3 papers
stat.CO2026
A Non-asymptotic Analysis for Learning and Applying a Preconditioner in MCMC
Max Hird, Florian Maire, Jeffrey Negrea
Preconditioning is a common method applied to modify Markov chain Monte Carlo algorithms with the goal of making them more efficient. In practice it is often extremely effective, e…
stat.CO2025
Adaptive Pseudo-Marginal Algorithm
Sarra Abaoubida, Mylène Bédard, Florian Maire
The Pseudo-Marginal (PM) algorithm is a popular Markov chain Monte Carlo (MCMC) method used to sample from a target distribution when its density is inaccessible, but can be estima…
stat.CO2024
The occlusion process: improving sampler performance with parallel computation and variational approximation
Max Hird, Florian Maire
Autocorrelations in MCMC chains increase the variance of the estimators they produce. We propose the occlusion process to mitigate this problem. It is a process that sits upon an e…