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We study diffusion processes corresponding to infinite dimensional semilinear stochastic differential equations with local Lipschitz drift term and an arbitrary Lipschitz diffusion coefficient. We prove tightness and the Feller property of…

Analysis of PDEs · Mathematics 2021-05-28 A. Es-Sarhir , M. Scheutzow , J. M. Tölle , O. van Gaans

We consider a stochastic partial differential equation (SPDE) model for chemorepulsion, with non-linear sensitivity on the one-dimensional torus. We show that for any suitable initial data there exists a pathwise unique, global solution to…

Probability · Mathematics 2023-08-22 Ilya Chevyrev , Ben Hambly , Avi Mayorcas

We consider stochastic semilinear partial differential equations with Lipschitz nonlinear terms. We prove existence and uniqueness of an invariant measure and the existence of a solution for the corresponding Kolmogorov equation in the…

Probability · Mathematics 2007-05-23 Luigi Manca

A series of recent articles introduced a method to construct stochastic partial differential equations (SPDEs) which are invariant with respect to the distribution of a given conditioned diffusion. These works are restricted to the case of…

Probability · Mathematics 2011-04-08 Martin Hairer , Andrew M. Stuart , Jochen Voss

We prove existence of invariant measures for the Markovian semigroup generated by the solution to a parabolic semilinear stochastic PDE whose nonlinear drift term satisfies only a kind of symmetry condition on its behavior at infinity, but…

Analysis of PDEs · Mathematics 2020-04-21 Carlo Marinelli , Luca Scarpa

We consider a general piecewise deterministic Markov process (PDMP) $X=\{X_t\}_{t\geqslant 0}$ with measure-valued generator $\mathcal{A}$, for which the conditional distribution function of the inter-occurrence time is not necessarily…

Probability · Mathematics 2017-04-27 Zhaoyang Liu , Yuying Liu , Guoxin Liu

Let X be the mild solution to a semilinear stochastic partial differential equation. In this article, we develop methodology to sample from the infinite-dimensional diffusion bridge that arises from conditioning X on a linear transformation…

Probability · Mathematics 2025-03-18 Thorben Pieper-Sethmacher , Frank van der Meulen , Aad van der Vaart

We consider the perturbation of parabolic operators of the form $\partial_t+P(x,D)$ by large-amplitude highly oscillatory spatially dependent potentials modeled as Gaussian random fields. The amplitude of the potential is chosen so that the…

Mathematical Physics · Physics 2015-05-13 Guillaume Bal

We investigate the longtime behavior of stochastic partial differential equations (SPDEs) with differential operators that depend on time and the underlying probability space. In particular, we consider stochastic parabolic evolution…

Probability · Mathematics 2021-02-10 Christian Kuehn , Alexandra Neamtu , Stefanie Sonner

In this article we show that a finite dimensional stochastic differential equation driven by a L\'evy process can be formulated as a stochastic partial differential equation. We prove the existence and uniqueness of strong solutions of such…

Probability · Mathematics 2018-02-15 Suprio Bhar , Rajeev Bhaskaran , Barun Sarkar

We introduce a guided stochastic sampling method that augments sampling from diffusion models with physics-based guidance derived from partial differential equation (PDE) residuals and observational constraints, ensuring generated samples…

Machine Learning · Computer Science 2026-05-28 Andrew Millard , Fredrik Lindsten , Zheng Zhao

In this article we introduce and analyze a notion of mild solution for a class of non-autonomous parabolic stochastic partial differential equations defined on a bounded open subset $D\subset\mathbb{R}^{d}$ and driven by an…

Probability · Mathematics 2009-02-19 Marta Sanz-Solé , Pierre-A. Vuillermot

In this article, we solve the problem of the long time behaviour of transition probabilities of time-inhomogeneous Markov processes and give a unified approach to stochastic differential equations (SDEs) with periodic, quasi-periodic,…

Probability · Mathematics 2023-07-18 Chunrong Feng , Baoyou Qu , Huaizhong Zhao

In this paper we study a system of stochastic differential equations with dissipative nonlinearity which arise in certain neurobiology models. Besides proving existence, uniqueness and continuous dependence on the initial datum, we shall be…

Probability · Mathematics 2008-01-16 Stefano Bonaccorsi , Elisa Mastrogiacomo

This paper develops and analyzes a fully discrete finite element method for a class of semilinear stochastic partial differential equations (SPDEs) with multiplicative noise. The nonlinearity in the diffusion term of the SPDEs is assumed to…

Numerical Analysis · Mathematics 2018-11-22 Xiaobing Feng , Yukun Li , Yi Zhang

We establish necessary and sufficient conditions for stochastic invariance of closed subsets in Hilbert spaces for solutions to infinite-dimensional stochastic differential equations (SDEs) under mild assumptions on the coefficients. Our…

Probability · Mathematics 2026-02-24 Eduardo Abi Jaber , Stefan Tappe

We study a change point model based on a stochastic partial differential equation (SPDE) corresponding to the heat equation governed by the weighted Laplacian $\Delta_\vartheta = \nabla\vartheta\nabla$, where $\vartheta=\vartheta(x)$ is a…

Statistics Theory · Mathematics 2026-03-06 Markus Reiß , Claudia Strauch , Lukas Trottner

We study quasilinear parabolic stochastic partial differential equations with general multiplicative noise on a bounded domain in $\mathbb{R}^{d}$, with homogeneous Dirichlet boundary condition. We establish the existence and uniqueness of…

Probability · Mathematics 2023-10-26 Mengzi Xie

We stu\dd y a class of nonlinear stochastic partial differential equations with dissipative nonlinear drift, driven by L\'evy noise. Our work is divided in two parts. In the present part I we first define a Hilbert-Banach setting in which…

Probability · Mathematics 2013-12-10 Sergio Albeverio , Luca Di Persio , Elisa Mastrogiacomo , Boubaker Smii

In many applications, it is important to be able to sample paths of SDEs conditional on observations of various kinds. This paper studies SPDEs which solve such sampling problems. The SPDE may be viewed as an infinite-dimensional analogue…

Probability · Mathematics 2007-11-06 M. Hairer , A. M. Stuart , J. Voss
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