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By means of a novel variational approach and using dual maps techniques and general ideas of dynamical system theory we derive exact results about several models of transport flows, for which we also obtain a complete description of their…

Chaotic Dynamics · Physics 2007-05-23 Michael Blank

The behavior of the probability density function (PDF) transport equation at the limits of the probability space is studied from the point of view of fluid mechanics. Different boundary conditions are considered depending on the nature of…

Fluid Dynamics · Physics 2025-02-04 Luis Valiño , Juan Hierro

Optimal mass transport, also known as the earth mover's problem, is an optimization problem with important applications in various disciplines, including economics, probability theory, fluid dynamics, cosmology and geophysics to cite a few.…

Numerical Analysis · Mathematics 2022-06-28 Said Kerrache , Yasushi Nakauchi

The present review article has attempted a compact formalism description of transport coefficient calculations for relativistic fluid, which is expected in heavy ion collision experiments. Here, we first address the macroscopic description…

Nuclear Theory · Physics 2024-04-03 Ashutosh Dwibedi , Nandita Padhan , Arghya Chatterjee , Sabyasachi Ghosh

Obtaining solutions to Optimal Transportation (OT) problems is typically intractable when the marginal spaces are continuous. Recent research has focused on approximating continuous solutions with discretization methods based on i.i.d.…

Optimization and Control · Mathematics 2021-02-17 Junqi Wang , Pei Wang , Patrick Shafto

Optimal Transport has received much attention in Machine Learning as it allows to compare probability distributions by exploiting the geometry of the underlying space. However, in its original formulation, solving this problem suffers from…

Machine Learning · Computer Science 2023-11-27 Clément Bonet

In this work, we analyze the properties of the solution to the covariance steering problem for discrete time Gaussian linear systems with a squared Wasserstein distance terminal cost. In our previous work, we have shown that by utilizing…

Optimization and Control · Mathematics 2021-03-26 Isin M. Balci , Abhishek Halder , Efstathios Bakolas

We consider optimal transportation of measures on metric and topological spaces in the case where the cost function and marginal distributions depend on a parameter with values in a metric space. The Hausdorff distance between the sets of…

Functional Analysis · Mathematics 2021-11-29 Vladimir Bogachev , Svetlana Popova

A common way to quantify the ,,distance'' between measures is via their discrepancy, also known as maximum mean discrepancy (MMD). Discrepancies are related to Sinkhorn divergences $S_\varepsilon$ with appropriate cost functions as…

Optimization and Control · Mathematics 2020-08-25 Sebastian Neumayer , Gabriele Steidl

This is the first part of a general description in terms of mass transport for time-evolving interacting particles systems, at a mesoscopic level. Beyond kinetic theory, our framework naturally applies in biology, computer vision, and…

Analysis of PDEs · Mathematics 2025-08-12 Giovanni Brigati , Jan Maas , Filippo Quattrocchi

The paper studies the robustness properties of discrete-time stochastic optimal control under Wasserstein model approximation for both discounted-cost and average-cost criteria. Specifically, we study the performance loss when applying an…

Systems and Control · Electrical Eng. & Systems 2026-03-10 Yichen Zhou , Yanglei Song , Serdar Yüksel

Given two probability measures on sequential data, we investigate the transport problem with time-inconsistent preferences in a discrete-time setting. Motivating examples are nonlinear objectives, state-dependent costs, and regularized…

Optimization and Control · Mathematics 2025-06-23 Erhan Bayraktar , Bingyan Han

Coupling probability measures lies at the core of many problems in statistics and machine learning, from domain adaptation to transfer learning and causal inference. Yet, even when restricted to deterministic transports, such couplings are…

Machine Learning · Statistics 2025-09-22 Lucas De Lara , Luca Ganassali

The Wasserstein distance, rooted in optimal transport (OT) theory, is a popular discrepancy measure between probability distributions with various applications to statistics and machine learning. Despite their rich structure and…

Machine Learning · Statistics 2023-03-02 Sloan Nietert , Rachel Cummings , Ziv Goldfeld

We shall present a measure theoretical approach for which together with the Kantorovich duality provide an efficient tool to study the optimal transport problem. Specifically, we study the support of optimal plans where the cost function…

Analysis of PDEs · Mathematics 2014-11-21 Abbas Moameni

The notion of entropy-regularized optimal transport, also known as Sinkhorn divergence, has recently gained popularity in machine learning and statistics, as it makes feasible the use of smoothed optimal transportation distances for data…

Statistics Theory · Mathematics 2019-11-05 Jérémie Bigot , Elsa Cazelles , Nicolas Papadakis

We discuss a new notion of distance on the space of finite and nonnegative measures which can be seen as a generalization of the well-known Kantorovich-Wasserstein distance. The new distance is based on a dynamical formulation given by an…

Metric Geometry · Mathematics 2018-01-17 Matthias Liero , Alexander Mielke , Giuseppe Savaré

We give a characterization of optimal transport plans for a variant of the usual quadratic transport cost introduced in [33]. Optimal plans are composition of a deterministic transport given by the gradient of a continuously differentiable…

Probability · Mathematics 2019-09-18 Nathael Gozlan , Nicolas Juillet

Some optimization or equilibrium problems involving somehow the concept of optimal transport are presented in these notes, mainly devoted to applications to economic and game theory settings. A variant model of transport, taking into…

Classical Analysis and ODEs · Mathematics 2010-09-21 Filippo Santambrogio

For a functional defined on the class of closed one-dimensional connected subsets of ${\mathbb R}^n$ we consider the corresponding minimization problem and we give suitable first order necessary conditions of optimality. The cases studied…

Optimization and Control · Mathematics 2014-01-03 Giuseppe Buttazzo , Edoardo Mainini , Eugene Stepanov