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We survey some of our recent results on existence, uniqueness and regularity of function solutions to parabolic and transport type partial differential equations driven by non-differentiable noises. When applied pathwise to random…

Probability · Mathematics 2013-12-12 Michael Hinz , Elena Issoglio , Martina Zähle

The full history recursive multilevel Picard approximation method for semilinear parabolic partial differential equations (PDEs) is the only method which provably overcomes the curse of dimensionality for general time horizons if the…

Numerical Analysis · Mathematics 2022-04-29 Martin Hutzenthaler , Tuan Anh Nguyen

This paper presents theoretical advances in the application of the Stochastic Partial Differential Equation (SPDE) approach in geostatistics. We show a general approach to construct stationary models related to a wide class of linear SPDEs,…

Statistics Theory · Mathematics 2018-07-30 Ricardo Carrizo Vergara , Denis Allard , Nicolas Desassis

The aim of this article is to study the asymptotic behaviour for large times of solutions to a certain class of stochastic partial differential equations of parabolic type. In particular, we will prove the backward uniqueness result and the…

Analysis of PDEs · Mathematics 2009-06-18 Z. Brzeźniak , M. Neklyudov

We consider a stochastic parabolic partial differential equation with Dirichlet boundary conditions, multiplicative stochastic noise, and a monotone parabolic operator A. The growth and coercivity of A is controlled by a general N-function…

Analysis of PDEs · Mathematics 2025-06-17 Piotr Gwiazda , Jakub Woźnicki , Aneta Wróblewska-Kamińska , Aleksandra Zimmermann

Spatial differentiability of solutions of stochastic differential equations (SDEs) is a classical question in stochastic analysis. The case of coefficients with globally Lipschitz continuous derivatives is well understood in the literature.…

Probability · Mathematics 2022-04-27 Anselm Hudde , Martin Hutzenthaler , Sara Mazzonetto

Backward stochastic partial differential equations of parabolic type with variable coefficients are considered in the whole Euclidean space. Improved existence and uniqueness results are given in the Sobolev space $H^n$ ($=W^n_2$) under…

Probability · Mathematics 2009-11-09 Kai Du , Qingxin Meng

We consider state-dependent delay equations (SDDE) obtained by adding delays to a planar ordinary differential equation with a limit cycle. These situations appear in models of several physical processes, where small delay effects are…

Dynamical Systems · Mathematics 2021-08-13 Jiaqi Yang , Joan Gimeno , Rafael de la Llave

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 prove a parabolic version of the Littlewood-Paley inequality for a class of time-dependent local and non-local operators of arbitrary order, and as an application we show this inequality gives a fundamental estimate for the…

Functional Analysis · Mathematics 2015-03-10 Ildoo Kim , Kyeong-Hun Kim , Sungbin Lim

In this paper, we consider the Cauchy problem of semi-linear degenerate backward stochastic partial differential equations (BSPDEs in short) under general settings without technical assumptions on the coefficients. For the solution of…

Probability · Mathematics 2011-09-06 Kai Du , Qi Zhang

This paper proposes a novel low-rank approximation to the multivariate State-Space Model. The Stochastic Partial Differential Equation (SPDE) approach is applied component-wise to the independent-in-time Mat\'ern Gaussian innovation term in…

In this paper, we investigate an ill-posed Cauchy problem involving a stochastic parabolic equation. We first establish a Carleman estimate for this equation. Leveraging this estimate, we derive the conditional stability and convergence…

Numerical Analysis · Mathematics 2024-05-13 Fangfang Dou , Peimin Lü , Yu Wang

Parabolic integro-differential non degenerate Cauchy problem is considered in the scale of H\"older spaces of functions whose regularity is defined by a radially O-regularly varying L\'evy measure. Existence and uniqueness and the estimates…

Probability · Mathematics 2018-10-02 R. Mikulevicius , Fanhui Xu

Numerical methods for stochastic partial differential equations typically estimate moments of the solution from sampled paths. Instead, we shall directly target the deterministic equations satisfied by the first and second moments, as well…

Numerical Analysis · Mathematics 2020-11-17 Kristin Kirchner

It is frequently the case that a white-noise-driven parabolic and/or hyperbolic stochastic partial differential equation (SPDE) can have random-field solutions only in spatial dimension one. Here we show that in many cases, where the…

Probability · Mathematics 2007-11-14 Mohammud Foondun , Davar Khoshnevisan , Eulalia Nualart

In this paper we establish the strong existence, pathwise uniqueness and a comparison theorem to a stochastic partial differential equation driven by Gaussian colored noise with non-Lipschitz drift, H\"older continuous diffusion…

Probability · Mathematics 2020-06-02 Jie Xiong , Xu Yang

The asymptotic analysis of a class of stochastic partial differential equations (SPDEs) with fully locally monotone coefficients covering a large variety of physical systems, a wide class of quasilinear SPDEs and a good number of fluid…

Probability · Mathematics 2022-12-13 Ankit Kumar , Manil T. Mohan

In this paper we study parabolic stochastic partial differential equations defined on arbitrary bounded domain $\cO \subset \bR^d$ allowing Hardy inequality: $$ \int_{\cO}|\rho^{-1}g|^2\,dx\leq C\int_{\cO}|g_x|^2 dx, \quad \forall g\in…

Probability · Mathematics 2011-09-23 Kyeong-Hun Kim

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