Computational optimal transport: With applications to data science
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 …
mathematician Gaspard Monge (1746–1818): A worker with a shovel in hand has to move a …
Convolutional wasserstein distances: Efficient optimal transportation on geometric domains
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 …
transportation over geometric domains. Our main contribution is to show that optimal …
Entropic metric alignment for correspondence problems
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 …
geometric domains. Efficient methods that stably extract" soft" matches in the presence of …
Deep variational network embedding in wasserstein space
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 …
preserving the inherent structural properties of the network, has attracted considerable …
A survey of optimal transport for computer graphics and computer vision
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 …
theoretical and numerical point of views. Starting from the 50s this theory has also found a …
Convergence of a Newton algorithm for semi-discrete optimal transport
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 …
probability measure is absolutely continuous while the target measure is finitely supported …
SPARKLING: variable‐density k‐space filling curves for accelerated T2*‐weighted MRI
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 …
context of compressed sensing: Spreading Projection Algorithm for Rapid K‐space …
Efficiency of methods for determining the relevance of criteria in sustainable transport problems: A comparative case study
Problems related to sustainable urban transport have gained in importance with the rapid
growth of urban agglomerations. There is, therefore, a need to support decision-making …
growth of urban agglomerations. There is, therefore, a need to support decision-making …
Nonparametric multiple-output center-outward quantile regression
Building on recent measure-transportation-based concepts of multivariate quantiles, we are
considering the problem of nonparametric multiple-output quantile regression. Our approach …
considering the problem of nonparametric multiple-output quantile regression. Our approach …
High-contrast computational caustic design
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 …
shape of a transparent object such that the refracted light paints a desired caustic image on …