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Petr Mokrov

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#machine learning Preprint Oct 2026

Light Entropic Optimal Transport on Riemannian Manifolds

Entropic Optimal Transport (EOT) has become a practical framework for learning stochastic couplings between complex distributions, with applications in generative modeling and domain adaptation. However, most EOT solvers are designed for Euclidean spaces, while manifold extensions remain limited and often rely on costl...

Xavier Aramayo-Carrasco, Petr Mokrov, Alexander Korotin · 0 citations