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The 2021 schedule is still incomplete
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Oral
Tue Jul 20 06:00 AM -- 06:20 AM (PDT)
What Are Bayesian Neural Network Posteriors Really Like?
In Deep Learning (Bayesian)
Pavel Izmailov · Sharad Vikram · Matthew Hoffman · Andrew Wilson
[ Paper ]
Spotlight
Tue Jul 20 06:20 AM -- 06:25 AM (PDT)
Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning
In Deep Learning (Bayesian)
Alexander Immer · Matthias Bauer · Vincent Fortuin · Gunnar Ratsch · Khan Emtiyaz
[ Paper ]
Spotlight
Tue Jul 20 06:25 AM -- 06:30 AM (PDT) @ Virtual
Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation
In Deep Learning (Bayesian)
Aurick Zhou · Sergey Levine
[ Slides] 
[ Paper ]
Spotlight
Tue Jul 20 06:30 AM -- 06:35 AM (PDT)
Deep kernel processes
In Deep Learning (Bayesian)
Laurence Aitchison · Adam Yang · Sebastian Ober
[ Paper ]
Spotlight
Tue Jul 20 06:35 AM -- 06:40 AM (PDT)
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes
In Deep Learning (Bayesian)
Sebastian Ober · Laurence Aitchison
[ Paper ]
Spotlight
Tue Jul 20 06:40 AM -- 06:45 AM (PDT)
Bayesian Deep Learning via Subnetwork Inference
In Deep Learning (Bayesian)
Erik Daxberger · Eric Nalisnick · James Allingham · Javier Antorán · Jose Miguel Hernandez-Lobato
[ Paper ]
Spotlight
Tue Jul 20 06:45 AM -- 06:50 AM (PDT)
Generative Particle Variational Inference via Estimation of Functional Gradients
In Deep Learning (Bayesian)
Neale Ratzlaff · Jerry Bai · Fuxin Li · Wei Xu
[ Paper ]
Q&A
Tue Jul 20 06:50 AM -- 06:55 AM (PDT)
Q&A
In Deep Learning (Bayesian)