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math.OC2026

Neural feedback approximation for stochastic control with degenerate diffusions: error estimates and numerical analysis

Olivier Bokanowski, Jean-François Chassagneux, Marco Scaratti +1

We study finite-horizon stochastic optimal control problems and approximate the resulting time-discrete formulation by a direct policy-learning problem over neural-network feedback…

math.OC2026

Saddle Networks: Structure-Preserving Architectures for Convex-Concave Functions

Xavier Warin

Saddle-point models arise throughout optimization, optimal transport, robust learning, and control. In many applications, the relevant function f(x,y) is convex in x and concave in…

math.OC2026

Growth model with externalities for energetic transition via MFG with common external variable

Pierre Lavigne, Quentin Petit, Xavier Warin

This article introduces a novel mean-field game model for multi-sector economic growth in which a dynamically evolving externality, influenced by the collective actions of agents,…

math.OC2026

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 ,…

math.OC2024

Representation results and error estimates for differential games with applications using neural networks

Olivier Bokanowski, Xavier Warin

We study deterministic optimal control problems for differential games with finite horizon. We propose new approximations of the strategies in feedback form, and show error estimat…