10 papers with MLG authors to appear at NeurIPS 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)
Wenbo Gong, Sebastian Tschiatschek, Richard E. Turner, Sebastian Nowozin, José Miguel Hernández-Lobato, Cheng Zhang
Icebreaker: Efficient Information Acquisition with Active Learning..
Kazuki Osawa, Siddharth Swaroop, Anirudh Jain, Runa Eschenhagen, Richard E. Turner, Rio Yokota, Mohammad Emtiyaz Khan
Practical Deep Learning with Bayesian Principles
Yunfei Teng, Wenbo Gao, Francois Chalus, Anna Choromanska, Donald Goldfarb, Adrian Weller
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models.
Robert Pinsler, Jonathan Gordon, Eric Nalisnick, José Miguel Hernández-Lobato
Bayesian Batch Active Learning as Sparse Subset Approximation
Martin Trapp, Robert Peharz, Hong Ge, Franz Pernkopf, Zoubin Ghahramani
Bayesian Learning of Sum-Product Networks
David Janz, Jiri Hron, Przemysław Mazur, Katja Hofmann, José Miguel Hernández-Lobato, Sebastian Tschiatschek
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato
A Model to Search for Synthesizable Molecules
Paul Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya Tolstikhin
Practical and Consistent Estimation of f-Divergences
Laurence Aitchison
Tensor Monte Carlo: Particle Methods for the GPU era
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