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Poster
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Tue 7:00 |
Variational Bayesian Quantization Yibo Yang · Robert Bamler · Stephan Mandt |
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Poster
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Tue 7:00 |
Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization Richard Zhang · Daniel Golovin |
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Poster
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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 |
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Poster
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Tue 7:00 |
Recurrent Hierarchical Topic-Guided RNN for Language Generation Dandan Guo · Bo Chen · Ruiying Lu · Mingyuan Zhou |
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Poster
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Tue 8:00 |
Meta-learning for Mixed Linear Regression Weihao Kong · Raghav Somani · Zhao Song · Sham Kakade · Sewoong Oh |
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Poster
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Tue 9:00 |
On Semi-parametric Inference for BART Veronika Rockova |
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Poster
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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 |
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Poster
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Tue 9:00 |
Variance Reduction in Stochastic Particle-Optimization Sampling Jianyi Zhang · Yang Zhao · Changyou Chen |
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Poster
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Tue 9:00 |
Being Bayesian about Categorical Probability Taejong Joo · Uijung Chung · Min-Gwan Seo |
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Poster
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Tue 9:00 |
Source Separation with Deep Generative Priors Vivek Jayaram · John Thickstun |
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Poster
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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 |
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Poster
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Tue 11:00 |
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation Steven Kleinegesse · Michael Gutmann |