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While MCMC methods have become a main work-horse for Bayesian inference, scaling them to large distributed datasets is still a challenge.
Bayesian inference in econometric models using Monte Carlo integration
John Geweke · 1989
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Truncated importance sampling
Edward L Ionides · 2008
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Analyzing hogwild parallel Gaussian Gibbs sampling
Matthew Johnson, James Saunderson, and Alan Willsky · 2013
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Distributed stochastic gradient MCMC
Sungjin Ahn, Babak Shahbaba, and Max Welling · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2014
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Asymptotically exact, embarrassingly parallel MCMC
Willie Neiswanger, Chong Wang, and Eric P. Xing · 2014
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A complete recipe for stochastic gradient MCMC
Yi-An Ma, Tianqi Chen, and Emily B. Fox · 2015
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Pareto Smoothed Importance Sampling
Aki Vehtari, Andrew Gelman, and Jonah Gabry · 2015
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Parallelizing MCMC with random partition trees
Xiangyu Wang, Fangjian Guo, Katherine A. Heller, and David B. Dunson · 2015
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Patterns of scalable Bayesian inference
Elaine Angelino, Matthew James Johnson, and Ryan P. Adams · 2016
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Bayes and big data: The consensus Monte Carlo algorithm
Steven L. Scott, Alexander W. Blocker, Fernando V. Bonassi, Hugh A. Chipman, Edward I. George, and Robert E. McCulloch · 2016
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Stan: A probabilistic programming language
Bob Carpenter, Andrew Gelman, Matthew Hoffman, Daniel Lee, Ben Goodrich, Michael Betancourt, Marcus Brubaker, Jiqiang Guo, Peter Li, and Allen Riddell · 2017
Density estimation using real NVP
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2017
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Glow: Generative Flow with Invertible 1x1 Convolutions
Diederik P. Kingma and Prafulla Dhariwal · 2018
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Merging MCMC subposteriors through Gaussian-process approximations
Christopher Nemeth and Chris Sherlock · 2018
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Speeding up MCMC by efficient data subsampling
Matias Quiroz, Robert Kohn, Mattias Villani, and Minh-Ngoc Tran · 2018
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Accelerating MCMC algorithms
Christian P. Robert, VÃctor Elvira, Nick Tawn, and Changye Wu · 2018
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Scalable reversible generative models with free-form continuous dynamics
Will Grathwohl, Ricky T. Q. Chen, Jesse Bettencourt, and David Duvenaud · 2019
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