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stat.CO2025
Analysis of kinetic Langevin Monte Carlo under the stochastic exponential Euler discretization from underdamped all the way to overdamped
Kyurae Kim, Samuel Gruffaz, Ji Won Park +1
Simulating the kinetic Langevin dynamics is a popular approach for sampling from distributions, where only their unnormalized densities are available. Various discretizations of th…
stat.CO2024
Stochastic Approximation with Biased MCMC for Expectation Maximization
Samuel Gruffaz, Kyurae Kim, Alain Oliviero Durmus +1
The expectation maximization (EM) algorithm is a widespread method for empirical Bayesian inference, but its expectation step (E-step) is often intractable. Employing a stochastic…
stat.CO2023
Geodesic slice sampling on Riemannian manifolds
Alain Durmus, Samuel Gruffaz, Mareike Hasenpflug +1
We propose a theoretically justified and practically applicable slice sampling based Markov chain Monte Carlo (MCMC) method for approximate sampling from probability measures on Ri…