A Jump-Modified Wasserstein Gradient Flow for Maximum Mean Discrepancy with Energy Kernels

Ansh Desai, Jason Liu, Srujan Roplekar, Matthew Rosenzweig · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.29007 · cited by 0 works (OpenAlex) · open-access PDF

Korean

We study a jump-modified Wasserstein gradient flow of the square maximum average discrepancy generated by the energy kernels $K(z)=-- Áthaz Átha^q$, $0

Machine translation (Meta M2M100); the English original follows.

Abstract

We study a jump-modified Wasserstein gradient flow of the squared maximum mean discrepancy generated by the energy kernels $K(z)=-|z|^q$, $0

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Topics: Mathematics, Balanced flow, Mathematical analysis, Energy (signal processing), Flow (mathematics), Wasserstein metric

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