12 papers with MLG authors appeared at ICML 2019

Published

September 19, 2019

12 papers with MLG authors appeared at ICML 2019 in Long Beach, CA, USA.

David R. Burt, Carl E. Rasmussen and Mark van der Wilk

Rates of Convergence for Sparse Variational Gaussian Process Regression (Best Paper Award)

Paper

Francisco J. R. Ruiz and Michalis K. Titsias

A Contrastive Divergence for Combining Variational Inference and MCMC

Paper

Tameem Adel and Adrian Weller

TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning

Paper

Yingzhen Li, John Bradshaw and Yash Sharma

Are Generative Classifiers More Robust to Adversarial Attacks?

Paper

Alessandro Davide Ialongo, Mark van der Wilk, James Hensman and Carl E. Rasmussen

Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models

Paper

Chao Ma, Sebastian Tschiatschek, Konstantina Palla, José Miguel Hernández- Lobato, Sebastian Nowozin and Cheng Zhang

EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE

Paper

Chao Ma, Yingzhen Li and José Miguel Hernández-Lobato

Variational Implicit Processes

Paper

Ping Liang Tan and Robert Peharz

Hierarchical Decompositional Mixtures of Variational Autoencoders

Paper

Krzystof Choromanski, Mark Rowland, Wenyu Chen and Adrian Weller

Unifying Orthogonal Monte Carlo Methods

Paper

Eric Nalisnick, Akihito Matsukawa, Yee Whye Teh, Dilan Gorur and Balaji Lakshminarayanan

Hybrid Models with Deep and Invertible Features

Paper

Eric Nalisnick, José Miguel Hernández-Lobato and Padhraic Smyth

Dropout as a Structured Shrinkage Prior

Paper

Karl Stelzner, Robert Peharz and Kristian Kersting

Faster Attend-Infer-Repeat with Tractable Probabilistic Models

Paper

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