7 papers
Deep-MKV-TS: Path-Dependent McKean--Vlasov Control for Financial Time Series Generation
Samer El Boustany, Théo Basseras, Samy Mekkaoui +3
We introduce Deep-MKV-TS, a path-dependent McKean-Vlasov framework for financial scenario generation. The stochastic dynamics are chosen by matching selected path and volatility fe…
Policy Gradient Learning for Distributionally Robust Markov Decision Processes under Wasserstein Ambiguity
Yadh Hafsi, Samy Mekkaoui, Huyên Pham +1
We study finite-horizon Markov decision processes under distributional uncertainty in the transition kernels and develop a policy-gradient framework for Wasserstein distributionall…
Learning Generative Dynamics with Soft Law Constraints: A McKean-Vlasov FBSDE Approach
Samer El Boustany, Samy Mekkaoui, Yadh Hafsi +2
We propose a generative framework for learning stochastic dynamics from endpoint and intermediate distributional observations. The method formulates generation as a McKean-Vlasov c…
Learning operators on labelled conditional distributions with applications to mean field control of non exchangeable systems
Samy Mekkaoui, Huyên Pham, Xavier Warin
We study the approximation of operators acting on probability measures on a product space with prescribed marginal. Let be a label space endowed with a reference measure ,…
Non-Exchangeable Mean Field Markov Decision Processes with common noise : from Bellman equation to quantitative propagation of chaos
Samy Mekkaoui, Huyên Pham
We study infinite-horizon Markov Decision Processes (MDPs) with a continuum of heterogeneous agents interacting through a common noise, without assuming exchangeability. We introdu…
Optimal Control of Heterogeneous Mean-Field Stochastic Differential Equations with Common Noise and Applications
Filippo de Feo, Samy Mekkaoui
We initiate the study of optimal control problems of heterogeneous mean-field stochastic differential equations with common noise. We formulate the problem within a linear-quadrati…