Bayesian estimation with MCMC

par Dr Maxime Egéa (LPSM)

mardi 26 mai 2026, 14:00 → 15:00 Europe/Paris

GI-UTC

My talk is motivated by the problem of sampling from a posterior distribution in Bayesian estimation, particularly when the posterior concentrates as the number of observations increases. In this context, I will present the Laplace approximation—a classical method for approximating concentrated posterior distributions. We will examine its application in the setting of log-concave measures, and then extend the discussion to more challenging cases involving multimodal distributions. The second part of the talk will be devoted to MCMC algorithm, and how one can use the previously established results to improve its performance.