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We address the weak numerical solution of stochastic differential equations driven by independent Brownian motions (SDEs for short). This paper develops a new methodology to design adaptive strategies for determining automatically the…

Probability · Mathematics 2023-02-10 Carlos M. Mora , Juan Carlos Jimenez , Monica Selva

We propose a method for the approximation of solutions of PDEs with stochastic coefficients based on the direct, i.e., non-adapted, sampling of solutions. This sampling can be done by using any legacy code for the deterministic problem as a…

Numerical Analysis · Mathematics 2015-05-19 Alireza Doostan , Houman Owhadi

A novel efficient and high accuracy numerical method for the time-fractional differential equations (TFDEs) is proposed in this work. We show the equivalence between TFDEs and the integer-order extended parametric differential equations…

Numerical Analysis · Mathematics 2025-05-13 Peng Ding , Zhiping Mao

We propose a sparse grid stochastic collocation method for long-time simulations of stochastic differential equations (SDEs) driven by white noise. The method uses pre-determined sparse quadrature rules for the forcing term and constructs…

Numerical Analysis · Mathematics 2017-06-13 H. Cagan Ozen , Guillaume Bal

Pseudospectral approximation provides a means to approximate the dynamics of delay differential equations (DDE) by ordinary differential equations (ODE). This article develops a computer-aided algorithm to determine the distance between the…

Dynamical Systems · Mathematics 2024-05-14 Shane Kepley , Babette A. J. de Wolff

Stochastic differential equations (SDEs), which models uncertain phenomena as the time evolution of random variables, are exploited in various fields of natural and social sciences such as finance. Since SDEs rarely admit analytical…

Quantum Physics · Physics 2021-05-26 Kenji Kubo , Yuya O. Nakagawa , Suguru Endo , Shota Nagayama

Recently, it has been shown in [Hairer, M., Hutzenthaler, M., Jentzen, A., Loss of regularity for Kolmogorov equations, Ann. Probab. 43, 2 (2015), 468--527] that there exists a system of stochastic differential equations (SDE) on the time…

Probability · Mathematics 2016-09-27 Larisa Yaroslavtseva

In this paper we propose an all-in-one statement which includes existence, uniqueness, regularity, and numerical approximations of mild solutions for a class of stochastic partial differential equations (SPDEs) with non-globally monotone…

Probability · Mathematics 2024-12-20 Sara Mazzonetto , Diyora Salimova

We consider delay differential equations with a polynomially distributed delay. We derive an equivalent system of delay differential equations, which includes just two discrete delays. The stability of the equivalent system and its…

Numerical Analysis · Mathematics 2024-09-27 Roland Pulch

This work investigates numerical approximations of index 1 stochastic differential algebraic equations (SDAEs) with non-constant singular matrices under non-global Lipschitz conditions. Analyzing the strong convergence rates of numerical…

Numerical Analysis · Mathematics 2025-09-16 Lin Chen , Ziheng Chen , Jing Zhao

In this paper an alternative approach to solve uncertain Stochastic Differential Equation (SDE) is proposed. This uncertainty occurs due to the involved parameters in system and these are considered as Triangular Fuzzy Numbers (TFN). Here…

Numerical Analysis · Computer Science 2015-02-11 Sukanta Nayak , Snehashish Chakraverty

Neural Stochastic Differential Equations (NSDEs) model the drift and diffusion functions of a stochastic process as neural networks. While NSDEs are known to make accurate predictions, their uncertainty quantification properties have been…

Machine Learning · Computer Science 2022-09-13 Andreas Look , Melih Kandemir , Barbara Rakitsch , Jan Peters

We consider the problem of inferring latent stochastic differential equations (SDEs) with a time and memory cost that scales independently with the amount of data, the total length of the time series, and the stiffness of the approximate…

Machine Learning · Computer Science 2023-12-19 Kevin Course , Prasanth B. Nair

The exponential stability of numerical methods to stochastic differential equations (SDEs) has been widely studied. In contrast, there are relatively few works on polynomial stability of numerical methods. In this letter, we address the…

Probability · Mathematics 2014-04-25 Mohammud Foondun , Wei Liu , Xuerong Mao

We study a class of importance sampling methods for stochastic differential equations (SDEs). A small-noise analysis is performed, and the results suggest that a simple symmetrization procedure can significantly improve the performance of…

Numerical Analysis · Mathematics 2018-07-04 Andrew Leach , Kevin K. Lin , Matthias Morzfeld

In this article we propose a new explicit Euler-type approximation method for stochastic differential equations (SDEs). In this method, Brownian increments in the recursion of the Euler method are replaced by suitable bounded functions of…

Probability · Mathematics 2022-04-27 Martin Hutzenthaler , Kai Kisker

For Kolmogorov equations associated to finite dimensional stochastic differential equations (SDEs) in high dimension, a numerical method alternative to Monte Carlo simulations is proposed. The structure of the SDE is inspired by stochastic…

Probability · Mathematics 2020-10-01 Franco Flandoli , Dejun Luo , Cristiano Ricci

In this paper, we study numerical approximations for stochastic differential equations (SDEs) that use adaptive step sizes. In particular, we consider a general setting where decisions to reduce step sizes are allowed to depend on the…

Numerical Analysis · Mathematics 2025-12-10 James Foster , Andraž Jelinčič

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

For time-homogeneous stochastic differential equations (SDEs) it is enough to know that the coefficients are Lipschitz to conclude existence and uniqueness of a solution, as well as the existence of a strongly convergent numerical method…

Numerical Analysis · Mathematics 2018-12-04 Gunther Leobacher , Michaela Szölgyenyi
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