Papers
Wasserstein Dependency Measure for Representation Learning
Sherjil Ozair, Corey Lynch, Yoshua Bengio et al.
Differentially Private Bayesian Linear Regression
Garrett Bernstein, Daniel R. Sheldon
Normalization Helps Training of Quantized LSTM
Lu Hou, Jinhua Zhu, James Kwok et al.
MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization
Shangyu Chen, Wenya Wang, Sinno Jialin Pan
Episodic Memory in Lifelong Language Learning
Cyprien de Masson d'Autume, Sebastian Ruder, Lingpeng Kong et al.
Verified Uncertainty Calibration
Ananya Kumar, Percy Liang, Tengyu Ma
Multi-relational Poincaré Graph Embeddings
Ivana Balazevic, Carl Allen, Timothy Hospedales
Multiclass Learning from Contradictions
Sauptik Dhar, Vladimir Cherkassky, Mohak Shah
DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters
W. O. K. Asiri Suranga Wijesinghe, Qing Wang
Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters
Alberto Maria Metelli, Amarildo Likmeta, Marcello Restelli
The continuous Bernoulli: fixing a pervasive error in variational autoencoders
Gabriel Loaiza-Ganem, John P. Cunningham
MAVEN: Multi-Agent Variational Exploration
Anuj Mahajan, Tabish Rashid, Mikayel Samvelyan et al.
Constrained deep neural network architecture search for IoT devices accounting for hardware calibration
Florian Scheidegger, Luca Benini, Costas Bekas et al.
Certifying Geometric Robustness of Neural Networks
Mislav Balunovic, Maximilian Baader, Gagandeep Singh et al.
Variational Bayes under Model Misspecification
Yixin Wang, David Blei
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks
Ruben Villegas, Arkanath Pathak, Harini Kannan et al.
On Adversarial Mixup Resynthesis
Christopher Beckham, Sina Honari, Vikas Verma et al.
Compression with Flows via Local Bits-Back Coding
Jonathan Ho, Evan Lohn, Pieter Abbeel
Adaptive Influence Maximization with Myopic Feedback
Binghui Peng, Wei Chen
Park: An Open Platform for Learning-Augmented Computer Systems
Hongzi Mao, Parimarjan Negi, Akshay Narayan et al.
Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards
Falcon Dai, Matthew Walter
FastSpeech: Fast, Robust and Controllable Text to Speech
Yi Ren, Yangjun Ruan, Xu Tan et al.
On the Utility of Learning about Humans for Human-AI Coordination
Micah Carroll, Rohin Shah, Mark K Ho et al.
Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer
Wenzheng Chen, Huan Ling, Jun Gao et al.
A Composable Specification Language for Reinforcement Learning Tasks
Kishor Jothimurugan, Rajeev Alur, Osbert Bastani