activity
20242026
collaborators

6 papers

math.OC2026

Numerical Approximation for Path-Dependent McKean-Vlasov Control with Non-Asymptotic Error Estimates

Olivier Bokanowski, Jean-Francois Chassagneux, Xinyu Li +1

Path-dependent McKean--Vlasov (MKV) control models large interacting populations with history-dependent dynamics and costs. This paper develops a unified approximation-and-learning…

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…

math.OC2025

Convergence Rates of Time Discretization in Extended Mean Field Control

Christoph Reisinger, Wolfgang Stockinger, Maria Olympia Tsianni +1

Piecewise constant control approximation provides a practical framework for designing numerical schemes of continuous-time control problems. We analyze the accuracy of such approxi…

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…

q-fin.TR2024

Limit Order Book Simulation and Trade Evaluation with -Nearest-Neighbor Resampling

Michael Giegrich, Roel Oomen, Christoph Reisinger

In this paper, we show how -nearest neighbor (-NN) resampling, an off-policy evaluation method proposed in \cite{giegrich2023k}, can be applied to simulate limit order book (…