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Variational problems that involve Wasserstein distances have been recently proposed to summarize and learn from probability measures. Despite being conceptually simple, such problems are computationally challenging because they involve…

Machine Learning · Statistics 2015-08-26 Marco Cuturi , Gabriel Peyré

In this paper we have constructed an approximation for the Harris flow and the Arratia flow using a sequence of independent stationary Gaussian processes as a perturbation. We have established what should be the relationship between the…

Probability · Mathematics 2011-05-23 Iryna Nishchenko

We propose a new minimum-distance estimator for linear random coefficient models. This estimator integrates the recently advanced sliced Wasserstein distance with the nearest neighbor methods, both of which enhance computational efficiency.…

Statistics Theory · Mathematics 2025-04-25 Keunwoo Lim , Ting Ye , Fang Han

We study existence of probability measure valued jump-diffusions described by martingale problems. We develop a simple device that allows us to embed Wasserstein spaces and other similar spaces of probability measures into locally compact…

Probability · Mathematics 2020-12-03 Martin Larsson , Sara Svaluto-Ferro

In this work we study systems consisting of a group of moving particles. In such systems, often some important parameters are unknown and have to be estimated from observed data. Such parameter estimation problems can often be solved via a…

Applications · Statistics 2023-07-11 Chen Cheng , Linjie Wen , Jinglai Li

We derive a relation between the dissipation in a stochastic dynamics and the Wasserstein distance. We show that the minimal amount of dissipation required to transform an initial state to a final state during a diffusion process is given…

Statistical Mechanics · Physics 2019-12-19 Andreas Dechant , Yohei Sakurai

The sliced-Wasserstein flow is an evolution equation where a probability density evolves in time, advected by a velocity field computed as the average among directions in the unit sphere of the optimal transport displacements from its 1D…

Optimization and Control · Mathematics 2024-05-13 Giacomo Cozzi , Filippo Santambogio

We prove the existence of a diffusion process whose invariant measure is the fractional polymer or Edwards measure for fractional Brownian motion in dimension $d\in\mathbb{N}$ with Hurst parameter $H\in(0,1)$ fulfilling $dH < 1$. The…

Mathematical Physics · Physics 2019-07-09 Wolfgang Bock , Torben Fattler , Ludwig Streit

In this paper we introduce some recent progresses on the convergence rate in Wasserstein distance for empirical measures of Markov processes. For diffusion processes on compact manifolds possibly with reflecting or killing boundary…

Probability · Mathematics 2025-07-22 Feng-Yu Wang

We consider Brownian particles immersed in the fluid which flow is turbulent. We study the limit where the particles' inertia is weak and their velocity relaxes fast to the velocity of the flow. The trajectories of the particles in this…

Chaotic Dynamics · Physics 2011-10-25 Itzhak Fouxon , Eugene Mednikov

We study the Wasserstein gradient flow of semi-discrete energies in the space of probability measures, that is functionals depending on two measures-one being an absolutely continuous density and the other an atomic measure. These energies…

Analysis of PDEs · Mathematics 2026-03-05 Joao Miguel Machado

We propose a transfer principle to study the adapted 2-Wasserstein distance between stochastic processes. First, we obtain an explicit formula for the distance between real-valued mean-square continuous Gaussian processes by introducing the…

Probability · Mathematics 2025-06-09 Yifan Jiang , Fang Rui Lim

We propose a variational finite volume scheme to approximate the solutions to Wasserstein gradient flows. The time discretization is based on an implicit linearization of the Wasserstein distance expressed thanks to Benamou-Brenier formula,…

Numerical Analysis · Mathematics 2019-07-22 Clément Cancès , Thomas O. Gallouët , Gabriele Todeschi

The convergence rate in Wasserstein distance is estimated for empirical measures of ergodic Markov processes, and the estimate can be sharp in some specific situations. The main result is applied to subordinations of typical models excluded…

Probability · Mathematics 2024-08-14 Feng-Yu Wang

Variational inference, such as the mean-field (MF) approximation, requires certain conjugacy structures for efficient computation. These can impose unnecessary restrictions on the viable prior distribution family and further constraints on…

Statistics Theory · Mathematics 2023-09-11 Rentian Yao , Yun Yang

Brownian motion has served as a pilot of studies in diffusion and other transport phenomena for over a century. The foundation of Brownian motion, laid by Einstein, has generally been accepted to be far from being complete since the late…

Statistical Mechanics · Physics 2017-06-06 Hanqing Zhao , Hong Zhao

We demonstrate experimentally that a Brownian particle is subject to inertial effects at long time scales. By using a blinking optical tweezers, we extend the range of previous experiments by several orders of magnitude up to a few seconds.…

Statistical Mechanics · Physics 2015-06-18 Giuseppe Pesce , Giorgio Volpe , Giovanni Volpe , Antonio Sasso

We present a simple approach to study the one-dimensional pressureless Euler system via adhesion dynamics in the Wasserstein space of probability measures with finite quadratic moments. Starting from a discrete system of a finite number of…

Analysis of PDEs · Mathematics 2014-09-16 Luca Natile , Giuseppe Savaré

In this paper we consider a stepping-stone model on a circle with circular Brownian migration. We first point out a connection between Arratia flow and the marginal distribution of this model. We then give a new representation for the…

Probability · Mathematics 2007-05-23 Xiaowen Zhou

We investigate analytically a microfluidic device consisting of a tube with non-uniform but spatially periodic diameter, where a fluid driven back and forth by a pump carries colloidal particles. Although the net flow of the fluid is zero,…

Soft Condensed Matter · Physics 2017-07-11 Frantisek Slanina