23 citations · 25 across the 3 of their papers we have counts for
1 paper · 1 filter
Titouan Vayer, Rémi Flamary, Romain Tavenard +2
Recently used in various machine learning contexts, the Gromov-Wasserstein distance (GW) allows for comparing distributions whose supports do not necessarily lie in the same metric…