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We introduce an optimal transport topology on the space of probability measures over a fiber bundle, which penalizes the transport cost from one fiber to another. For simplicity, we illustrate our construction in the Euclidean case…

Analysis of PDEs · Mathematics 2024-01-12 Jan Peszek , David Poyato

We suggest a new way of defining optimal transport of positive-semidefinite matrix-valued measures. It is inspired by a recent rendering of the incompressible Euler equations and related conservative systems as concave maximization…

Optimization and Control · Mathematics 2019-07-16 Yann Brenier , Dmitry Vorotnikov

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 study the Lagrangian formulation of a class of the Monge-Kantorovich optimal transportation problem. It can be considered a stochastic optimal transportation problem for absolutely continuous stochastic processes. A cost function and…

Optimization and Control · Mathematics 2023-01-02 Toshio Mikami , Haruka Yamamoto

We study the stability of entropically regularized optimal transport with respect to the marginals. Lipschitz continuity of the value and H\"older continuity of the optimal coupling in $p$-Wasserstein distance are obtained under general…

Optimization and Control · Mathematics 2022-07-06 Stephan Eckstein , Marcel Nutz

The classical problem of optimal transportation can be formulated as a linear optimization problem on a convex domain: among all joint measures with fixed marginals find the optimal one, where optimality is measured against a cost function.…

Optimization and Control · Mathematics 2012-11-29 Jonathan Korman , Robert J. McCann

Let $M,N$ be two smooth compact hypersurfaces of $\mathbb{R}^n$ which bound strictly convex domains equipped with two absolutely continuous measures $\mu$ and $\nu$ (with respect to the volume measures of $M$ and $N$). We consider the…

Differential Geometry · Mathematics 2015-07-10 Emmanuel Humbert , Luc Molinet

We consider an extension of the Monge-Kantorovitch optimal transportation problem. The mass is transported along a continuous semimartingale, and the cost of transportation depends on the drift and the diffusion coefficients of the…

Probability · Mathematics 2013-10-04 Xiaolu Tan , Nizar Touzi

We introduce a general class of transport distances ${\rm WB}_{\Lambda}$ over the space of positive semi-definite matrix-valued Radon measures $\mathcal{M}(\Omega,\mathbb{S}_+^n)$, called the weighted Wasserstein-Bures distance. Such a…

Numerical Analysis · Mathematics 2023-10-18 Bowen Li , Jun Zou

We introduce the optimal transportation interpretation of the Kantorovich norm on thespace of signed Radon measures with finite mass, based on a generalized Wasserstein distancefor measures with different masses.With the formulation and the…

Analysis of PDEs · Mathematics 2019-10-14 Benedetto Piccoli , Francesco Rossi , Magali Tournus

This paper focuses on the Monge-Kantorovich formulation of the optimal transport problem and the associated $L^2$ Wasserstein distance. We use the $L^2$ Wasserstein distance in the Nearest Neighbour (NN) machine learning architecture to…

Computer Vision and Pattern Recognition · Computer Science 2019-03-20 Michael Snow , Jan Van lent

In this paper we study two basic facts of optimal transportation on Wiener space W. Our first aim is to answer to the Monge Problem on the Wiener space endowed with the Sobolev type norm (k,gamma) to the power of p (cases p = 1 and p > 1…

Probability · Mathematics 2013-01-25 Vincent Nolot

We prove the Duality Theorems for the stochastic optimal transportation problems with a convex cost function without a regularity assumption that is often supposed in the proof of the lower semicontinuity of an action integral. In our new…

Probability · Mathematics 2021-01-18 Toshio Mikami

The Monge-Kantorovich transportation problem involves optimizing with respect to a given a cost function. Uniqueness is a fundamental open question about which little is known when the cost function is smooth and the landscapes containing…

Probability · Mathematics 2010-08-27 Najma Ahmad , Hwa Kil Kim , Robert J. McCann

To improve the performance of classical generative adversarial network (GAN), Wasserstein generative adversarial networks (W-GAN) was developed as a Kantorovich dual formulation of the optimal transport (OT) problem using Wasserstein-1…

Computer Vision and Pattern Recognition · Computer Science 2020-09-01 Byeongsu Sim , Gyutaek Oh , Jeongsol Kim , Chanyong Jung , Jong Chul Ye

Suppose that $c(x,y)$ is the cost of transporting a unit of mass from $x\in X$ to $y\in Y$ and suppose that a mass distribution $\mu$ on $X$ is transported optimally (so that the total cost of transportation is minimal) to the mass…

Functional Analysis · Mathematics 2014-05-20 Sedi Bartz , Simeon Reich

We show that the Hellinger-Kantorovich distance can be expressed as the metric infimal convolution of the Hellinger and the Wasserstein distances, as conjectured by Liero, Mielke, and Savar\'e. To prove it, we study with the tools of…

Metric Geometry · Mathematics 2025-03-18 Nicolò De Ponti , Giacomo Enrico Sodini , Luca Tamanini

Using the dual formulation only, we show that the regularity of unbalanced optimal transport also called entropy-transport inherits from the regularity of standard optimal transport. We provide detailed examples of Riemannian manifolds and…

Optimization and Control · Mathematics 2024-07-02 Thomas Gallouët , Roberta Ghezzi , François-Xavier Vialard

We consider the problem of finding an optimal transport plan between an absolutely continuous measure $\mu$ on $\mathcal{X} \subset \mathbb{R}^d$ and a finitely supported measure $\nu$ on $\mathbb{R}^d$ when the transport cost is the…

Numerical Analysis · Mathematics 2018-10-08 Valentin Hartmann , Dominic Schuhmacher

We propose a fundamental metric for measuring the distance between two distributions. This metric, referred to as the decision-focused (DF) divergence, is tailored to stochastic linear optimization problems in which the objective…

Statistics Theory · Mathematics 2026-02-04 Suhan Liu , Mo Liu