10 papers with MLG authors to appear at NeurIPS 2019

Published

September 19, 2019

10 papers with MLG authors will appear at NeurIPS 2019 in Vancouver, Canada.

James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E. Turner

Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes (spotlight)

Paper

Wenbo Gong, Sebastian Tschiatschek, Richard E. Turner, Sebastian Nowozin, José Miguel Hernández-Lobato, Cheng Zhang

Icebreaker: Efficient Information Acquisition with Active Learning..

Paper

Kazuki Osawa, Siddharth Swaroop, Anirudh Jain, Runa Eschenhagen, Richard E. Turner, Rio Yokota, Mohammad Emtiyaz Khan

Practical Deep Learning with Bayesian Principles

Paper

Yunfei Teng, Wenbo Gao, Francois Chalus, Anna Choromanska, Donald Goldfarb, Adrian Weller

Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models.

Paper

Robert Pinsler, Jonathan Gordon, Eric Nalisnick, José Miguel Hernández-Lobato

Bayesian Batch Active Learning as Sparse Subset Approximation

Paper

Martin Trapp, Robert Peharz, Hong Ge, Franz Pernkopf, Zoubin Ghahramani

Bayesian Learning of Sum-Product Networks

Paper

David Janz, Jiri Hron, Przemysław Mazur, Katja Hofmann, José Miguel Hernández-Lobato, Sebastian Tschiatschek

Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning

Paper

John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato

A Model to Search for Synthesizable Molecules

Paper

Paul Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya Tolstikhin

Practical and Consistent Estimation of f-Divergences

Paper

Laurence Aitchison

Tensor Monte Carlo: Particle Methods for the GPU era

Paper

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