Rapid Model Comparison by Amortizing Across Models

; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-11

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Characterizing and Avoiding Problematic Global Optima of Variational Autoencoders

Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-17

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AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms

Kai Xu, Hong Ge, Will Tebbutt, Mohamed Tarek, Martin Trapp, Zoubin Ghahramani; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-10

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Variational Gaussian Process Models without Matrix Inverses

Mark van der Wilk, ST John, Artem Artemev, James Hensman; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-9

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Information in Infinite Ensembles of Infinitely-Wide Neural Networks

Ravid Shwartz-Ziv, Alexander A Alemi; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-17

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Pseudo-Bayesian Learning via Direct Loss Minimization with Applications to Sparse Gaussian Process Models

Rishit Sheth, Roni Khardon; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-18

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MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming

Yura Perov, Logan Graham, Kostis Gourgoulias, Jonathan Richens, Ciaran Lee, Adam Baker, Saurabh Johri; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-36

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The Gaussian Process Prior VAE for Interpretable Latent Dynamics from Pixels

Michael Pearce; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-12

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Neural Permutation Processes

Ari Pakman, Yueqi Wang, Liam Paninski; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-7

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Sinkhorn Permutation Variational Marginal Inference

Gonzalo Mena, Erdem Varol, Amin Nejatbakhsh, Eviatar Yemini, Liam Paninski; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-9

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Improving Sequential Latent Variable Models with Autoregressive Flows

Joseph Marino, Lei Chen, Jiawei He, Stephan Mandt; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-16

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HM-VAEs: a Deep Generative Model for Real-valued Data with Heterogeneous Marginals

Chao Ma, Sebastian Tschiatschek, Yingzhen Li, Richard Turner, Jose Miguel Hernandez-Lobato, Cheng Zhang; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-8

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Scalable Gradients and Variational Inference for Stochastic Differential Equations

Xuechen Li, Ting-Kam Leonard Wong, Ricky T. Q. Chen, David K. Duvenaud; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-28

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Approximate Inference for Fully Bayesian Gaussian Process Regression

Vidhi Lalchand, Carl Edward Rasmussen; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-12

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Normalizing Constant Estimation with Gaussianized Bridge Sampling

He Jia, Uros Seljak; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-14

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Variational Bayesian Methods for Stochastically Constrained System Design Problems

Prateek Jaiswal, Harsh Honnappa, Vinayak A. Rao; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-12

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Variational Selective Autoencoder

Yu Gong, Hossein Hajimirsadeghi, Jiawei He, Megha Nawhal, Thibaut Durand, Greg Mori; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-17

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Bijectors.jl: Flexible transformations for probability distributions

Tor Erlend Fjelde, Kai Xu, Mohamed Tarek, Sharan Yalburgi, Hong Ge; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-17

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MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy

Badr-Eddine Cherief-Abdellatif, Pierre Alquier; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-21

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GP-ALPS: Automatic Latent Process Selection for Multi-Output Gaussian Process Models

Pavel Berkovich, Eric Perim, Wessel Bruinsma; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-14

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Variational Predictive Information Bottleneck

Alexander A. Alemi; Proceedings of The 2nd Symposium on Advances in Approximate Bayesian Inference, PMLR 118:1-6

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