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Optimal transport is widely used in pure and applied mathematics to find probabilistic solutions to hard combinatorial matching problems. We extend the Wasserstein metric and other elements of optimal transport from the matching of sets to…

Optimization and Control · Mathematics 2019-07-16 Evan Patterson

We analyze optimal transport problems with additional entropic cost evaluated along curves in the Wasserstein space which join two probability measures $m_0,m_1$. The effect of the additional entropy functional results into an elliptic…

Analysis of PDEs · Mathematics 2022-11-18 Alessio Porretta

We propose a volumetric formulation for computing the Optimal Transport problem defined on surfaces in $\mathbb{R}^3$, found in disciplines like optics, computer graphics, and computational methodologies. Instead of directly tackling the…

Numerical Analysis · Mathematics 2024-05-16 Richard Tsai , Axel G. R. Turnquist

In shape optimisation it is desirable to obtain deformations of a given mesh without negative impact on the mesh quality. We propose a new algorithm using least square formulations of the Cauchy-Riemann equations. Our method allows to…

Optimization and Control · Mathematics 2021-06-09 José A. Iglesias , Kevin Sturm , Florian Wechsung

Functional lifting methods provide a tool for approximating solutions of difficult non-convex problems by embedding them into a larger space. In this work, we investigate a mathematically rigorous formulation based on embedding into the…

Optimization and Control · Mathematics 2020-07-07 Thomas Vogt , Roland Haase , Danielle Bednarski , Jan Lellmann

We propose an efficient residual minimization technique for the nonlinear model-order reduction of parameterized hyperbolic partial differential equations. Our nonlinear approximation space is a span of snapshots evaluated on a shifted…

Numerical Analysis · Mathematics 2021-01-21 Neeraj Sarna , Sara Grundel

In the current book I suggest an off-road path to the subject of optimal transport. I tried to avoid prior knowledge of analysis, PDE theory and functional analysis, as much as possible. Thus I concentrate on discrete and semi-discrete…

Optimization and Control · Mathematics 2020-09-15 Gershon Wolansky

The problem of optimization on Stiefel manifold, i.e., minimizing functions of (not necessarily square) matrices that satisfy orthogonality constraints, has been extensively studied. Yet, a new approach is proposed based on, for the first…

Machine Learning · Computer Science 2023-03-06 Lingkai Kong , Yuqing Wang , Molei Tao

The quadratically regularized optimal transport problem is empirically known to have sparse solutions: its optimal coupling $\pi_{\varepsilon}$ has sparse support for small regularization parameter $\varepsilon$, in contrast to entropic…

Optimization and Control · Mathematics 2026-02-25 Alberto González-Sanz , Marcel Nutz

We study the convergence of divergence-regularized optimal transport as the regularization parameter vanishes. Sharp rates for general divergences including relative entropy or $L^{p}$ regularization, general transport costs and…

Optimization and Control · Mathematics 2023-06-22 Stephan Eckstein , Marcel Nutz

Optimal transportation provides a means of lifting distances between points on a geometric domain to distances between signals over the domain, expressed as probability distributions. On a graph, transportation problems can be used to…

Optimization and Control · Mathematics 2018-03-26 Montacer Essid , Justin Solomon

We introduce a new technique, which we call the boundary method, for solving semi-discrete optimal transport problems with a wide range of cost functions. The boundary method reduces the effective dimension of the problem, thus improving…

Numerical Analysis · Mathematics 2019-05-03 Luca Dieci , J. D. Walsh

This paper is devoted to the understanding of regularisation process in the shape optimization approach to the so-called Dirichlet inverse obstacle problem for elliptic operators. More precisely, we study two different regularisations of…

Optimization and Control · Mathematics 2024-04-05 Fabien Caubet , Marc Dambrine , Jérémi Dardé

This article investigates the numerical approximation of shape optimization problems with PDE constraint on classes of convex domains. The convexity constraint provides a compactness property which implies well posedness of the problem.…

Optimization and Control · Mathematics 2018-10-26 Sören Bartels , Gerd Wachsmuth

This paper introduces the use of unbalanced optimal transport methods as a similarity measure for diffeomorphic matching of imaging data. The similarity measure is a key object in diffeomorphic registration methods that, together with the…

Numerical Analysis · Mathematics 2017-06-19 Jean Feydy , Benjamin Charlier , François-Xavier Vialard , Gabriel Peyré

We consider the optimization problem for a shape cost functional $F(\Omega,f)$ which depends on a domain $\Omega$ varying in a suitable admissible class and on a "right-hand side" $f$. More precisely, the cost functional $F$ is given by an…

Optimization and Control · Mathematics 2016-05-18 José Carlos Bellido , Giuseppe Buttazzo , Bozhidar Velichkov

The optimal transport barycenter (a.k.a. Wasserstein barycenter) is a fundamental notion of averaging that extends from the Euclidean space to the Wasserstein space of probability distributions. Computation of the unregularized barycenter…

Machine Learning · Statistics 2025-05-27 Kaheon Kim , Rentian Yao , Changbo Zhu , Xiaohui Chen

Coastal erosion describes the displacement of sand caused by the movement induced by tides, waves or currents. Some of its wave phenomena are modeled by Helmholtz-type equations. Our purposes, in this paper are, first, to study optimal…

Numerical Analysis · Mathematics 2022-07-05 Mame Gor Ngom , Ibrahima Faye , Diaraf Seck

A Coefficient Inverse Problem for the radiative transport equation is considered. The globally convergent numerical method, the so-called convexification, is developed. For the first time, the viscosity solution is considered for a boundary…

Numerical Analysis · Mathematics 2023-03-17 Michael V. Klibanov , Jingzhi Li , Zhipeng Yang

We propose a fast and scalable algorithm to project a given density on a set of structured measures defined over a compact 2D domain. The measures can be discrete or supported on curves for instance. The proposed principle and algorithm are…

Numerical Analysis · Mathematics 2019-02-05 Frédéric de Gournay , Jonas Kahn , Léo Lebrat , Pierre Weiss