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Given a smooth Riemannian manifold $(M,g)$, compact and without boundary, we analyze the dynamical optimal mass transport problem where the cost is given by the sum of the kinetic energy and the relative entropy with respect to a reference…

Analysis of PDEs · Mathematics 2024-01-05 Gabriele Bocchi , Alessio Porretta

In this paper we develop a boundary $\varepsilon$-regularity theory for optimal transport maps between bounded open sets with $C^{1,\alpha}$-boundary. Our main result asserts sharp $C^{1,\alpha}$-regularity of transport maps at the boundary…

Analysis of PDEs · Mathematics 2021-02-16 Tatsuya Miura , Felix Otto

Coupling probability measures lies at the core of many problems in statistics and machine learning, from domain adaptation to transfer learning and causal inference. Yet, even when restricted to deterministic transports, such couplings are…

Machine Learning · Statistics 2025-09-22 Lucas De Lara , Luca Ganassali

This article generalizes the study of ramified optimal transport with capacity constraint in transport multi-paths by generalizing the $\mathbf{M}_{\alpha}$ cost to $\mathbf{M}_{\alpha,c}$, which incorporates capacity constraints into the…

Optimization and Control · Mathematics 2025-10-14 Qinglan Xia , Haotian Sun

We study an optimal transport problem with a backward martingale constraint in a pseudo-Euclidean space $S$. We show that the dual problem consists in the minimization of the expected values of the Fitzpatrick functions associated with…

Probability · Mathematics 2023-12-11 Dmitry Kramkov , Mihai Sîrbu

In the classical Monge-Kantorovich problem, the transportation cost only depends on the amount of mass sent from sources to destinations and not on the paths followed by this mass. Thus, it does not allow for congestion effects. Using the…

Optimization and Control · Mathematics 2007-05-23 G. Carlier , C. Jimenez , F. Santambrogio

In this paper, we introduce a variant of optimal transport adapted to the causal structure given by an underlying directed graph $G$. Different graph structures lead to different specifications of the optimal transport problem. For…

Statistics Theory · Mathematics 2024-07-08 Patrick Cheridito , Stephan Eckstein

We study a multi-marginal optimal transportation problem with a cost function of the form $c(x_{1}, \ldots,x_{m})=\sum_{k=1}^{m-1}|x_{k}-x_{k+1}|^{2} + |x_{m}- F(x_{1})|^{2}$, where $F: \mathbb{R}^n \rightarrow \mathbb{R}^n$. When $m=4$,…

Optimization and Control · Mathematics 2020-01-13 Brendan Pass , Adolfo Vargas-Jiménez

It is well known that martingale transport plans between marginals $\mu\neq\nu$ are never given by Monge maps -- with the understanding that the map is over the first marginal $\mu$, or forward in time. Here, we change the perspective, with…

Probability · Mathematics 2024-07-03 Marcel Nutz , Ruodu Wang , Zhenyuan Zhang

We study the small-regularisation limit of the entropic optimal transport problem on the line with distance cost. While convergence of entropic minimizers is well understood in the discrete setting and in the case where the cost is…

Optimization and Control · Mathematics 2025-12-08 Armand Ley

We consider the model of a transportation problem with the objective of finding a minimum-cost transportation plan for shipping a given commodity from a set of supply centers to the customers. Since the exact values of supply and demand and…

Optimization and Control · Mathematics 2023-01-31 Elif Garajová , Miroslav Rada

We give a characterization of optimal transport plans for a variant of the usual quadratic transport cost introduced in [33]. Optimal plans are composition of a deterministic transport given by the gradient of a continuously differentiable…

Probability · Mathematics 2019-09-18 Nathael Gozlan , Nicolas Juillet

The inverse optimal transport problem is to find the underlying cost function from the knowledge of optimal transport plans. While this amounts to solving a linear inverse problem, in this work we will be concerned with the nonlinear…

Optimization and Control · Mathematics 2025-09-03 Alberto González-Sanz , Michel Groppe , Axel Munk

We investigate the minimum cost of a wide class of combinatorial optimization problems over random bipartite geometric graphs in $\mathbb{R}^d$ where the edge cost between two points is given by a $p$-th power of their Euclidean distance.…

Probability · Mathematics 2023-07-20 Michael Goldman , Dario Trevisan

We study the inverse optimal transport problem of recovering the ground cost from an optimal transport plan. In discrete settings, this problem reduces to inverse linear programming and is intrinsically ill-posed, exhibiting…

Optimization and Control · Mathematics 2026-04-27 Gabriel Peyré , Clarice Poon , Oscar Tron

We investigate metric conditions that allow to prove existence and uniqueness of a map solving the Monge problem between two marginals in a metric (measure) space, proving two main results. Firstly, we introduce a nonsmooth version of the…

Metric Geometry · Mathematics 2024-10-31 Shucheng Li , Mattia Magnabosco , Timo Schultz

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

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

We prove that for two-marginal optimal transport with Coulomb cost, the optimal map is a $C^{1,\alpha}$ diffeomorphism outside a closed set of Lebesgue measure zero provided the marginals are $\alpha$-H\"older continuous and bounded away…

Analysis of PDEs · Mathematics 2025-08-05 Gero Friesecke , Tobias Ried

We focus on Optimal Transport PDE on the unit sphere $\mathbb{S}^2$ with a particular type of cost function $c(x,y) = F(x \cdot y, x \cdot \hat{e}, y \cdot \hat{e})$ which we call cost functions with preferential direction, where $\hat{e}…

Analysis of PDEs · Mathematics 2024-07-11 Axel G. R. Turnquist
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