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In this paper, we want to establish some general results in the Lorentzian optimal transport theory that have well-known Riemannian counterparts. As a first result, we will provide non-trivial assumptions on the measures to ensure strong…

Optimization and Control · Mathematics 2026-01-15 Alec Metsch

We introduce a general notion of transport cost that encompasses many costs used in the literature (including the classical one and weak transport costs introduced by Talagrand and Marton in the 90's), and prove a Kantorovich type duality…

Probability · Mathematics 2015-12-25 Nathael Gozlan , Cyril Roberto , Paul-Marie Samson , Prasad Tetali

The classical Kantorovich-Rubinstein duality theorem establishes a significant connection between Monge optimal transport and maximization of a linear form on the set of 1-Lipschitz functions. This result has been widely used in various…

Optimization and Control · Mathematics 2025-11-04 Karol Bołbotowski , Guy Bouchitté

We introduce weak barycenters of a family of probability distributions, based on the recently developed notion of optimal weak transport of mass by Gozlanet al. (2017) and Backhoff-Veraguas et al. (2020). We provide a theoretical analysis…

Machine Learning · Statistics 2023-03-13 Elsa Cazelles , Felipe Tobar , Joaquín Fontbona

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

Given a complete Riemannian manifold $M$ with a lower Ricci curvature bound, we consider barycenters in the Wasserstein space $\mathcal{W}_2(M)$ of probability measures on $M$. We refer to them as Wasserstein barycenters, which by…

Probability · Mathematics 2025-12-05 Jianyu Ma

An analogue of the quadratic Wasserstein (or Monge-Kantorovich) distance between Borel probability measures on $\mathbf{R}^d$ has been defined in [F. Golse, C. Mouhot, T. Paul: Commun. Math. Phys. 343 (2015), 165-205] for density operators…

Mathematical Physics · Physics 2021-02-10 Emanuele Caglioti , François Golse , Thierry Paul

An easy consequence of Kantorovich-Rubinstein duality is the following: if $f:[0,1]^d \rightarrow \infty$ is Lipschitz and $\left\{x_1, \dots, x_N \right\} \subset [0,1]^d$, then $$ \left| \int_{[0,1]^d} f(x) dx - \frac{1}{N}…

Probability · Mathematics 2020-10-27 Stefan Steinerberger

We consider the optimal transportation problem on a globally hyperbolic spacetime for some cost function $c_2$, which corresponds to the optimal transportation problem on a complete Riemannian manifold where the cost function is the…

Optimization and Control · Mathematics 2025-06-10 Alec Metsch

Given a collection of probability measures, a practitioner sometimes needs to find an "average" distribution which adequately aggregates reference distributions. A theoretically appealing notion of such an average is the Wasserstein…

In many applications in statistics and machine learning, the availability of data samples from multiple possibly heterogeneous sources has become increasingly prevalent. On the other hand, in distributionally robust optimization, we seek…

Machine Learning · Statistics 2022-05-31 Tim Tsz-Kit Lau , Han Liu

In this paper, we address a fundamental limitation of the classical Wasserstein barycenter -- its sensitivity to outliers and its reliance on finite first/second moment assumptions. To overcome these issues, we propose the robust…

Methodology · Statistics 2026-03-10 Zixiong Cheng , Hang Liu

The optimal weak transport problem has recently been introduced by Gozlan et.\ al. We provide general existence and duality results for these problems on arbitrary Polish spaces, as well as a necessary and sufficient optimality criterion in…

Optimization and Control · Mathematics 2019-09-06 Julio Backhoff Veraguas , Mathias Beiglboeck , Gudmund Pammer

Controlling the $\mathcal W_\infty$ Wasserstein distance by the $\mathcal W_p$ Wasserstein distance is interesting both for theorical and numerical applications. A first paper on this problem was written several years ago [3]. Some year…

Optimization and Control · Mathematics 2026-01-22 Luigi De Pascale , Igor Pinheiro

We formulate and study an optimal transportation problem with infinitely many marginals; this is a natural extension of the multi-marginal problem studied by Gangbo and Swiech (1998). We prove results on the existence, uniqueness and…

Analysis of PDEs · Mathematics 2012-06-26 Brendan Pass

In this article, we generalize the Wasserstein distance to measures with different masses. We study the properties of such distance. In particular, we show that it metrizes weak convergence for tight sequences. We use this generalized…

Analysis of PDEs · Mathematics 2015-06-05 Benedetto Piccoli , Francesco Rossi

We present a novel method for efficiently computing optimal transport maps and Wasserstein barycenters in high-dimensional spaces. Our approach uses conditional normalizing flows to approximate the input distributions as invertible…

Machine Learning · Statistics 2025-05-29 Gabriele Visentin , Patrick Cheridito

This is our first paper on the extension of our recent work on the Lax-Oleinik commutators and its applications to the intrinsic approach of propagation of singularities of the viscosity solutions of Hamilton-Jacobi equations. We…

Analysis of PDEs · Mathematics 2024-02-07 Wei Cheng , Jiahui Hong , Tianqi Shi

We consider a multimarginal optimal transport, which includes as a particular case the Wasserstein barycenter problem. In this problem one has to find an optimal coupling between $m$ probability measures, which amounts to finding a tensor…

Optimization and Control · Mathematics 2020-09-11 Nazarii Tupitsa , Pavel Dvurechensky , Alexander Gasnikov , César A. Uribe

In recent work arXiv:2109.07820 we have shown the equivalence of the widely used nonconvex (generalized) branched transport problem with a shape optimization problem of a street or railroad network, known as (generalized) urban planning…

Optimization and Control · Mathematics 2022-10-19 Julius Lohmann , Bernhard Schmitzer , Benedikt Wirth