Showing stat.MLShow all
2 papers · 1 filter
stat.ML2025
Properties of Discrete Sliced Wasserstein Losses
Eloi Tanguy, Rémi Flamary, Julie Delon
The Sliced Wasserstein (SW) distance has become a popular alternative to the Wasserstein distance for comparing probability measures. Widespread applications include image processi…
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…