Approximation and computation of the geodesic Sinkhorn distance
Abstract
In [H. Lavenant, J. Luckhardt, G. Mordant, B. Schmitzer, L. Tamanini, The Riemannian geometry of Sinkhorn divergences. Ann. Inst. H. Poincaré Anal. Non Linéaire 43 (2026)] we introduced a Riemannian metric $\mathsf{d}_S$ on the space of probability distributions obtained from entropic optimal transport, specifically from the Sinkhorn divergence $S_\varepsilon$. In the present work we discuss how to approximate and compute $\mathsf{d}_S$. Spatially, we prove Gromov--Hausdorff convergence of the m...
Description / Details
In [H. Lavenant, J. Luckhardt, G. Mordant, B. Schmitzer, L. Tamanini, The Riemannian geometry of Sinkhorn divergences. Ann. Inst. H. Poincaré Anal. Non Linéaire 43 (2026)] we introduced a Riemannian metric on the space of probability distributions obtained from entropic optimal transport, specifically from the Sinkhorn divergence . In the present work we discuss how to approximate and compute . Spatially, we prove Gromov--Hausdorff convergence of the metric and convergence of geodesics for increasingly fine Eulerian discretization of the base space. Temporally, we show -convergence of the chain discretization to the energy functional defining . We deduce and implement numerical schemes to compute approximations of .
Source: arXiv:2610.02007v1 - http://arxiv.org/abs/2610.02007v1 PDF: https://arxiv.org/pdf/2610.02007v1 Original Link: http://arxiv.org/abs/2610.02007v1
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Oct 3, 2026
Mathematics
Mathematics
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