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Computationally solving multi-marginal optimal transport (MOT) with squared Euclidean costs for $N$ discrete probability measures has recently attracted considerable attention, in part because of the correspondence of its solutions with…

Numerical Analysis · Mathematics 2022-02-03 Johannes von Lindheim

Weak optimal transport generalizes the classical theory of optimal transportation to nonlinear cost functions and covers a range of problems that lie beyond the traditional theory - including entropic transport, martingale transport, and…

Probability · Mathematics 2025-07-16 Filip Pramenković

We propose a discrete transport equation on graphs which connects distributions on both vertices and edges. We then derive a discrete analogue of the Benamou-Brenier formulation for Wasserstein-$1$ distance on a graph and as a result…

Information Theory · Computer Science 2026-04-16 Kieran Morris , Oliver Johnson

We present a survey on several mass transportation problems, in which a given mass dynamically moves from an initial configuration to a final one. The approach we consider is the one introduced by Benamou and Brenier in [5], where a…

Optimization and Control · Mathematics 2012-04-10 Giuseppe Buttazzo

We develop a numerical method for the martingale analogue of the Benamou--Brenier optimal transport problem, which seeks a martingale interpolating two prescribed marginals which is closest to the Brownian motion. Recent contributions have…

Computational Finance · Quantitative Finance 2026-03-10 Manuel Hasenbichler , Benjamin Joseph , Gregoire Loeper , Jan Obloj , Gudmund Pammer

We investigate the convergence rate of multi-marginal optimal transport costs that are regularized with the Boltzmann-Shannon entropy, as the noise parameter $\varepsilon$ tends to $0$. We establish lower and upper bounds on the difference…

Optimization and Control · Mathematics 2025-04-30 Luca Nenna , Paul Pegon

We investigate how mass transports that optimize the inner product cost -considered by Y. Brenier- propagate in time along a given Lagrangian. In the deterministic case, we consider transports that maximize and minimize the following…

Analysis of PDEs · Mathematics 2018-04-27 Alistair Barton , Nassif Ghoussoub

We consider robust variants of the standard optimal transport, named robust optimal transport, where marginal constraints are relaxed via Kullback-Leibler divergence. We show that Sinkhorn-based algorithms can approximate the optimal cost…

Machine Learning · Computer Science 2021-10-29 Khang Le , Huy Nguyen , Quang Nguyen , Tung Pham , Hung Bui , Nhat Ho

We construct Two-Point Flux Approximation (TPFA) finite volume schemes to solve the quadratic optimal transport problem in its dynamic form, namely the problem originally introduced by Benamou and Brenier. We show numerically that these…

Numerical Analysis · Mathematics 2021-08-31 Andrea Natale , Gabriele Todeschi

Variational problems that involve Wasserstein distances and more generally optimal transport (OT) theory are playing an increasingly important role in data sciences. Such problems can be used to form an examplar measure out of various…

Machine Learning · Computer Science 2018-11-15 Marco Cuturi , Gabriel Peyré

Multi-marginal optimal transport enables one to compare multiple probability measures, which increasingly finds application in multi-task learning problems. One practical limitation of multi-marginal transport is computational scalability…

Wasserstein barycenter, built on the theory of optimal transport, provides a powerful framework to aggregate probability distributions, and it has increasingly attracted great attention within the machine learning community. However, it…

Machine Learning · Computer Science 2022-12-20 Jinjin Chi , Zhiyao Yang , Jihong Ouyang , Ximing Li

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

Wasserstein barycenters correspond to optimal solutions of transportation problems for several marginals, and as such have a wide range of applications ranging from economics to statistics and computer science. When the marginal probability…

Optimization and Control · Mathematics 2015-08-11 Ethan Anderes , Steffen Borgwardt , Jacob Miller

The purpose of this paper is to introduce a new numerical method to solve multi-marginal optimal transport problems with pairwise interaction costs. The complexity of multi-marginal optimal transport generally scales exponentially in the…

Optimization and Control · Mathematics 2023-08-08 Luca Nenna , Brendan Pass

We investigate the optimal mass transport problem associated to the following "ballistic" cost functional on phase space $M\times M^*$, $$ b_T(v, x):=\inf\{\langle v, \gamma (0)\rangle +\int_0^TL(\gamma (t), {\dot \gamma}(t))\, dt, \gamma…

Analysis of PDEs · Mathematics 2017-06-13 Nassif Ghoussoub

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 provide a solution to the problem of optimal transport by Brownian martingales in general dimensions whenever the transport cost satisfies certain subharmonic properties in the target variable, as well as a stochastic version of the…

Analysis of PDEs · Mathematics 2020-10-07 Nassif Ghoussoub , Young-Heon Kim , Aaron Zeff Palmer

In this paper we consider the Benamou-Brenier formulation of optimal transport for nonlinear control affine systems on $\Rd$, removing the compactness assumption of the underlying manifold in previous work by the author. By using Bernard's…

Optimization and Control · Mathematics 2025-05-02 Karthik Elamvazhuthi

A convex duality result for martingale optimal transport problems with two marginals was established in Beiglb\"ock et al. (2013). In this paper we provide a generalization of this result to the multi-period setting.

Probability · Mathematics 2024-03-06 Julian Sester