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stat.ML2026
Repulsive Monte Carlo on the sphere for the sliced Wasserstein distance
Vladimir Petrovic, Rémi Bardenet, Agnès Desolneux
In this paper, we consider the problem of computing the integral of a function on the unit sphere, in any dimension, using Monte Carlo methods. Although the methods we present are…
stat.ML2024
Gromov-Wasserstein-like Distances in the Gaussian Mixture Models Space
Antoine Salmona, Julie Delon, Agnès Desolneux
The Gromov-Wasserstein (GW) distance is frequently used in machine learning to compare distributions across distinct metric spaces. Despite its utility, it remains computationally…