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Numerical solutions of stationary diffusion equations on the unit sphere with isotropic lognormal diffusion coefficients are considered. H\"older regularity in $L^p$ sense for isotropic Gaussian random fields is obtained and related to the…

Probability · Mathematics 2023-12-06 Lukas Herrmann , Annika Lang , Christoph Schwab

Inspired by the stochastic particle method, this paper establishes an easily implementable explicit numerical method for McKean-Vlasov stochastic differential equations (MV-SDEs) with superlinear growth coefficients. The paper establishes…

Probability · Mathematics 2025-12-25 Yuanping Cui , Xiaoyue Li , Yi Liu , Fengyu Wang

We study the Crank-Nicolson scheme for stochastic differential equations (SDEs) driven by multidimensional fractional Brownian motion $(B^{1}, \dots, B^{m})$ with Hurst parameter $H \in (\frac 12,1)$. It is well-known that for ordinary…

Probability · Mathematics 2017-09-07 Yaozhong Hu , Yanghui Liu , David Nualart

We solve multidimensional SDEs with distributional drift driven by symmetric, $\alpha$-stable L\'evy processes for $\alpha\in (1,2]$ by studying the associated (singular) martingale problem and by solving the Kolmogorov backward equation.…

Probability · Mathematics 2024-06-21 Helena Kremp , Nicolas Perkowski

We study stochastic differential equations(SDEs) with a small perturbation parameter. Under the dissipative condition on the drift coefficient and the local Lipschitz condition on the drift and diffusion coefficients we prove the existence…

Probability · Mathematics 2022-05-05 Luca Di Persio , Yuri Kondratiev , Viktorya Vardanyan

In this paper, we investigate the convergence order in probability of a novel ergodic numerical scheme for damped stochastic nonlinear Schr\"{o}dinger equation with an additive noise. Theoretical analysis shows that our scheme is of order…

Numerical Analysis · Mathematics 2016-11-29 Jialin Hong , Lihai Ji , Xu Wang

This paper develops methods for numerically solving stochastic delay-differential equations (SDDEs) with multiple fixed delays that do not align with a uniform time mesh. We focus on numerical schemes of strong convergence orders $1/2$ and…

Numerical Analysis · Mathematics 2026-05-05 Mitchell T. Griggs , Kevin Burrage , Pamela M. Burrage

Existing fundamental theorems for mean-square convergence of numerical methods for stochastic differential equations (SDEs) require globally or one-sided Lipschitz continuous coefficients, while strong convergence results under merely local…

Probability · Mathematics 2026-02-16 Pierre Étoré , Anna Melnykova , Irene Tubikanec

Since it is difficult to implement implicit schemes on the infinite-dimensional space, we aim to develop the explicit numerical method for approximating super-linear stochastic functional differential equations (SFDEs). Precisely, borrowing…

Numerical Analysis · Mathematics 2022-08-23 Xiaoyue Li , Xuerong Mao , Guoting Song

In this article we investigate the numerical solution of a scalar semilinear stochastic delay differential equation (SDDE) where the linear instantaneous feedback and nonlinear delayed feedback terms are perturbed by a pair of standard…

Numerical Analysis · Mathematics 2026-03-24 Cónall Kelly , Wenshi Tang

In this article, we study a numerical scheme for stochastic differential equations driven by fractional Brownian motion with Hurst parameter H in (1/4; 1/2). Towards this end, we apply Doss-Sussmann representation of the solution and an…

Probability · Mathematics 2019-04-08 H. Araya , J. A. León , S. Torres

We consider non-parametric Bayesian estimation of the drift coefficient of a one-dimensional stochastic differential equation from discrete-time observations on the solution of this equation. Under suitable regularity conditions that are…

Statistics Theory · Mathematics 2014-07-15 Shota Gugushvili , Peter Spreij

We study the weak convergence of a generic tamed Euler-Maruyama scheme for kinetic stochastic differential equations (SDEs) with integrable drifts. We show that the marginal density of the considered scheme converges at rate 1/2 to the…

Probability · Mathematics 2026-03-25 Zimo Hao , Khoa Lê , Chengcheng Ling

This paper establishes a quantitative stability theory for one-dimensional stochastic differential equations (SDEs) with non-zero drift, driven by a symmetric $\alpha$-stable process for $\alpha\in(1,2)$. Our work generalizes the classical…

Probability · Mathematics 2026-04-21 Takuya Nakagawa

This paper focuses on the numerical scheme for multiple-delay stochastic differential equations with partially H\"older continuous drifts and locally H\"older continuous diffusion coefficients. To handle with the superlinear terms in…

Numerical Analysis · Mathematics 2024-03-19 Zhuoqi Liu , Zhaohang Wang , Siying Sun , Shuaibin Gao

We establish the well-posedness of SDE with the additive noise when a singular drift belongs to the critical spaces. We prove that if the drift belongs to the Orlicz-critical space $L^{q,1}([0,T],L^p_x)$ for $p,q\in (1,\infty)$ satisfying…

Probability · Mathematics 2018-10-08 Kyeongsik Nam

We consider numerical schemes for computing the linear response of steady-state averages of stochastic dynamics with respect to a perturbation of the drift part of the stochastic differential equation. The schemes are based on Girsanov's…

Numerical Analysis · Mathematics 2019-12-18 Petr Plechac , Gabriel Stoltz , Ting Wang

We study the numerical approximation of the stochastic heat equation with a distributional reaction term. Under a condition on the Besov regularity of the reaction term, it was proven recently that a strong solution exists and is unique in…

Probability · Mathematics 2024-07-12 Ludovic Goudenège , El Mehdi Haress , Alexandre Richard

The existence and uniqueness of the stationary distribution of the numerical solution generated by the stochastic theta method is studied. When the parameter theta takes different values, the requirements on the drift and diffusion…

Numerical Analysis · Mathematics 2018-01-30 Yanan Jiang , Wei Liu , Lihui Weng

We study the dynamics of a continuous-time model of the Stochastic Gradient Descent (SGD) for the least-square problem. Indeed, pursuing the work of Li et al. (2019), we analyze Stochastic Differential Equations (SDEs) that model SGD either…

Machine Learning · Computer Science 2024-07-03 Adrien Schertzer , Loucas Pillaud-Vivien