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We adapt the problem of continuous congested optimal transport to the Heisenberg group, equipped with a sub-Riemannian metric. Originally introduced in the Euclidean setting by Carlier, Jimenez, and Santambrogio as a path-dependent variant…

Optimization and Control · Mathematics 2025-10-29 Michele Circelli , Giovanna Citti

We introduce and study a variant of the Wasserstein distance on the space of probability measures, specially designed to deal with measures whose support has a dendritic, or treelike structure with a particular direction of orientation. Our…

Optimization and Control · Mathematics 2020-11-18 Young-Heon Kim , Brendan Pass , David J. Schneider

Optimal transport theory has recently been extended to quantum settings, where the density matrices generalize the probability measures. In this paper, we study the computational aspects of the order 2 quantum Wasserstein distance,…

Optimization and Control · Mathematics 2025-11-27 Saroj Prasad Chhatoi , Victor Magron

This article continues the investigation of the tracial geometry of classifiable $\mathrm{C}^*$-algebras that have real rank zero and stable rank one. Using the language of optimal transport, we describe several situations in which the…

Operator Algebras · Mathematics 2023-05-08 Bhishan Jacelon

We consider the problem of optimal approximation of a target measure by an atomic measure with $N$ atoms, in branched optimal transport distance. This is a new branched transport version of optimal quantization problems. New difficulties…

Optimization and Control · Mathematics 2025-04-01 Paul Pegon , Mircea Petrache

We develop a theory for image restoration with a learned regularizer that is analogous to that of Meyer's characterization of solutions of the classical variational method of Rudin-Osher-Fatemi (ROF). The learned regularizer we use is a…

Optimization and Control · Mathematics 2023-05-02 Tristan Milne , Adrian Nachman

Optimal transport has found widespread applications in signal processing and machine learning. Among its many equivalent formulations, optimal transport seeks to reconstruct a random variable/vector with a prescribed distribution at the…

Information Theory · Computer Science 2025-03-06 Jun Chen , Jia Wang , Ruibin Li , Han Zhou , Wei Dong , Huan Liu , Yuanhao Yu

This paper is concerned with six variational problems and their mutual connections: The quadratic Monge-Kantorovich optimal transport, the Schr\"odinger problem, Brenier's relaxed model for incompressible fluids, the so-called Br\"odinger…

Analysis of PDEs · Mathematics 2019-08-09 Aymeric Baradat , Léonard Monsaingeon

We study a parabolic equation for finding solutions to the optimal transport problem on compact Riemannian manifolds with general cost functions. We show that if the cost satisfies the strong MTW condition and the stay-away singularity…

Differential Geometry · Mathematics 2010-08-24 Young-Heon Kim , Jeffrey Streets , Micah Warren

On the space of probability densities, we extend the Wasserstein geodesics to the case of higher-order interpolation such as cubic spline interpolation. After presenting the natural extension of cubic splines to the Wasserstein space, we…

Optimization and Control · Mathematics 2018-07-27 Jean-David Benamou , Thomas Gallouët , François-Xavier Vialard

Assume that we observe i.i.d.~points lying close to some unknown $d$-dimensional $\mathcal{C}^k$ submanifold $M$ in a possibly high-dimensional space. We study the problem of reconstructing the probability distribution generating the…

Statistics Theory · Mathematics 2022-02-15 Vincent Divol

This paper presents a unified framework for smooth convex regularization of discrete optimal transport problems. In this context, the regularized optimal transport turns out to be equivalent to a matrix nearness problem with respect to…

Machine Learning · Statistics 2018-07-17 Arnaud Dessein , Nicolas Papadakis , Jean-Luc Rouas

In this work, we show the intrinsic relations between optimal transportation and convex geometry, especially the variational approach to solve Alexandrov problem: constructing a convex polytope with prescribed face normals and volumes. This…

Machine Learning · Computer Science 2017-12-20 Na Lei , Kehua Su , Li Cui , Shing-Tung Yau , David Xianfeng Gu

We present a general convex relaxation approach to study a wide class of Unbalanced Optimal Transport problems for finite non-negative measures with possibly different masses. These are obtained as the lower semicontinuous and convex…

Optimization and Control · Mathematics 2024-01-02 Giuseppe Savaré , Giacomo Enrico Sodini

We give the solution of the Monge-Kantorovitch problem on the Wiener space for the singular Wasserstein metric which is defined with respect to the distance of the underlying Cameron-Martin space. We show, under the hypothesis that this…

Probability · Mathematics 2007-05-23 D. Feyel , A. S. Ustunel

We study the problem of reconstructing the latent geometry of a $d$-dimensional Riemannian manifold from a random geometric graph. While recent works have made significant progress in manifold recovery from random geometric graphs, and more…

Machine Learning · Statistics 2026-04-02 Han Huang , Pakawut Jiradilok , Elchanan Mossel

Many variants of Optimal Transport (OT) have been developed to address its heavy computation. Among them, notably, Sliced Wasserstein (SW) is widely used for application domains by projecting the OT problem onto one-dimensional lines, and…

Machine Learning · Computer Science 2025-06-10 Viet-Hoang Tran , Trang Pham , Tho Tran , Minh Khoi Nguyen Nhat , Thanh Chu , Tam Le , Tan M. Nguyen

The goal of the present paper is to discuss new transport inequalities for convex measures. We retrieve some dimensional forms of Brascamp-Lieb inequalities. We also give some quantitative forms involving the Wasserstein's distances.

Functional Analysis · Mathematics 2017-02-27 Erik Thomas

This work establishes a framework for solving inverse boundary problems with the geodesic based quadratic Wasserstein distance ($W_{2}$). A general form of the Fr\'echet gradient is systematically derived by optimal transportation (OT)…

Numerical Analysis · Mathematics 2022-10-31 Gang Bao , Yixuan Zhang

The group of diffeomorphisms of a compact manifold endowed with the L^2 metric acting on the space of probability densities gives a unifying framework for the incompressible Euler equation and the theory of optimal mass transport. Recently,…

Differential Geometry · Mathematics 2017-12-15 Thomas Gallouët , François-Xavier Vialard