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We develop a mean-field theory for large, non-exchangeable particle (agent) systems where the states and interaction weights co-evolve in a coupled system of SDEs. A first main result is the establishment of the propagation of…

Probability · Mathematics 2025-12-30 Datong Zhou

In this work, we are concerned with existence and uniqueness of invariant measures for path-dependent random diffusions and their time discretizations. The random diffusion here means a diffusion process living in a random environment…

Probability · Mathematics 2017-06-20 Jianhai Bao , Jinghai Shao , Chenggui Yuan

The aim of this paper is to obtain convergence in mean in the uniform topology of piecewise linear approximations of Stochastic Differential Equations (SDEs) with $C^1$ drift and $C^2$ diffusion coefficients with uniformly bounded…

Probability · Mathematics 2025-03-13 Sahani Pathiraja

We study mean field stochastic differential equations with a diffusion coefficient that depends on the distribution function of the unknown process in a discontinuous manner, which is a type of distribution dependent regime switching. To…

Probability · Mathematics 2025-03-28 Jani Nykänen

This paper studies McKean-Vlasov stochastic differential equations (MVSDEs) whose drift coefficients grow super-linearly in both state variables and measure arguments, and whose diffusion coefficients exhibit super-linear growth in the…

Probability · Mathematics 2026-02-09 Zhuoqi Liu , Qian Guo , Shuaibin Gao , Chenggui Yuan

Asymptotic couplings by reflection are constructed for a class of non-linear monotone SPDES (stochastic partial differential equations). As applications, the gradient/H\"older estimates as well as the exponential convergence are derived for…

Probability · Mathematics 2014-07-15 Feng-Yu Wang

This paper focuses on the invariant measure of McKean-Vlasov (MV) stochastic differential equations (SDEs) with common noise (wCN) whose coefficients depend on both the state and the measure. Using the existence of the unique solution of…

Probability · Mathematics 2025-09-23 Xing Chen , Xiaoyue Li , Chenggui Yuan

In this paper, concerning SDEs with H\"older continuous drifts, which are merely dissipative at infinity, and SDEs with piecewise continuous drifts, we investigate the strong law of large numbers and the central limit theorem for underlying…

Probability · Mathematics 2024-03-12 Jianhai Bao , Jiaqing Hao

In this paper, we study a two-species model in the form of a coupled system of nonlinear stochastic differential equations (SDEs) that arises from a variety of applications such as aggregation of biological cells and pedestrian movements.…

Analysis of PDEs · Mathematics 2018-10-03 Manh Hong Duong , Julian Tugaut

In this paper, we investigate the exponential ergodicity in a Wasserstein-type distance for a damping Hamiltonian dynamics with state-dependent and non-local collisions, which indeed is a special case of piecewise deterministic Markov…

Probability · Mathematics 2022-04-05 Jianhai Bao , Jian Wang

We study a nonlocal adhesion model for two interacting tumor cell phenotypes, combining diffusion, pairwise interactions, and random phenotypic switching. The system admits a microscopic diffusion--jump particle description whose mean-field…

Analysis of PDEs · Mathematics 2026-03-16 Myeongju Chae , Young-Pil Choi

McKean-Vlasov stochastic differential equations (MV-SDEs) provide a mathematical description of the behavior of an infinite number of interacting particles by imposing a dependence on the particle density. As such, we study the influence of…

Machine Learning · Computer Science 2024-04-16 Haoming Yang , Ali Hasan , Yuting Ng , Vahid Tarokh

Pathwise uniqueness for multi-dimensional stochastic McKean--Vlasov equation is established under moderate regularity conditions on the drift and diffusion coefficients. Both drift and diffusion depend on the marginal measure of the…

Probability · Mathematics 2023-01-02 Alexander Veretennikov

Under Lyapunov and monotone conditions, the exponential ergodicity in the induced Wasserstein quasi-distance is proved for a class of fully non-dissipative McKean-Vlasov SDEs, which strengthen some recent results established under…

Probability · Mathematics 2021-06-24 Feng-Yu Wang

Applying Zvonkin's transform, the exponential convergence in Wasserstein distance for a class of functional SDEs with H\"older continuous drift is obtained. This combining with log-Harnack inequality implies the same convergence in the…

Probability · Mathematics 2018-11-06 Xing Huang

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 consider the problem of parameter estimation for a stochastic McKean-Vlasov equation, and the associated system of weakly interacting particles. We study two cases: one in which we observe multiple independent trajectories of the…

Statistics Theory · Mathematics 2022-11-28 Louis Sharrock , Nikolas Kantas , Panos Parpas , Grigorios A. Pavliotis

In this paper, we numerically study the stochastic and the deterministic occasional uncoupling methods of effecting identical synchronized states in low dimensional, dissipative, diffusively coupled, chaotic flows that are otherwise not…

Adaptation and Self-Organizing Systems · Physics 2020-07-07 Anupam Ghosh , Sagar Chakraborty

Based on the assumption of the existence and uniqueness of the invariant measure for McKean-Vlasov stochastic differential equations (MV-SDEs), a self-interacting process that depends only on the current and historical information of the…

Probability · Mathematics 2024-04-09 Cui Yuanping , Li Xiaoyue

Let P2(Rd) be the space of probability measures on Rd with finite second moment. The path independence of additive functionals of McKean-Vlasov SDEs is characterized by PDEs on the product space Rd*P2(Rd) equipped with the usual derivative…

Probability · Mathematics 2018-06-07 Panpan Ren , Feng-Yu Wang