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Poster
Tue 7:00 Variational Bayesian Quantization
Yibo Yang · Robert Bamler · Stephan Mandt
Poster
Tue 7:00 Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization
Richard Zhang · Daniel Golovin
Poster
Tue 7:00 Amortized Population Gibbs Samplers with Neural Sufficient Statistics
Hao Wu · Heiko Zimmermann · Eli Sennesh · Tuan Anh Le · Jan-Willem van de Meent
Poster
Tue 7:00 Recurrent Hierarchical Topic-Guided RNN for Language Generation
Dandan Guo · Bo Chen · Ruiying Lu · Mingyuan Zhou
Poster
Tue 8:00 Meta-learning for Mixed Linear Regression
Weihao Kong · Raghav Somani · Zhao Song · Sham Kakade · Sewoong Oh
Poster
Tue 9:00 On Semi-parametric Inference for BART
Veronika Rockova
Poster
Tue 9:00 How Good is the Bayes Posterior in Deep Neural Networks Really?
Florian Wenzel · Kevin Roth · Bastiaan Veeling · Jakub Swiatkowski · Linh Tran · Stephan Mandt · Jasper Snoek · Tim Salimans · Rodolphe Jenatton · Sebastian Nowozin
Poster
Tue 9:00 Variance Reduction in Stochastic Particle-Optimization Sampling
Jianyi Zhang · Yang Zhao · Changyou Chen
Poster
Tue 9:00 Being Bayesian about Categorical Probability
Taejong Joo · Uijung Chung · Min-Gwan Seo
Poster
Tue 9:00 Source Separation with Deep Generative Priors
Vivek Jayaram · John Thickstun
Poster
Tue 10:00 Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems
Hans Kersting · Nicholas Krämer · Martin Schiegg · Christian Daniel · Michael Schober · Philipp Hennig
Poster
Tue 11:00 Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation
Steven Kleinegesse · Michael Gutmann