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Poster
Wed 12:45 Scalable Constrained Bayesian Optimization
David Eriksson · Matthias Poloczek
Poster
Tue 18:30 Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?
Chaoqi Wang · Shengyang Sun · Roger Grosse
Poster
Wed 6:00 Hyperparameter Transfer Learning with Adaptive Complexity
Samuel Horv├íth · Aaron Klein · Peter Richtarik · Cedric Archambeau
Poster
Thu 7:30 Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon
Jeremiah Liu
Poster
Tue 14:00 A Hybrid Approximation to the Marginal Likelihood
Eric Chuu · Debdeep Pati · Anirban Bhattacharya
Poster
Tue 18:30 PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming
Alexander Lew · Monica Agrawal · David Sontag · Vikash Mansinghka
Poster
Thu 7:30 Bayesian Inference with Certifiable Adversarial Robustness
Matthew Wicker · Luca Laurenti · Andrea Patane · Zhuotong Chen · Zheng Zhang · Marta Kwiatkowska
Poster
Tue 14:00 Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective
Yibo Zhang · Rajiv Khanna · Anastasios Kyrillidis · Sanmi Koyejo
Poster
Wed 6:00 Predictive Complexity Priors
Eric Nalisnick · Jonathan Gordon · Jose Miguel Hernandez-Lobato
Poster
Thu 7:30 A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models
Jiaxin Zhang · Sirui Bi · Guannan Zhang
Poster
Tue 14:00 Accelerating Metropolis-Hastings with Lightweight Inference Compilation
Feynman Liang · Nimar Arora · Nazanin Tehrani · Yucen Li · Michael Tingley · Erik Meijer
Poster
Wed 6:00 Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations
Simone Rossi · Markus Heinonen · Edwin Bonilla · Zheyang Shen · Maurizio Filippone