Mean field games (MFG) and mean field control (MFC) are critical classes of multiagent
models for the efficient analysis of massive populations of interacting agents. Their areas of …

Computing Wasserstein barycenters (aka optimal transport barycenters) is a fundamental
problem in geometry which has recently attracted considerable attention due to many …

We devise a theoretical framework and a numerical method to infer trajectories of a
stochastic process from samples of its temporal marginals. This problem arises in the …

Abstract Multimarginal Optimal Transport (MOT) has attracted significant interest due to
applications in machine learning, statistics, and the sciences. However, in most applications …

Trajectory inference aims at recovering the dynamics of a population from snapshots of its
temporal marginals. To solve this task, a min-entropy estimator relative to the Wiener …

We investigate the resolution of second-order, potential, and monotone mean field games
with the generalized conditional gradient algorithm, an extension of the Frank-Wolfe …

Abstract Multimarginal Optimal Transport (MOT) is the problem of linear programming over
joint probability distributions with fixed marginals. A key issue in many applications is the …

Optimal transportation, modelling and numerical simulation Optimal transportation, modelling
and numerical simulation Abstract We present an overviewof the basic theory, modern optimal …

We study the mean field Schrödinger problem (MFSP), that is the problem of finding the most
likely evolution of a cloud of interacting Brownian particles conditionally on the observation …

We show non-asymptotic exponential convergence of Sinkhorn iterates to the Schr\" odinger
potentials, solutions of the quadratic Entropic Optimal Transport problem on $\mathbb {R}^ d …