3 papers
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…
math.OC2025
Constrained Approximate Optimal Transport Maps
Eloi Tanguy, Agnès Desolneux, Julie Delon
We investigate finding a map within a function class that minimises an Optimal Transport (OT) cost between a target measure and the image by of a source measure $Î…
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…