Differential Inclusions in Wasserstein Spaces: The Cauchy-Lipschitz Framework
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Abstract (arXiv)
In this article, we propose a general framework for the study of differential inclusions in the Wasserstein space of probability measures. Based on earlier geometric insights on the structure of continuity equations, we define solutions of differential inclusions as absolutely continuous curves whose driving velocity fields are measurable selections of multifunction taking their values in the space of vector fields. In this general setting, we prove three of the founding results of the theory of differential inclusions: Filippov's theorem, the Relaxation theorem, and the compactness of the solution sets. These contributions -- which are based on novel estimates on solutions of continuity equations -- are then applied to derive a new existence result for fully non-linear mean-field optimal control problems with closed-loop controls.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Jul 2020.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 0; 2025: 0; 2026: 1.
4 papers.
- 2021Kernel Stein Discrepancy Descentcited by 57
- 2023Variational formulations of ODE-Net as a mean-field optimal control problem and existence resultscited by 3
- 2026Sobolev Regularized MMD Gradient Flowcited by 3
- 2022Path differentiability of ODE flowscited by 1
- 2026Sobolev Regularized MMD Gradient Flow12 May 2026
- 2023Variational formulations of ODE-Net as a mean-field optimal control problem and existence results9 Mar 2023
- 2022Path differentiability of ODE flows11 Jan 2022
- 2021Kernel Stein Discrepancy Descent20 May 2021