Structure preserving schemes for a class of Wasserstein gradient flows
Shiheng Zhang,Jie Shen

TL;DR
This paper presents two novel time discretization schemes for Wasserstein gradient flows that preserve key properties like mass, positivity, and energy dissipation, validated through extensive numerical experiments.
Contribution
Introduction of two new discretization schemes for Wasserstein gradient flows that maintain physical properties and improve numerical robustness.
Findings
Schemes preserve mass, positivity, and energy dissipation.
Numerical experiments confirm robustness and accuracy.
Schemes are computationally efficient.
Abstract
We introduce in this paper two time discretization schemes tailored for a range of Wasserstein gradient flows. These schemes are designed to preserve mass, positivity and to be uniquely solvable. In addition, they also ensure energy dissipation in many typical scenarios. Through extensive numerical experiments, we demonstrate the schemes' robustness, accuracy and efficiency.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGeometric Analysis and Curvature Flows · Geometry and complex manifolds · Heme Oxygenase-1 and Carbon Monoxide
