AABI

Keyphrases

Publications

volume 118, 2020

Symposium on Advances in Approximate Bayesian Inference, AABI 2019, Vancouver, BC, Canada, December 8, 2019. AABI 118 (2020)

2019

Vidhi Lalchand, Carl Edward Rasmussen
Approximate Inference for Fully Bayesian Gaussian Process Regression. AABI (2019)
Lily H. Zhang, Michael C. Hughes
Rapid Model Comparison by Amortizing Across Models. AABI (2019)
He Jia, Uros Seljak
Normalizing Constant Estimation with Gaussianized Bridge Sampling. AABI (2019)
Prateek Jaiswal, Harsha Honnappa, Vinayak A. Rao
Variational Bayesian Methods for Stochastically Constrained System Design Problems. AABI (2019)
Michael Pearce
The Gaussian Process Prior VAE for Interpretable Latent Dynamics from Pixels. AABI (2019)
Mark van der Wilk, S. T. John, Artem Artemev, James Hensman
Variational Gaussian Process Models without Matrix Inverses. AABI (2019)
Rishit Sheth, Roni Khardon
Pseudo-Bayesian Learning via Direct Loss Minimization with Applications to Sparse Gaussian Process Models. AABI (2019)
Ari Pakman, Yueqi Wang, Liam Paninski
Neural Permutation Processes. AABI (2019)
Chao Ma, Sebastian Tschiatschek, Yingzhen Li, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang
HM-VAEs: a Deep Generative Model for Real-valued Data with Heterogeneous Marginals. AABI (2019)
Tor Erlend Fjelde, Kai Xu, Mohamed Tarek, Sharan Yalburgi, Hong Ge
Bijectors.jl: Flexible transformations for probability distributions. AABI (2019)
Gonzalo E. Mena, Erdem Varol, Amin Nejatbakhsh, Eviatar Yemini, Liam Paninski
Sinkhorn Permutation Variational Marginal Inference. AABI (2019)
Yura Perov, Logan Graham, Kostis Gourgoulias, Jonathan G. Richens, Ciarán M. Lee, Adam Baker, Saurabh Johri
MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming. AABI (2019)
Kai Xu, Hong Ge, Will Tebbutt, Mohamed Tarek, Martin Trapp, Zoubin Ghahramani
AdvancedHMC.jl: A robust, modular and e cient implementation of advanced HMC algorithms. AABI (2019)
Alexander A. Alemi
Variational Predictive Information Bottleneck. AABI (2019)
Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
Characterizing and Avoiding Problematic Global Optima of Variational Autoencoders. AABI (2019)
Yu Gong, Hossein Hajimirsadeghi, Jiawei He, Megha Nawhal, Thibaut Durand, Greg Mori
Variational Selective Autoencoder. AABI (2019)
Joseph Marino, Lei Chen, Jiawei He, Stephan Mandt
Improving Sequential Latent Variable Models with Autoregressive Flows. AABI (2019)
Pavel Berkovich, Eric Perim, Wessel Bruinsma
GP-ALPS: Automatic Latent Process Selection for Multi-Output Gaussian Process Models. AABI (2019)
Ravid Shwartz-Ziv, Alexander A. Alemi
Information in Infinite Ensembles of Infinitely-Wide Neural Networks. AABI (2019)
Xuechen Li, Ting-Kam Leonard Wong, Ricky T. Q. Chen, David Kristjanson Duvenaud
Scalable Gradients and Variational Inference for Stochastic Differential Equations. AABI (2019)
Badr-Eddine Chérief-Abdellatif, Pierre Alquier
MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy. AABI (2019)

volume 96, 2019

Symposium on Advances in Approximate Bayesian Inference, AABI 2018, Montréal, QC, Canada, December 2, 2018. AABI 96 (2019)

2018