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approximate Bayesian inference [survey]

May 3, 2021

In connection with the special issue of Entropy I mentioned a while ago, Pierre Alquier (formerly of CREST) has written an introduction to the topic of approximate Bayesian inference that is worth advertising (and freely-available as well). Its reference list is particularly relevant. (The deadline for submissions is 21 June,)

online approximate Bayesian learning

September 25, 2020

My friends and coauthors Matthieu Gerber and Randal Douc have just arXived a massive paper on online approximate Bayesian learning, namely the handling of the posterior distribution on the parameters of a state-space model, which remains a challenge to this day… Starting from the iterated batch importance sampling (IBIS) algorithm of Nicolas (Chopin, 2002) which […]

Approximate Bayesian analysis of (un)conditional copulas [webinar]

September 17, 2020

The Algorithms & Computationally Intensive Inference seminar (access by request) will virtually resume this week in Warwick U on Friday, 18 Sept., at noon (UK time, ie +1GMT) with a talk by (my coauthor and former PhD student) Clara Grazian (now at UNSW), talking about approximate Bayes for copulas: Many proposals are now available to […]

computational advances in approximate Bayesian methods [at JSM]

August 5, 2020

Another broadcast for an ABC (or rather ABM) session at JSM, organised and chaired by Robert Kohn, taking place tomorrow at 10am, ET, i.e., 2pm GMT, with variational and ABC talks: 454 * Thu, 8/6/2020, 10:00 AM – 11:50 AM Virtual Computational Advances in Approximate Bayesian Methods — Topic Contributed Papers Section on Bayesian Statistical […]

distortion estimates for approximate Bayesian inference

July 7, 2020

A few days ago, Hanwen Xing, Geoff Nichols and Jeong Eun Lee arXived a paper with the following title, to be presented at uai2020. Towards assessing the fit of the approximation for the actual posterior, given the available data. This covers of course ABC methods (which seems to be the primary focus of the paper) […]