23 citations · 25 across the 3 of their papers we have counts for
3 papers
Subspace Detours Meet Gromov-Wasserstein
Clément Bonet, Nicolas Courty, François Septier +1
In the context of optimal transport methods, the subspace detour approach was recently presented by Muzellec and Cuturi (2019). It consists in building a nearly optimal transport p…
Efficient Gradient Flows in Sliced-Wasserstein Space
Clément Bonet, Nicolas Courty, François Septier +1
Minimizing functionals in the space of probability distributions can be done with Wasserstein gradient flows. To solve them numerically, a possible approach is to rely on the Jorda…
Sliced Gromov-Wasserstein
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…