On optimal transport of matrix-valued measures
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Abstract (arXiv)
We suggest a new way of defining optimal transport of positive-semidefinite matrix-valued measures. It is inspired by a recent rendering of the incompressible Euler equations and related conservative systems as concave maximization problems. The main object of our attention is the Kantorovich-Bures metric space, which is a matricial analogue of the Wasserstein and Hellinger-Kantorovich metric spaces. We establish some topological, metric and geometric properties of this space, which includes the existence of the optimal transportation path.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Aug 2018.
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Citing papers per year: 2022: 3; 2023: 0; 2024: 1.
4 papers.
- 2022Birth-death dynamics for sampling: Global convergence, approximations and their asymptoticscited by 30
- 2022Two-Scale Gradient Descent Ascent Dynamics Finds Mixed Nash Equilibria of Continuous Games: A Mean-Field Perspectivecited by 13
- 2024Fisher-Rao Gradient Flow: Geodesic Convexity and Functional Inequalitiescited by 13
- 2022A deep learning framework for geodesics under spherical Wasserstein-Fisher-Rao metric and its application for weighted sample generationcited by 0
- 2024Fisher-Rao Gradient Flow: Geodesic Convexity and Functional Inequalities22 Jul 2024
- 2022Two-Scale Gradient Descent Ascent Dynamics Finds Mixed Nash Equilibria of Continuous Games: A Mean-Field Perspective17 Dec 2022
- 2022Birth-death dynamics for sampling: Global convergence, approximations and their asymptotics1 Nov 2022
- 2022A deep learning framework for geodesics under spherical Wasserstein-Fisher-Rao metric and its application for weighted sample generation25 Aug 2022