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Workshop
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Fri 9:30
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Keynote by Max Welling: A Nonparametric Bayesian Approach to Deep Learning (without GPs)
Max Welling
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Poster
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Wed 18:30
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Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap
Edwin Fong · Simon Lyddon · Christopher Holmes
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Oral
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Wed 14:30
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Variational Russian Roulette for Deep Bayesian Nonparametrics
Kai Xu · Akash Srivastava · Charles Sutton
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Oral
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Thu 16:20
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Nonparametric Bayesian Deep Networks with Local Competition
Konstantinos Panousis · Sotirios Chatzis · Sergios Theodoridis
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Poster
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Tue 18:30
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Rates of Convergence for Sparse Variational Gaussian Process Regression
David Burt · Carl E Rasmussen · Mark van der Wilk
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Poster
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Wed 18:30
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Variational Russian Roulette for Deep Bayesian Nonparametrics
Kai Xu · Akash Srivastava · Charles Sutton
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Poster
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Wed 18:30
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Random Function Priors for Correlation Modeling
Aonan Zhang · John Paisley
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Poster
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Wed 18:30
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Graph Convolutional Gaussian Processes
Ian Walker · Ben Glocker
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Poster
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Wed 18:30
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Distribution calibration for regression
Hao Song · Tom Diethe · Meelis Kull · Peter Flach
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Poster
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Wed 18:30
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Incorporating Grouping Information into Bayesian Decision Tree Ensembles
JUNLIANG DU · Antonio Linero
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Poster
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Tue 18:30
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Bayesian Deconditional Kernel Mean Embeddings
Kelvin Hsu · Fabio Ramos
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Poster
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Wed 18:30
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Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior
Fadhel Ayed · Juho Lee · Francois Caron
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