Label Proportions: A Mutual Contamination Framework
Clayton Scott, Jianxin Zhang
Learning from Mixtures of Private and Public Populations
Raef Bassily, Shay Moran, Anupama Nandi
Learning from Positive and Unlabeled Data with Arbitrary Positive Shift
Zayd Hammoudeh, Daniel Lowd
Learning Global Transparent Models consistent with Local Contrastive Explanations
Tejaswini Pedapati, Avinash Balakrishnan, Karthikeyan Shanmugam et al.
Learning Graph Structure With A Finite-State Automaton Layer
Daniel Johnson, Hugo Larochelle, Daniel Tarlow
Learning Guidance Rewards with Trajectory-space Smoothing
Tanmay Gangwani, Yuan Zhou, Jian Peng
Learning Implicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning
Meng Zhou, Ziyu Liu, Pengwei Sui et al.
Learning Implicit Functions for Topology-Varying Dense 3D Shape Correspondence
Feng Liu, Xiaoming Liu
Learning Individually Inferred Communication for Multi-Agent Cooperation
Ziluo Ding, Tiejun Huang, Zongqing Lu
Learning Invariances in Neural Networks from Training Data
Gregory Benton, Marc Finzi, Pavel Izmailov et al.
Learning Invariants through Soft Unification
Nuri Cingillioglu, Alessandra Russo
Learning Kernel Tests Without Data Splitting
Jonas Kübler, Wittawat Jitkrittum, Bernhard Schölkopf et al.
Learning Latent Space Energy-Based Prior Model
Bo Pang, Tian Han, Erik Nijkamp et al.
Learning Linear Programs from Optimal Decisions
Yingcong Tan, Daria Terekhov, Andrew Delong
Learning Loss for Test-Time Augmentation
Ildoo Kim, Younghoon Kim, Sungwoong Kim
Learning Manifold Implicitly via Explicit Heat-Kernel Learning
Yufan Zhou, Changyou Chen, Jinhui Xu