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We provide an analysis of the squared Wasserstein-2 ($W_2$) distance between two probability distributions associated with two stochastic differential equations (SDEs). Based on this analysis, we propose the use of a squared $W_2$…

Probability · Mathematics 2024-01-23 Mingtao Xia , Xiangting Li , Qijing Shen , Tom Chou

The exponential ergodicity of partially dissipative McKean-Vlasov SDEs in the \(L^1\)-Wasserstein distance has been extensively studied using asymptotic reflection coupling. However, the reflection coupling method is not applicable for the…

Probability · Mathematics 2025-11-13 Xing Huang , Eva Kopfer , Panpan Ren

The exponential contraction in $L^1$-Wasserstein distance and exponential convergence in $L^q$-Wasserstein distance ($q\geq 1$) are considered for stochastic differential equations with irregular drift. When the irregular drift drift is…

Probability · Mathematics 2024-04-22 Shao-Qin Zhang

Monge-Kantorovich distances, otherwise known as Wasserstein distances, have received a growing attention in statistics and machine learning as a powerful discrepancy measure for probability distributions. In this paper, we focus on…

Machine Learning · Statistics 2018-01-30 François Bachoc , Fabrice Gamboa , Jean-Michel Loubes , Nil Venet

Wasserstein distances are metrics on probability distributions inspired by the problem of optimal mass transportation. Roughly speaking, they measure the minimal effort required to reconfigure the probability mass of one distribution in…

Methodology · Statistics 2019-04-10 Victor M. Panaretos , Yoav Zemel

The well-posedness is established for McKean-Vlasov SDEs driven by $\alpha$-stable noises ($1<\alpha<2$). In this model, the drift is H\"{o}lder continuous in space variable and Lipschitz continuous in distribution variable with respect to…

Probability · Mathematics 2023-06-21 Chang-Song Deng , Xing Huang

The following type exponential convergence is proved for (non-degenerate or degenerate) McKean-Vlasov SDEs: $$W_2(\mu_t,\mu_\infty)^2 +{\rm Ent}(\mu_t|\mu_\infty)\le c {\rm e}^{-\lambda t} \min\big\{W_2(\mu_0, \mu_\infty)^2,{\rm…

Probability · Mathematics 2024-10-01 Panpan Ren , Feng-Yu Wang

Via constructing an asymptotic coupling by reflection, in this paper we establish uniform-in-time estimates on probability distances for mean-field type SDEs, where the drift terms under consideration are dissipative merely in the long…

Probability · Mathematics 2024-09-26 Jianhai Bao , Jiaqing Hao

Coupling by reflection mixed with synchronous coupling is constructed for a class of stochastic differential equations (SDEs) driven by L\'{e}vy noises. As an application, we establish the exponential contractivity of the associated…

Statistics Theory · Mathematics 2016-03-18 Jian Wang

In this note, under a weak monotonicity and a weak coercivity, we address strong well-posedness of McKean-Vlasov stochastic differential equations (SDEs) driven by L\'{e}vy jump processes, where the coefficients are Lipschitz continuous…

Probability · Mathematics 2024-12-03 Jianhai Bao , Yao Liu , Jian Wang

We study the reknown deconvolution problem of recovering a distribution function from independent replicates (signal) additively contaminated with random errors (noise), whose distribution is known. We investigate whether a Bayesian…

Statistics Theory · Mathematics 2021-11-15 Judith Rousseau , Catia Scricciolo

This paper proves that, under a monotonicity condition, the invariant probability measure of a McKean--Vlasov process can be approximated by weighted empirical measures of some processes including itself. These processes are described by…

Probability · Mathematics 2021-12-30 Kai Du , Yifan Jiang , Jinfeng Li

We study a class of McKean-Vlasov type stochastic differential equations (SDEs) which arise from the random vortex dynamics and other physics models. By introducing a new approach we resolve the existence and uniqueness of both the weak and…

Probability · Mathematics 2021-04-13 Zhongmin Qian , Yuhan Yao

We establish quantitative comparisons between classical distances for probability distributions belonging to the class of convex probability measures. Distances include total variation distance, Wasserstein distance, Kullback-Leibler…

Probability · Mathematics 2021-12-17 Arnaud Marsiglietti , Puja Pandey

We design a fully implementable scheme to compute the invariant distribution of ergodic McKean-Vlasov SDE satisfying a uniform confluence property. Under natural conditions, we prove various convergence results notably we obtain rates for…

Probability · Mathematics 2025-02-13 Jean-François Chassagneux , Gilles Pagès

The existence and uniqueness of stationary distributions and the exponential convergence in $L^p$-Wasserstein distance are derived for distribution dependent SDEs from associated decoupled equations. To establish the exponential…

Probability · Mathematics 2022-03-14 Shao-Qin Zhang

The first goal of this note is to prove the strong well-posedness of McKean-Vlasov SDEs driven by L{\'e}vy processes on $\mathbb{R}^d$ having a finite moment of order $\beta \in [1,2]$ and under standard Lipschitz assumptions on the…

Probability · Mathematics 2025-04-24 Thomas Cavallazzi

This article is a continuation of our first work \cite{chaudruraynal:frikha}. We here establish some new quantitative estimates for propagation of chaos of non-linear stochastic differential equations in the sense of McKean-Vlasov. We…

Analysis of PDEs · Mathematics 2021-08-26 Noufel Frikha , Paul-Eric Chaudru de Raynal

We consider the fully-coupled McKean-Vlasov equation with multi-time-scale potentials, and all the coefficients depend on the distributions of both the slow component and the fast motion. By studying the smoothness of the solution of the…

Probability · Mathematics 2022-04-28 Yun Li , Fuke Wu , Longjie Xie

In this paper, existence and uniqueness are proved for path-dependent McKean-Vlasov type SDEs with integrability conditions. Gradient estimates and Harnack type inequalities are derived in the case that the coefficients are Dini continuous…

Probability · Mathematics 2019-02-26 Xing Huang