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A Milstein-type method is proposed for some highly non-linear non-autonomous time-changed stochastic differential equations (SDEs). The spatial variables in the coefficients of the time-changed SDEs satisfy the super-linear growth condition…

Numerical Analysis · Mathematics 2023-08-29 Wei Liu , Ruoxue Wu , Ruchun Zuo

We propose an explicit drift-randomised Milstein scheme for both McKean--Vlasov stochastic differential equations and associated high-dimensional interacting particle systems with common noise. By using a drift-randomisation step in space…

Probability · Mathematics 2023-06-19 Sani Biswas , Chaman Kumar , Neelima , Gonçalo dos Reis , Christoph Reisinger

This article investigates the propagation of chaos property for weakly interacting mild solutions to semilinear stochastic partial differential equations whose coefficients might not satisfy Lipschitz conditions. Furthermore, we derive…

Probability · Mathematics 2023-07-05 David Criens

We propose a particle system of diffusion processes coupled through a chain-like network structure described by an infinite-dimensional, nonlinear stochastic differential equation of McKean-Vlasov type. It has both (i) a local chain…

Probability · Mathematics 2019-07-18 Nils Detering , Jean-Pierre Fouque , Tomoyuki Ichiba

Here we present stochastic differential equations (SDEs) on a memristor crossbar, where the source of gaussian noise is derived from the random conductance due to ion drift in the devices during programming. We examine the effects of line…

Emerging Technologies · Computer Science 2022-02-04 Louis Primeau , Amirali Amirsoleimani , Roman Genov

In this paper, we establish the Stroock-Varadhan type support theorems for stochastic differential equations (SDEs) under Lyapunov conditions, which significantly improve the existing results in the literature where the coefficients of the…

Probability · Mathematics 2024-03-05 Qi Li , Jianliang Zhai , Tusheng Zhang

Stochastic differential equations (SDEs) provide a natural framework for modelling intrinsic stochasticity inherent in many continuous-time physical processes. When such processes are observed in multiple individuals or experimental units,…

Computation · Statistics 2016-05-19 Gavin A. Whitaker , Andrew Golightly , Richard J. Boys , Chris Sherlock

We study geometric stochastic differential equations (SDEs) and their approximations on Riemannian manifolds. In particular, we introduce a simple new construction of geometric SDEs, using which with bounded curvature. In particular, we…

Probability · Mathematics 2023-11-22 Xiang Cheng , Jingzhao Zhang , Suvrit Sra

The purpose of this paper is to study some properties of solutions to one dimensional as well as multidimensional stochastic differential equations (SDEs in short) with super-linear growth conditions on the coefficients. Taking inspiration…

Probability · Mathematics 2015-02-18 Khaled Bahlali , Antoine Hakassou , Youssef Ouknine

The combination of Monte Carlo methods and deep learning has recently led to efficient algorithms for solving partial differential equations (PDEs) in high dimensions. Related learning problems are often stated as variational formulations…

Machine Learning · Computer Science 2022-08-08 Lorenz Richter , Julius Berner

The Stochastic Partial Differential Equation (SPDE) approach, now commonly used in spatial statistics to construct Gaussian random fields, is revisited from a mechanistic perspective based on the movement of microscopic particles, thereby…

Methodology · Statistics 2021-11-11 Lionel Roques , Denis Allard , Samuel Soubeyrand

In this paper, we investigate a class of mean reflected McKean-Vlasov stochastic differential equation, which extends the equation proposed by \cite{briand2020particles} by allowing the solution's distribution to not only constrain its…

Probability · Mathematics 2024-11-21 Shaopeng Hong , Sheng Xiao

We propose a new algorithm to approach weakly the solution of a McKean-Vlasov SDE. Based on the cubature method of Lyons and Victoir 2004, the algorithm is deterministic differing from the the usual methods based on interacting particles.…

Probability · Mathematics 2019-04-22 Paul-Eric Chaudru de Raynal , Camilo Garcia Trillos

We establish the existence of solutions to common noise McKean-Vlasov martingale problems for coefficients with low regularity. Our approach is able to handle the key challenge posed by drift coefficients that are discontinuous with respect…

Probability · Mathematics 2025-09-01 Robert Alexander Crowell

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

Stochastic differential equations (SDEs) are popular tools to analyse time series data in many areas, such as mathematical finance, physics, and biology. They provide a mechanistic description of the phenomeon of interest, and their…

Methodology · Statistics 2021-02-01 Théo Michelot , Richard Glennie , Catriona Harris , Len Thomas

We present a Lyapunov type approach to the problem of existence and uniqueness of general law-dependent stochastic differential equations. In the existing literature most results concerning existence and uniqueness are obtained under…

Probability · Mathematics 2019-11-19 Sima Mehri , Wilhelm Stannat

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

This work is concerned with the existence and uniqueness of generalized (mild or distributional) solutions to (possibly degenerate) Fokker-Planck equations $\rho_t-\Delta\beta(\rho)+{\rm div}(Db(\rho)\rho)=0$ in…

Analysis of PDEs · Mathematics 2023-03-01 Viorel Barbu , Michael Röckner

We consider conditional McKean-Vlasov stochastic differential equations (SDEs), such as the ones arising in the large-system limit of mean field games and particle systems with mean field interactions when common noise is present. The…

Probability · Mathematics 2020-04-02 Daniel Lacker , Mykhaylo Shkolnikov , Jiacheng Zhang