Automatic Variational Inference in Stan

10 June 2015

Papers citing "Automatic Variational Inference in Stan"

21 / 21 papers shown

Title
An Embedded Diachronic Sense Change Model with a Case Study from Ancient Greek Schyan Zafar Geoff K. Nicholls 24 1 0 01 Nov 2023
Manifold Gaussian Variational Bayes on the Precision Matrix M. Magris M. Shabani Alexandros Iosifidis 34 2 0 26 Oct 2022
Modeling and mitigation of occupational safety risks in dynamic industrial environments Ashutosh Tewari António R. C. Paiva 14 1 0 02 May 2022
Simplifying deflation for non-convex optimization with applications in Bayesian inference and topology optimization Mohamed Tarek Yijiang Huang 11 2 0 28 Jan 2022
Epidemia: An R Package for Semi-Mechanistic Bayesian Modelling of Infectious Diseases using Point Processes Shuhang Tan Axel Gandy Swapnil Mishra Samir Bhatt Seth Flaxman H. Juliette T. Unwin J. Ish-Horowicz 6 9 0 24 Oct 2021
$Bayesian model selection in the $\mathcal{M}$-open setting -- Approximate posterior inference and probability-proportional-to-size subsampling for efficient large-scale leave-one-out cross-validation$ Bayesian model selection in the $\mathcal{M}$ -open setting -- Approximate posterior inference and probability-proportional-to-size subsampling for efficient large-scale leave-one-out cross-validation Riko Kelter 11 0 0 27 May 2020
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 16 135 0 16 Jul 2019
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models Yuanshuo Zhou Bradley Gram-Hansen Tobias Kohn Tom Rainforth Hongseok Yang Frank D. Wood 20 24 0 06 Mar 2019
Bayesian Incremental Learning for Deep Neural Networks Max Kochurov T. Garipov D. Podoprikhin Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov OOD CLL BDL 10 22 0 20 Feb 2018
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference Jonathan H. Huggins Ryan P. Adams Tamara Broderick 16 32 0 26 Sep 2017
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks L. Mescheder Sebastian Nowozin Andreas Geiger GAN BDL 29 525 0 17 Jan 2017
Boosting Variational Inference Fangjian Guo Xiangyu Wang Kai Fan Tamara Broderick David B. Dunson BDL 21 75 0 17 Nov 2016
Deep Amortized Inference for Probabilistic Programs Daniel E. Ritchie Paul Horsfall Noah D. Goodman TPM 13 81 0 18 Oct 2016
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms C. A. Naesseth Francisco J. R. Ruiz Scott W. Linderman David M. Blei BDL 18 108 0 18 Oct 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm Qiang Liu Dilin Wang BDL 19 1,067 0 16 Aug 2016
Swift: Compiled Inference for Probabilistic Programming Languages Yi Wu Lei Li Stuart J. Russell Rastislav Bodík 15 29 0 30 Jun 2016
Automatic Variational ABC Alexander Moreno T. Adel Edward Meeds James M. Rehg Max Welling 15 12 0 28 Jun 2016
Overdispersed Black-Box Variational Inference Francisco J. R. Ruiz Michalis K. Titsias David M. Blei 14 47 0 03 Mar 2016
Automatic Differentiation Variational Inference A. Kucukelbir Dustin Tran Rajesh Ranganath Andrew Gelman David M. Blei 24 708 0 02 Mar 2016
Fitting Bayesian item response models in Stata and Stan Robert Grant Daniel Furr Bob Carpenter Andrew Gelman 59 17 0 13 Jan 2016
Black-box $α$ -divergence Minimization José Miguel Hernández-Lobato Yingzhen Li Mark Rowland Daniel Hernández-Lobato T. Bui Richard E. Turner 21 137 0 10 Nov 2015