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In this paper, we present a numerical method, based on iterative Bregman projections, to solve the optimal transport problem with Coulomb cost. This is related to the strong interaction limit of Density Functional Theory. The first idea is…

Numerical Analysis · Mathematics 2015-05-11 Jean-David Benamou , Guillaume Carlier , Luca Nenna

In this article we prove the existence of a stochastic optimal transference plan for a stochastic Monge-Kantorovich problem by measurable selection theorem. A stochastic version of Kantorovich duality and the characterization of stochastic…

Probability · Mathematics 2010-02-12 Xicheng Zhang

The classical duality theory of Kantorovich and Kellerer for the classical optimal transport is generalized to an abstract framework and a characterization of the dual elements is provided. This abstract generalization is set in a Banach…

Functional Analysis · Mathematics 2017-10-25 Ibrahim Ekren , H. Mete Soner

The use of distances based on optimal transportation has recently shown promise for discrimination of power spectra. In particular, spectral estimation methods based on l1 regularization as well as covariance based methods can be shown to…

Computer Vision and Pattern Recognition · Computer Science 2019-04-09 Ali Sadeghian , Deoksu Lim , Johan Karlsson , Jian Li

We develop and analyze methods for computing provably optimal {\em maximum a posteriori} (MAP) configurations for a subclass of Markov random fields defined on graphs with cycles. By decomposing the original distribution into a convex…

Information Theory · Computer Science 2007-07-13 Martin J. Wainwright , Tommi S. Jaakkola , Alan S. Willsky

We present a general duality result for Wasserstein distributionally robust optimization that holds for any Kantorovich transport cost, measurable loss function, and nominal probability distribution. Assuming an interchangeability principle…

Optimization and Control · Mathematics 2024-11-26 Luhao Zhang , Jincheng Yang , Rui Gao

In this work, we propose a novel machine learning approach to compute the optimal transport map between two continuous distributions from their unpaired samples, based on the DeepParticle methods. The proposed method leads to a min-min…

Machine Learning · Statistics 2025-07-01 Yingyuan Li , Aokun Wang , Zhongjian Wang

We study the linearization of a discrete transportation distance between probability distributions on finite weighted graphs originally due to Maas (``Gradient flows of the entropy for finite {M}arkov chains,'' J. Funct. Anal. 261(8), 2011)…

Optimization and Control · Mathematics 2026-04-09 Sawyer Robertson , Zhengchao Wan , Alexander Cloninger

We pose the Kantorovich optimal transport problem as a min-max problem with a Nash equilibrium that can be obtained dynamically via a two-player game, providing a framework for approximating optimal couplings. We prove convergence of the…

Optimization and Control · Mathematics 2025-05-28 Lauren Conger , Franca Hoffmann , Ricardo Baptista , Eric Mazumdar

We consider so-called branched transport and variants thereof in two space dimensions. In these models one seeks an optimal transportation network for a given mass transportation task. In two space dimensions, they are closely connected to…

Numerical Analysis · Mathematics 2020-04-01 Carolin Dirks , Benedikt Wirth

Numerous problems of both theoretical and practical interest are related to finding shortest (or otherwise optimal) paths in networks, frequently in the presence of some obstacles or constraints. A somewhat related class of problems focuses…

Statistical Mechanics · Physics 2021-03-01 Ricardo Gutiérrez , Carlos Pérez-Espigares

We study dynamical optimal transport of discrete time systems (dDOT) with Lagrangian cost. The problem is approached by combining optimal control and Kantorovich duality theory. Based on the derived solution, a first order splitting…

Optimization and Control · Mathematics 2024-10-15 Dongjun Wu , Anders Rantzer

Optimal transport (OT) theory provides powerful tools to compare probability measures. However, OT is limited to nonnegative measures having the same mass, and suffers serious drawbacks about its computation and statistics. This leads to…

Machine Learning · Statistics 2021-01-26 Tam Le , Truyen Nguyen

This paper deals with dynamical optimal transport metrics defined by spatial discretisation of the Benamou--Benamou formula for the Kantorovich metric $W_2$. Such metrics appear naturally in discretisations of $W_2$-gradient flow…

Analysis of PDEs · Mathematics 2020-01-24 Peter Gladbach , Eva Kopfer , Jan Maas , Lorenzo Portinale

Learning conditional distributions is challenging because the desired outcome is not a single distribution but multiple distributions that correspond to multiple instances of the covariates. We introduce a novel neural entropic optimal…

Machine Learning · Computer Science 2024-06-05 Bao Nguyen , Binh Nguyen , Hieu Trung Nguyen , Viet Anh Nguyen

This paper presents a widely applicable approach to solving (multi-marginal, martingale) optimal transport and related problems via neural networks. The core idea is to penalize the optimization problem in its dual formulation and reduce it…

Optimization and Control · Mathematics 2019-01-28 Stephan Eckstein , Michael Kupper

We consider dynamical transport metrics for probability measures on discretisations of a bounded convex domain in $\mathbb{R}^d$. These metrics are natural discrete counterparts to the Kantorovich metric $\mathbb{W}_2$, defined using a…

Analysis of PDEs · Mathematics 2020-01-30 Peter Gladbach , Eva Kopfer , Jan Maas

We study optimal transportation problems with constraints on densities of transport plans. We obtain a sharp condition for the uniqueness of an optimal solution to the Kantorovich problem with density constraints, namely that the Borel…

Functional Analysis · Mathematics 2024-01-17 Svetlana Popova

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 optimal transport (OT) problem for probability measures supported on a tree metric space. It is known that such OT problem (i.e., tree-Wasserstein (TW)) admits a closed-form expression, but depends fundamentally on the underlying…

Machine Learning · Statistics 2024-03-04 Tam Le , Truyen Nguyen , Kenji Fukumizu