#wasserstein News & Analysis

2 articles tagged with #wasserstein. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · Mar 127/10

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Gradient Flow Drifting: Generative Modeling via Wasserstein Gradient Flows of KDE-Approximated Divergences

Researchers introduce Gradient Flow Drifting, a new mathematical framework for generative AI models that connects the Drifting Model to Wasserstein gradient flows of KL divergence under kernel density estimation. The framework includes a mixed-divergence strategy to avoid mode collapse and extends to Riemannian manifolds for improved semantic space applications.

$KL

AINeutralarXiv – CS AI · Mar 54/10

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Implicit Bias of the JKO Scheme

Researchers analyzed the implicit bias of the Jordan-Kinderlehrer-Otto (JKO) scheme, a time-discretization method for Wasserstein gradient flow used in optimizing energy functionals over probability measures. They found that the JKO scheme adds a deceleration term at second order that corresponds to canonical implicit biases like Fisher information for entropy and kinetic energy for Riemannian gradient descent.