Next Session - December 13, with Marylou Gabrié

[All About That Bayes]

Dear All About that Bayes group,

The next session will be December 13, 2022. 14:30 (unusual time), Campus Pierre et Marie Curie (Sorbonne Université), Room 16.26-113 (a zoom link will also be provided few days prior to the session). For the next session we are pleased to welcome Marylou Gabrié (Ecole Polytechnique) who will talk about Opportunities and Challenges in Enhancing Sampling with Learning (abstract below).

You can also add to your calendar the following session : January 10, 2023. 14:00, Campus Pierre et Marie Curie (Sorbonne Université), Room 15.16-309. Talk by Daniele Durante (Bocconi University).

Best regards,

The organising team

Abstract

Deep generative models parametrize very flexible families of distributions able to fit complicated datasets of images or text. Virtually, these models provide independent samples from complex high-distributions at negligible costs. On the other hand, sampling exactly a target distribution, such a Bayesian posterior, is typically challenging: either because of dimensionality, multi-modality, ill-conditioning or a combination of the previous. In this talk, I will review recent works trying to enhance traditional inference and sampling algorithms with learning. I will present in particular flowMC, an adaptive MCMC with Normalizing Flow along with first applications and remaining challenges.

Webpage: https://marylou-gabrie.github.io/