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We propose a new method to estimate Wasserstein distances and optimal transport plans between two probability distributions from samples in high dimension. Unlike plug-in rules that simply replace the true distributions by their empirical…

We consider Monge-Kantorovich optimal transport problems on $\mathbb{R}^d$, $d\ge 1$, with a convex cost function given by the cumulant generating function of a probability measure. Examples include the Wasserstein-2 transport whose cost…

Probability · Mathematics 2017-08-29 Soumik Pal

We consider a system of particles which interact through a jump process. The jump intensities are functions of the proximity rank of the particles, a type of interaction referred to as topological in the literature. Such interactions have…

Probability · Mathematics 2022-12-20 Pierre Degond , Mario Pulvirenti , Stefano Rossi

The presentation covers prerequisite results from Topology and Measure Theory. This is then followed by an introduction into couplings and basic definitions for optimal transport. The Kantrorovich problem is then introduced and an existence…

Probability · Mathematics 2020-10-12 Austin Vandegriffe

We are interested in martingale rearrangement couplings. As introduced by Wiesel [37] in order to prove the stability of Martingale Optimal Transport problems, these are projections in adapted Wasserstein distance of couplings between two…

Probability · Mathematics 2021-02-01 Benjamin Jourdain , William Margheriti

We investigate the problem of quantifying contraction coefficients of Markov transition kernels in Kantorovich ($L^1$ Wasserstein) distances. For diffusion processes, relatively precise quantitative bounds on contraction rates have recently…

Probability · Mathematics 2018-08-22 Andreas Eberle , Mateusz B. Majka

The method of 'coupling from the past' permits exact sampling from the invariant distribution of a Markov chain on a finite state space. The coupling is successful whenever the stochastic dynamics are such that there is coalescence of all…

Probability · Mathematics 2025-10-17 Geoffrey R. Grimmett , Mark Holmes

An aperiodic and irreducible Markov chain on a finite state space converges to its stationary distribution. When convergence to equilibrium is measured by total variation distance, there exists an optimal coupling and a maximal coupling…

Probability · Mathematics 2015-04-01 Agnes Coquio

This paper integrates two strands of the literature on stability of general state Markov chains: conventional, total variation based results and more recent order-theoretic results. First we introduce a complete metric over Borel…

Probability · Mathematics 2024-10-02 Takashi Kamihigashi , John Stachurski

The dynamical systems found in Nature are rarely isolated. Instead they interact and influence each other. The coupling functions that connect them contain detailed information about the functional mechanisms underlying the interactions and…

Adaptation and Self-Organizing Systems · Physics 2017-11-15 Tomislav Stankovski , Tiago Pereira , Peter V. E. McClintock , Aneta Stefanovska

A coupling method is developed for univariate extreme value theory , providing an alternative to the use of the tail empirical/quantile processes. Emphasizing the Peak-over-Threshold approach that approximates the distribution above high…

Statistics Theory · Mathematics 2019-12-09 Benjamin Bobbia , Clément Dombry , Davit Varron

Constructing accurate, flexible, and efficient parametrizations is one of the great challenges in the numerical modelling of geophysical fluids. We consider here the simple yet paradigmatic case of a Lorenz 84 model forced by a Lorenz 63…

Statistical Mechanics · Physics 2020-11-16 Gabriele Vissio , Valerio Lucarini

We consider two weakly coupled systems and adopt a perturbative approach based on the Ruelle response theory to study their interaction. We propose a systematic way to parametrize the effect of the coupling as a function of only the…

Statistical Mechanics · Physics 2012-08-16 Jeroen Wouters , Valerio Lucarini

We provide a coupling proof of Doob's theorem which says that the transition probabilities of a regular Markov process which has an invariant probability measure $\mu$ converge to $\mu$ in the total variation distance. In addition we show…

Probability · Mathematics 2014-08-01 Alexei Kulik , Michael Scheutzow

We introduce a unified framework to estimate the convergence of Markov chains to equilibrium in Wasserstein distance. The framework can provide convergence bounds with rates ranging from polynomial to exponential, all derived from a…

Probability · Mathematics 2025-06-09 Yanlin Qu , Jose Blanchet , Peter Glynn

We develop two generalizations of contraction theory, namely, semi-contraction and weak-contraction theory. First, using the notion of semi-norm, we propose a geometric framework for semi-contraction theory. We introduce matrix…

Systems and Control · Electrical Eng. & Systems 2020-10-06 Saber Jafarpour , Pedro Cisneros-Velarde , Francesco Bullo

We show continuity of the martingale optimal transport optimisation problem as a functional of its marginals. This is achieved via an estimate on the projection in the nested/causal Wasserstein distance of an arbitrary coupling on to the…

Probability · Mathematics 2022-06-22 Johannes Wiesel

This work investigates several aspects related to quantitative stability in optimal transport, as well as uniqueness of the dual transport problem. Our main contributions are as follows. Chapter 1: Observations regarding the quantitative…

Functional Analysis · Mathematics 2025-10-22 William Ford

We completely characterise the optimal solutions for the three-marginal optimal transport problem - introduced in [K. Bolbotowski, G. Bouchitt\'e, Kantorovich-Rubinstein duality theory for the Hessian, 2024, preprint], and whose relaxation…

Optimization and Control · Mathematics 2025-02-14 Krzysztof J. Ciosmak

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