December 8, 2019
Pan Pacific Hotel
300 - 999 Canada Pl
Vancouver, BC V6C 3B5, Canada
Crystal Pavilion
| 7:30 - 8:20 | Registration + Coffee |
| 8:20 - 8:30 | Introduction |
| 8:30 - 9:00 | Invited |
Michalis Titsias: Gradient-based Adaptive Markov Chain Monte Carlo
Slides |
| 9:00 - 9:15 | Contributed |
Jakub Swiatkowski: The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks
Slides |
| 9:15 - 9:45 | Invited |
Michael Gutmann: Robust Optimisation Monte Carlo
Slides |
| 9:45 - 10:05 | Spotlights |
Marko Jarvenpaa, William Wilkinson, Alexander Alemi, Joseph Marino, Jimmy Ba, Anthony Tompkins
Slides |
| 10:05 - 11:00 | Coffee Break and Poster Session (Paper IDs 1-32) |
| 11:00 - 11:30 | Invited | Sergey Levine: Reinforcement Learning, Optimal Control, and Probabilistic Inference |
| 11:30 - 11:45 | Contributed |
Iuliia Molchanova: Structured Semi-Implicit Variational Inference
Slides |
| 11:45 - 12:15 | Invited | Rianne van den Berg: Normalizing Flows for Discrete Data Slides |
| 12:15 - 13:45 | Lunch Break (on your own) |
| 13:45 - 14:00 | Contributed |
Matthew Hoffman: Langevin Dynamics as Nonparametric Variational Inference
Slides |
| 14:00 - 14:30 | Invited | Qiang Liu: Steepest Descent Neural Architecture Optimization: Going Beyond Black-Box |
| 14:30 - 14:50 | Spotlights |
Jiaxin Shi, Anna Kuzina, Mark van der Wilk, Xuechen Li, Yaniv Yacoby, Ravid Shwartz-Ziv
Slides |
| 14:50 - 15:45 | Coffee Break and Poster Session (Paper IDs 33-68) |
| 15:45 - 16:15 | Invited | Emily Fox: Stochastic Gradient MCMC for Sequential Data Sources |
| 16:15 - 16:30 | Contributed |
Roman Novak: Neural Tangents: Fast and Easy Infinite Neural Networks in Python
Slides |
| 16:30 - 17:00 | Invited | Christian Robert: ABC Gibbs for Hierarchical Models |
| 17:00 - 18:00 | Panel
James Hensman, Matthew Hoffman, Radford Neal, Christian Robert, Sinead Williamson Moderator: Frank Wood Video |