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The present article investigates the convergence of a class of space-time discretization schemes for the Cauchy problem for linear parabolic stochastic partial differential equations (SPDEs) defined on the whole space. Sufficient conditions…

Probability · Mathematics 2012-10-04 Eric Joseph Hall

This paper is concerned with solution in H\"{o}lder spaces of the Cauchy problem for linear and semi-linear backward stochastic partial differential equations (BSPDEs) of super-parabolic type. The pair of unknown variables are viewed as…

Analysis of PDEs · Mathematics 2016-02-10 Shanjian Tang , Wenning Wei

We give sufficient conditions under which the convergence of finite difference approximations in the space variable of the solution to the Cauchy problem for linear stochastic PDEs of parabolic type can be accelerated to any given order of…

Probability · Mathematics 2010-06-09 Istvan Gyongy , Nicolai Krylov

This paper investigates a numerical probabilistic method for the solution of some semilinear stochastic partial differential equations (SPDEs in short). The numerical scheme is based on discrete time approximation for solutions of systems…

Probability · Mathematics 2015-09-21 Achref Bachouch , Mohamed Anis Ben Lasmar , Anis Matoussi , Mohamed Mnif

A general class of KdV-type wave equations regularized with a convolution-type nonlocality in space is considered. The class differs from the class of the nonlinear nonlocal unidirectional wave equations previously studied by the addition…

Numerical Analysis · Mathematics 2022-09-16 H. A. Erbay , S. Erbay , A. Erkip

We construct and study a time--semidiscretization scheme for the Cauchy problem associated with a linear homogeneous differential equation with the Caputo fractional time derivative of order $\alpha\in(0,1)$ and a spatial sectorial operator…

Numerical Analysis · Mathematics 2017-12-11 M. M. Kokurin

Solving partial differential equations (PDEs) within the framework of probabilistic numerics offers a principled approach to quantifying epistemic uncertainty arising from discretization. By leveraging Gaussian process regression and…

Machine Learning · Statistics 2025-08-18 Akshay Thakur , Sawan Kumar , Matthew Zahr , Souvik Chakraborty

A comprehensive convergence and stability analysis of some probabilistic numerical methods designed to solve Cauchy-type inverse problems is performed in this study. Such inverse problems aim at solving an elliptic partial differential…

Numerical Analysis · Mathematics 2025-08-12 Iulian Cîmpean , Andreea Grecu , Liviu Marin

We study the Cauchy problem for a scalar semilinear degenerate parabolic partial differential equation with stochastic forcing. In particular, we are concerned with the well-posedness in any space dimension. We adapt the notion of kinetic…

Analysis of PDEs · Mathematics 2012-02-10 Martina Hofmanova

The space mapping technique is used to efficiently solve complex optimization problems. It combines the accuracy of fine model simulations with the speed of coarse model optimizations to approximate the solution of the fine model…

Optimization and Control · Mathematics 2025-10-14 Sebastian Blauth

The paper establishes the strong convergence rates of a spatio-temporal full discretization of the stochastic wave equation with nonlinear damping in dimension one and two. We discretize the SPDE by applying a spectral Galerkin method in…

Numerical Analysis · Mathematics 2024-12-30 Meng Cai , David Cohen , Xiaojie Wang

Numerical approximation of a general class of nonlinear unidirectional wave equations with a convolution-type nonlocality in space is considered. A semi-discrete numerical method based on both a uniform space discretization and the discrete…

Numerical Analysis · Mathematics 2021-05-19 H. A. Erbay , S. Erbay , A. Erkip

Considering stochastic partial differential equations of parabolic type with random coefficients in vector-valued H\"older spaces, we obtain a sharp Schauder estimate. As an application, the existence and uniqueness of solution to the…

Analysis of PDEs · Mathematics 2015-09-17 Kai Du , Jiakun Liu

We develop and analyse numerical schemes for uncertainty quantification in neural field equations subject to random parametric data in the synaptic kernel, firing rate, external stimulus, and initial conditions. The schemes combine a…

Numerical Analysis · Mathematics 2025-05-27 Daniele Avitabile , Francesca Cavallini , Svetlana Dubinkina , Gabriel J. Lord

In this note we introduce a new approach to rough and stochastic partial differential equations (RPDEs and SPDEs): we consider general Banach spaces as state spaces and -- for the sake of simiplicity -- finite dimensional sources of noise,…

Probability · Mathematics 2009-08-21 Josef Teichmann

In this paper we propose a general methodology for solving a broad class of continuous, multifacility location problems, in any dimension and with $\ell_\tau$-norms proposing two different methodologies: 1) by a new second order cone mixed…

Optimization and Control · Mathematics 2014-10-21 Víctor Blanco , Justo Puerto , Safae El-Haj Ben-Ali

We study linear stochastic partial differential equations of parabolic type. We consider a new boundary value problem where a Cauchy condition is replaced by a prescribed average of the solution either over time and probabilistic space for…

Probability · Mathematics 2017-06-22 Nikolai Dokuchaev

We study the Cauchy problem for the quasi-geostrophic equations in a unit ball of the two dimensional space with the homogeneous Dirichlet boundary condition. We show the existence, the uniqueness of the strong solution in the framework of…

Analysis of PDEs · Mathematics 2021-09-17 Tsukasa Iwabuchi

In this article, we prove the convergence of a semi-discrete numerical method applied to a general class of nonlocal nonlinear wave equations where the nonlocality is introduced through the convolution operator in space. The most important…

Numerical Analysis · Mathematics 2020-08-04 H. A. Erbay , S. Erbay , A. Erkip

Stochastic partial differential equations (SPDEs) are the mathematical tool of choice for modelling spatiotemporal PDE-dynamics under the influence of randomness. Based on the notion of mild solution of an SPDE, we introduce a novel neural…

Machine Learning · Computer Science 2022-09-27 Cristopher Salvi , Maud Lemercier , Andris Gerasimovics
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