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Marylou GABRIE (Ecole polytechnique) “Opportunities and Challenges in Enhancing Sampling with Learning”
Statistical Seminar: Every Monday at 2:00 pm.
Time: 2:00 pm – 3:15 pm
Date: 16th of January 2023
Place: Room 3001
Marylou GABRIE (Ecole polytechnique) “Opportunities and Challenges in Enhancing Sampling with Learning”
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.
Organizers:
Cristina BUTUCEA (CREST), Alexandre TSYBAKOV (CREST), Karim LOUNICI (CMAP) , Jaouad MOURTADA (CREST)
Sponsors:
CREST-CMAP