Papers
AvE: Assistance via Empowerment
Yuqing Du, Stas Tiomkin, Emre Kiciman et al.
POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis
Weichao Mao, Kaiqing Zhang, Qiaomin Xie et al.
Diversity can be Transferred: Output Diversification for White- and Black-box Attacks
Yusuke Tashiro, Yang Song, Stefano Ermon
Hierarchical Quantized Autoencoders
Will Williams, Sam Ringer, Tom Ash et al.
Learning Structured Distributions From Untrusted Batches: Faster and Simpler
Sitan Chen, Jerry Li, Ankur Moitra
Higher-Order Certification For Randomized Smoothing
Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng et al.
Unsupervised Learning of Dense Visual Representations
Pedro O O. Pinheiro, Amjad Almahairi, Ryan Benmalek et al.
Fast Fourier Convolution
Lu Chi, Borui Jiang, Yadong Mu
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning
Pan Li, Yanbang Wang, Hongwei Wang et al.
Continual Deep Learning by Functional Regularisation of Memorable Past
Pingbo Pan, Siddharth Swaroop, Alexander Immer et al.
Low Distortion Block-Resampling with Spatially Stochastic Networks
Sarah Hong, Martin Arjovsky, Darryl Barnhart et al.
Probabilistic Time Series Forecasting with Shape and Temporal Diversity
Vincent LE GUEN, Nicolas THOME
Reward-rational (implicit) choice: A unifying formalism for reward learning
Hong Jun Jeon, Smitha Milli, Anca Dragan
PAC-Bayes Learning Bounds for Sample-Dependent Priors
Pranjal Awasthi, Satyen Kale, Stefani Karp et al.
Influence-Augmented Online Planning for Complex Environments
Jinke He, Miguel Suau de Castro, Frans Oliehoek
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses
Raef Bassily, Vitaly Feldman, Cristóbal Guzmán et al.
Learning Differential Equations that are Easy to Solve
Jacob Kelly, Jesse Bettencourt, Matthew J Johnson et al.
Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms
Tengyu Xu, Zhe Wang, Yingbin Liang
Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations
Sebastian Farquhar, Lewis Smith, Yarin Gal
Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards
Yijie Guo, Jongwook Choi, Marcin Moczulski et al.
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
Vijil Chenthamarakshan, Payel Das, Samuel Hoffman et al.
SuperLoss: A Generic Loss for Robust Curriculum Learning
Thibault Castells, Philippe Weinzaepfel, Jerome Revaud
Heavy-tailed Representations, Text Polarity Classification & Data Augmentation
Hamid Jalalzai, Pierre Colombo, Chloé Clavel et al.
Semantic Visual Navigation by Watching YouTube Videos
Matthew Chang, Arjun Gupta, Saurabh Gupta
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing
Zihang Dai, Guokun Lai, Yiming Yang et al.