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 …

This paper introduces a new class of algorithms for optimization problems involving optimal
transportation over geometric domains. Our main contribution is to show that optimal …

Many shape and image processing tools rely on computation of correspondences between
geometric domains. Efficient methods that stably extract" soft" matches in the presence of …

Optimal transport is a long‐standing theory that has been studied in depth from both
theoretical and numerical point of views. Starting from the 50s this theory has also found a …

A popular way to solve optimal transport problems numerically is to assume that the source
probability measure is absolutely continuous while the target measure is finitely supported …

Network embedding, aiming to embed a network into a low dimensional vector space while
preserving the inherent structural properties of the network, has attracted considerable …

We present a new algorithm for computational caustic design. Our algorithm solves for the
shape of a transparent object such that the refracted light paints a desired caustic image on …

This chapter describes techniques for the numerical resolution of optimal transport
problems. We will consider several discretizations of these problems, and we will put a …

Purpose To present a new optimition‐driven design of optimal k‐space trajectories in the
context of compressed sensing: Spreading Projection Algorithm for Rapid K‐space …

We introduce a novel method for computing the earth mover's distance (EMD) between
probability distributions on a discrete surface. Rather than using a large linear program with …