Posts for: #optimal-transport

Last time we had an introductory look at OT, the definition and computation of the Wasserstein distance.

A few years ago, I wrote a solver for this variational formulation of mean-field games, as part of a project. This eventually led to a small C++ library as a toy project, which might or might not be usable.

The goal of optimal transport problems, is to find optimal mappings between probability meaures: these mappings are also called transport plans, and can take the form of functional transforms (in Monge's original problem) or joint probability distributions (in the Kantorovitch relaxation).