3 papers
math.OC2026
Model-free policy gradient for discrete-time mean-field control
Matthieu Meunier, Huyên Pham, Christoph Reisinger
We study model-free policy learning for discrete-time mean-field control (MFC) problems with finite state space and compact action space. In contrast to the extensive literature on…
cs.LG2026
Weighted Conditional Flow Matching
Sergio Calvo-Ordonez, Matthieu Meunier, Alvaro Cartea +3
Conditional flow matching (CFM) has emerged as a powerful framework for training continuous normalizing flows due to its computational efficiency and effectiveness. However, standa…
cs.LG2025
Efficient Learning for Entropy-Regularized Markov Decision Processes via Multilevel Monte Carlo
Matthieu Meunier, Christoph Reisinger, Yufei Zhang
Designing efficient learning algorithms with complexity guarantees for Markov decision processes (MDPs) with large or continuous state and action spaces remains a fundamental chall…