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Surrogate Likelihoods for Variational Annealed Importance Sampling



Martin Jankowiak , Du Phan

* 20 pages 

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Fast Bayesian Variable Selection in Binomial and Negative Binomial Regression



Martin Jankowiak

* 18 pages 

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Scalable Cross Validation Losses for Gaussian Process Models



Martin Jankowiak , Geoff Pleiss

* 19 pages, 14 figures 

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High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces



David Eriksson , Martin Jankowiak


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Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization



Geoff Pleiss , Martin Jankowiak , David Eriksson , Anil Damle , Jacob R. Gardner


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Deep Sigma Point Processes



Martin Jankowiak , Geoff Pleiss , Jacob R. Gardner

* 14 pages, 10 figures 

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Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro



Du Phan , Neeraj Pradhan , Martin Jankowiak

* 10 pages, 2 figures; NeurIPS 2019 Program Transformations for Machine Learning Workshop 

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A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments



Adam Foster , Martin Jankowiak , Matthew O'Meara , Yee Whye Teh , Tom Rainforth


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Functional Tensors for Probabilistic Programming



Fritz Obermeyer , Eli Bingham , Martin Jankowiak , Du Phan , Jonathan P. Chen


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Sparse Gaussian Process Regression Beyond Variational Inference



Martin Jankowiak , Geoff Pleiss , Jacob R. Gardner

* 13 pages, 9 figures 

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