Practical bounds on the error of Bayesian posterior approximations: A
nonasymptotic approach

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Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach

25 September 2018

Jonathan H. Huggins

Trevor Campbell

Mikolaj Kasprzak

Tamara Broderick

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Papers citing "Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach"

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How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences Mikolaj Kasprzak Ryan Giordano Tamara Broderick 66 4 0 29 Sep 2022
User-friendly introduction to PAC-Bayes bounds Pierre Alquier FedML 193 206 0 21 Oct 2021
Statistical Guarantees and Algorithmic Convergence Issues of Variational Boosting B. Guha A. Bhattacharya D. Pati 78 2 0 19 Oct 2020
Efficient hyperparameter optimization by way of PAC-Bayes bound minimization John J. Cherian Andrew G. Taube R. McGibbon Panagiotis Angelikopoulos Guy Blanc M. Snarski D. D. Richman J. L. Klepeis D. Shaw 33 6 0 14 Aug 2020
Convergence Rates of Variational Inference in Sparse Deep Learning Badr-Eddine Chérief-Abdellatif BDL 122 39 0 09 Aug 2019
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations Brian L. Trippe Jonathan H. Huggins Raj Agrawal Tamara Broderick BDL 73 9 0 17 May 2019