This was part of Applied Optimal Transport

Differentiable Matchings, Mappings and JKO Steps

Marco Cuturi, Apple ML Research and École Nationale de la Statistique et de l’Administration Économique

Wednesday, May 18, 2022


I will present in this talk use cases in ML where optimal matchings pop up in various applied areas in ML. I will in particular mention areas where the optimal matching needs to be differentiated, in a way or another w.r.t. input parameters. I will then introduce two approaches to do so, either through entropic regularization or using neural solvers. I will present the implementation of these approaches in two instances: in the ott-jax toolbox that I have been developing actively, or to solve a bilevel optimization problem that appears when fitting JKO models to time series of measures.