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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

In this work we consider a class of stochastic parabolic equations with singular space depending potential, random driving force and random initial condition. For the analysis of these equations we combine the chaos expansion method from…

Analysis of PDEs · Mathematics 2021-09-15 Snežana Gordić , Tijana Levajković , Ljubica Oparnica

This paper investigates the well-posedness and small-noise asymptotics of a class of stochastic partial differential equations defined on a bounded domain of $\mathbb{R}^d$, where the diffusion coefficient depends nonlinearly and…

Probability · Mathematics 2025-06-23 Sandra Cerrai , Giuseppina Guatteri , Gianmario Tessitore

Space-time fractional evolution equations are a powerful tool to model diffusion displaying space-time heterogeneity. We prove existence, uniqueness and stochastic representation of classical solutions for an extension of Caputo evolution…

Analysis of PDEs · Mathematics 2018-09-03 Lorenzo Toniazzi

In this paper we treat semilinear stochastic partial differential equations by two methods. First, we extend the framework of [BDR10] from a Hilbert space to a Gelfand triple and as an application we prove the existence of solutions for the…

Probability · Mathematics 2014-02-05 Michael Röckner , Rongchan Zhu , Xiangchan Zhu

We study stochastic parabolic and elliptic PDEs driven by purely spatial white noise. Even the simplest equations driven by this noise often do not have a square-integrable solution and must be solved in special weighted spaces. We…

Probability · Mathematics 2008-12-02 S. V. Lototsky , B. L. Rozovskii

This short survey article stems from recent progress on critical cases of stochastic evolution equations in variational formulation with additive, multiplicative or gradient noises. Typical examples appear as the limit cases of the…

Probability · Mathematics 2025-10-24 Ioana Ciotir , Dan Goreac , Jonas M. Tölle

We present a Bayesian non-parametric way of inferring stochastic differential equations for both regression tasks and continuous-time dynamical modelling. The work has high emphasis on the stochastic part of the differential equation, also…

Machine Learning · Statistics 2020-06-29 Martin Jørgensen , Marc Peter Deisenroth , Hugh Salimbeni

In this article, we study a class of semilinear stochastic partial differential equations driven by an additive space time white noise. We establish Harnack inequalities for the semigroup associated with the solution by using coupling…

Probability · Mathematics 2020-01-20 Rangrang Zhang

In this paper, we investigate the stochastic evolution equations (SEEs) driven by $\log$-Whittle-Mat$\acute{{\mathrm{e}}}$rn (W-M) random diffusion coefficient field and $Q$-Wiener multiplicative force noise. First, the well-posedness of…

Numerical Analysis · Mathematics 2022-07-05 X. Qi , M. Azaiez , C. Huang , C. Xu

We construct quasiparticles-like solutions to the one-dimensional Fisher-Kolmogorov-Petrovskii-Piskunov (FKPP) with a nonlocal nonlinearity using the method of semiclassically concentrated states in the weak diffusion approximation. Such…

Mathematical Physics · Physics 2024-03-07 A. E. Kulagin , A. V. Shapovalov

We prove a version of the Wong-Zakai theorem for one-dimensional parabolic nonlinear stochastic PDEs driven by space-time white noise. As a corollary, we obtain a detailed local description of solutions. Dedicated to the memory of Kiyosi…

Probability · Mathematics 2015-10-30 Martin Hairer , Étienne Pardoux

Stochastic differential equations (SDEs) and stochastic partial differential equations (SPDEs) are fundamental for modeling stochastic dynamics across the natural sciences and modern machine learning. Learning their solution operators with…

Machine Learning · Computer Science 2026-01-30 Dai Shi , Lequan Lin , Andi Han , Luke Thompson , José Miguel Hernández-Lobato , Zhiyong Wang , Junbin Gao

In this paper, we establish the existence and uniqueness of invariant measures for a class of semilinear stochastic partial differential equations driven by multiplicative noise on a bounded domain. The main results can be applied to SPDEs…

Probability · Mathematics 2018-12-12 Zhao Dong , Rangrang Zhang

Doubly nonlinear stochastic evolution equations are considered. Upon assuming the additive noise to be rough enough, we prove the existence of probabilistically weak solutions of Friedrichs type and study their uniqueness in law. This…

Probability · Mathematics 2025-07-24 Carlo Orrieri , Luca Scarpa , Ulisse Stefanelli

We study the wellposedness and pathwise regularity of semilinear non-autonomous parabolic evolution equations with boundary and interior noise in an $L^p$ setting. We obtain existence and uniqueness of mild and weak solutions. The boundary…

Probability · Mathematics 2010-01-14 Roland Schnaubelt , Mark Veraar

In this paper we study the following non-autonomous stochastic evolution equation on a UMD Banach space $E$ with type 2, {equation}\label{eq:SEab}\tag{SE} {{aligned} dU(t) & = (A(t)U(t) + F(t,U(t))) dt + B(t,U(t)) dW_H(t), \quad t\in [0,T],…

Probability · Mathematics 2009-09-14 Mark Veraar

This paper is devoted to studying stochastic parabolic evolution equations with additive noise in Banach spaces of M-type 2. We construct both strict and mild solutions possessing very strong regularities. First, we consider the linear…

Probability · Mathematics 2017-04-14 Ton Viet Ta

In the study of partial differential equations (PDEs) with random initial data and singular stochastic PDEs with random forcing, we typically decompose a classically ill-defined solution map into two steps, where, in the first step, we use…

Analysis of PDEs · Mathematics 2024-09-12 Tadahiro Oh , Mamoru Okamoto , Oana Pocovnicu , Nikolay Tzvetkov

We study the convergence of semilinear parabolic stochastic evolution equations, posed on a sequence of Banach spaces approximating a limiting space and driven by additive white noise projected onto the former spaces. Under appropriate…

Probability · Mathematics 2025-06-11 Yves van Gennip , Jonas Latz , Joshua Willems