73 citations · 134 across the 7 of their papers we have counts for
4 papers · 1 filter
Geometric Losses for Distributional Learning
Arthur Mensch, Mathieu Blondel, Gabriel Peyré
Building upon recent advances in entropy-regularized optimal transport, and upon Fenchel duality between measures and continuous functions , we propose a generalization of the logi…
Stochastic Deep Networks
Gwendoline de Bie, Gabriel Peyré, Marco Cuturi
Machine learning is increasingly targeting areas where input data cannot be accurately described by a single vector, but can be modeled instead using the more flexible concept of r…
Computational Optimal Transport
Gabriel Peyré, Marco Cuturi
Optimal transport (OT) theory can be informally described using the words of the French mathematician Gaspard Monge (1746-1818): A worker with a shovel in hand has to move a large…
Learning Generative Models with Sinkhorn Divergences
Aude Genevay, Gabriel Peyré, Marco Cuturi
The ability to compare two degenerate probability distributions (i.e. two probability distributions supported on two distinct low-dimensional manifolds living in a much higher-dime…