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Vincent Souveton

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#machine learning Preprint Sep 2026

Riemannian Neural Hamiltonian Flows: Geodesic Symplectic Transport and Interpretability

Hamiltonian normalizing flows are attractive generative models because their phase-space maps are invertible and volume preserving, but most neural constructions are formulated in Euclidean space. We introduce Riemannian Neural Hamiltonian Flows, which combine the fixed kinetic energy of a Riemannian manifold, a learne...

Vincent Souveton · 0 citations