113 citations · 145 across the 2 of their papers we have counts for
3 papers
The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation
Thibault Séjourné, François-Xavier Vialard, Gabriel Peyré
Comparing metric measure spaces (i.e. a metric space endowed with aprobability distribution) is at the heart of many machine learning problems. The most popular distance between su…
Interpolating between Optimal Transport and MMD using Sinkhorn Divergences
Jean Feydy, Thibault Séjourné, François-Xavier Vialard +3
Comparing probability distributions is a fundamental problem in data sciences. Simple norms and divergences such as the total variation and the relative entropy only compare densit…
The Price of Fragmentation in Mobility-on-Demand Services
Thibault Séjourné, Samitha Samaranayake, Siddhartha Banerjee
Mobility-on-Demand platforms are a fast growing component of the urban transit ecosystem. Though a growing literature addresses the question of how to make individual MoD platforms…