2 citations · 6 across the 14 of their papers we have counts for
Showing 2024Show all
2 papers · 1 filter
math.OC2024
Mirror and Preconditioned Gradient Descent in Wasserstein Space
Clément Bonet, Théo Uscidda, Adam David +2
As the problem of minimizing functionals on the Wasserstein space encompasses many applications in machine learning, different optimization algorithms on have receiv…
cs.LG2024★ 1 cited
Sliced-Wasserstein Distances and Flows on Cartan-Hadamard Manifolds
Clément Bonet, Lucas Drumetz, Nicolas Courty
While many Machine Learning methods were developed or transposed on Riemannian manifolds to tackle data with known non Euclidean geometry, Optimal Transport (OT) methods on such sp…