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Variational inference has become an increasingly attractive fast alternative to Markov chain Monte Carlo methods for approximate Bayesian inference.
Yes, but Did It Work?: Evaluating Variational Inference
Y. Yao, A. Vehtari, D. Simpson, and A. Gelman · 1910
Earlier work this paper cites.
The Bayesian Choice
C. P. Robert · 1994
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Asymptotic Statistics
A. W. van der Vaart · 1998
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Exponential Integrability and Transportation Cost Related to Logarithmic Sobolev Inequalities
S. G. Bobkov and F. Götze · 1999
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Topics in Optimal Transportation
C. Villani · 2003
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Transportation cost-information inequalities and applications to random dynamical systems and diffusions
H. Djellout, A. Guillin, and L. Wu · 2004
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Weighted Csiszár-Kullback-Pinsker inequalities and applications to transportation inequalities
F. Bolley and C. Villani · 2005
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Pattern recognition and machine learning , chapter 10: Approximate Inference
C. M. Bishop · 2006
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Graphical models, exponential families, and variational inference
M. J. Wainwright, M. I. Jordan, et al · 2008
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A characterization of dimension free concentration in terms of transportation inequalities
N. Gozlan · 2009
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On the Assessment of Monte Carlo Error in Simulation-Based Statistical Analyses
E. Koehler, E. Brown, and S. J. P. A. Haneuse · 2009
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Optimal transport: old and new , volume 338 of Grundlehren der mathematischen Wissenschaften
C. Villani · 2009
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Families of Alpha- Beta- and Gamma- Divergences: Flexible and Robust Measures of Similarities
A. Cichocki and S.-I. Amari · 2010
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Curvature, concentration and error estimates for Markov chain Monte Carlo
A. Joulin and Y. Ollivier · 2010
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Quantitative bounds for Markov chain convergence: Wasserstein and total variation distances
N. Madras and D. Sezer · 2010
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Mcmc using Hamiltonian dynamics
R. M. Neal · 2011
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The Bernstein-Von-Mises theorem under misspecification
B. J. K. Kleijn and A. W. van der Vaart · 2012
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Computing the Kullback-Leibler Divergence between two Weibull Distributions
C. Bauckhage · 2013
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Concentration Inequalities: A nonasymptotic theory of independence
S. Boucheron, G. Lugosi, and P. Massart · 2013
Earlier work this paper cites.
Bayesian Data Analysis
A. Gelman, J. Carlin, H. Stern, D. B. Dunson, A. Vehtari, and D. B. Rubin · 2013
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Fast computation of Wasserstein barycenters
M. Cuturi and A. Doucet · 2014
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The no-u-turn sampler: adaptively setting path lengths in hamiltonian monte carlo
M. D. Hoffman and A. Gelman · 2014
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Auto-Encoding Variational Bayes
D. P. Kingma and M. Welling · 2014
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Black Box Variational Inference
R. Ranganath, S. Gerrish, and D. M. Blei · 2014
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Measuring Sample Quality with Stein’s Method
J. Gorham and L. Mackey · 2015
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Automatic Variational Inference in Stan
Variational Inference via χ \chi Upper Bound Minimization
A. B. Dieng, D. Tran, R. Ranganath, J. Paisley, and D. M. Blei · 2017
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Measuring Sample Quality with Kernels
J. Gorham and L. Mackey · 2017
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Variational boosting: iteratively refining posterior approximations
A. Miller, N. Foti, and R. Adams · 2017
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The sample size required in importance sampling
S. Chatterjee and P. Diaconis · 2018
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Consistency of variational Bayes inference for estimation and model selection in mixtures
B.-E. Chérief-Abdellatif and P. Alquier · 2018
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Stochastic Wasserstein barycenters
S. Claici, E. Chien, and J. Solomon · 2018
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A. Kucukelbir, R. Ranganath, A. Gelman, and D. M. Blei · 2015
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On the properties of variational approximations of Gibbs posteriors
P. Alquier, J. Ridgway, and N. Chopin · 2016
Cited alongside, same era.
Boosting variational inference
F. Guo, X. Wang, K. Fan, T. Broderick, and D. Dunson · 2016
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Black-Box Alpha Divergence Minimization
J. M. Hernández-Lobato, Y. Li, M. Rowland, T. D. Bui, D. Hernández-Lobato, and R. E. Turner · 2016
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Rényi Divergence Variational Inference
Y. Li and R. E. Turner · 2016
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Probabilistic programming in Python using PyMC3
J. Salvatier, T. V. Wiecki, and C. Fonnesbeck · 2016
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Global Non-convex Optimization with Discretized Diffusions
M. A. Erdogdu, L. Mackey, and O. Shamir · 2018
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On Statistical Optimality of Variational Bayes
D. Pati, A. Bhattacharya, and Y. Yang · 2018
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Perturbation theory for Markov chains via Wasserstein distance
D. Rudolf and N. Schweizer · 2018
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Scalable Bayes via barycenter in Wasserstein space
S. Srivastava, C. Li, and D. B. Dunson · 2018
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Frequentist Consistency of Variational Bayes
Y. Wang and D. M. Blei · 2018
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Universal boosting variational inference
T. Campbell and X. Li · 2019
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High-dimensional Bayesian inference via the unadjusted Langevin algorithm
A. Durmus and E. Moulines · 2019
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Analysis of Langevin Monte Carlo via convex optimization
A. Durmus, S. Majewski, and B. Miasojedow · 2019
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Quantitative contraction rates for Markov chains on general state spaces
A. Eberle and M. B. Majka · 2019
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Measuring sample quality with diffusions
J. Gorham, A. B. Duncan, S. J. Vollmer, and L. Mackey · 2019
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Pareto Smoothed Importance Sampling
A. Vehtari, D. Simpson, A. Gelman, Y. Yao, and J. Gabry · 2019
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Variational Bayes under Model Misspecification
Y. Wang and D. M. Blei · 2019
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