Abstract

We will present a method to efficiently compute Wasserstein gradient flows. The approach is based on a generalization of the back-and-forth method that we developed with Matt Jacobs to solve optimal transport problems. The gradient flow is evolved by solving the dual problem to the JKO scheme: in general, this dual problem is much better behaved than the primal problem. This allows to efficiently run large scale gradient flows simulations for a large class of internal energies including singular and non-convex energies. This is joint work with Matt Jacobs and Wonjun Lee.