Approximate Bayesian Inference

This book is a reprint of the Special Issue Approximate Bayesian Inference that was published in the open access journal Entropy (ISSN 1099-4300) (available at: https://www.mdpi.com/journal/entropy/special_issues/approx_Bayes_inference). The objective of this Special Issue is to provide the latest advances in approximate Monte Carlo methods and in approximations of the posterior: design of efficient algorithms, study of the statistical properties of these algorithms, and challenging applications. Lien vers l'article

ALQUIER, P. [Ed] (2022). Approximate Bayesian Inference. MDPI.

Mots clés : #Bayesian-statistics, #machine-learning, #variational-approximations, #PAC, #Bayes, #expectation, #propagation, #Markov-chain-Monte-Carlo, #Langevin-Monte-Carlo, #sequential-Monte-Carlo, #Laplace-approximations, #approximate-Bayesian-computation, #Gibbs-posterior