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In this paper we study the existence of a unique solution for linear stochastic differential equations driven by a L\'evy process, where the initial condition and the coefficients are random and not necessarily adapted to the underlying…

Probability · Mathematics 2012-07-09 Jorge A. León , David Márquez-Carreras , Josep Vives

We study a stochastic model of protein dynamics that explicitly includes delay in the degradation. We rigorously derive the master equation for the processes and solve it exactly. We show that the equations for the mean values obtained…

Statistical Mechanics · Physics 2013-05-29 Luis F. Lafuerza , Raul Toral

We define various higher-order Markov properties for stochastic processes $(X(t))_{t\in \mathbb{T}}$, indexed by an interval $\mathbb{T} \subseteq \mathbb{R}$ and taking values in a real and separable Hilbert space $U$. We furthermore…

Probability · Mathematics 2026-01-06 Kristin Kirchner , Joshua Willems

We prove existence of weak solutions to an evolutionary model derived for magnetoelastic materials. The model is phrased in Eulerian coordinates and consists in particular of (i) a Navier-Stokes equation that involves magnetic and elastic…

Analysis of PDEs · Mathematics 2016-08-11 Barbora Benešová , Johannes Forster , Chun Liu , Anja Schlömerkemper

Stochastic antiderivational equations on Banach spaces over local non-Archimedean fields are investigated. Theorems about existence and uniqiuness of the solutions are proved under definite conditions. In particular Wiener processes are…

General Mathematics · Mathematics 2007-05-23 S. V. Ludkovsky

We develop a functional framework suitable for the treatment of partial differential equations and variational problems on evolving families of Banach spaces. We propose a definition for the weak time derivative that does not rely on the…

Analysis of PDEs · Mathematics 2023-02-17 Amal Alphonse , Diogo Caetano , Ana Djurdjevac , Charles M. Elliott

We study the problem of learning the law of linear stochastic partial differential equations (SPDEs) with additive Gaussian forcing from spatiotemporal observations. Most existing deep learning approaches either assume access to the driving…

Machine Learning · Computer Science 2026-02-13 Sebastian Zeng , Andreas Petersson , Wolfgang Bock

Analytic smooth solutions of a general, strongly parabolic semi-linear Cauchy problem of $2m$-th order in $\mathbb{R}^N\times (0,T)$ with analytic coefficients (in space and time variables) and analytic initial data (in space variables) are…

Analysis of PDEs · Mathematics 2021-01-05 Falko Baustian , Peter Takáč

We prove existence and uniqueness of a mild solution of a stochastic evolution equation driven by a standard $\alpha$-stable cylindrical L\'evy process defined on a Hilbert space for $\alpha \in (1,2)$. The coefficients are assumed to map…

Probability · Mathematics 2021-08-05 Tomasz Kosmala , Markus Riedle

We investigate the properties of a continuous time GARCH process as the solution to a L\'evy driven stochastic functional integral equation. This process occurs as a weak limit of a sequence of discrete time GARCH processes as the time…

Probability · Mathematics 2018-04-25 Adam Nie

A subdiffusion problem in which the diffusion term is related to a stable stochastic process is introduced. Linear models of these systems have been studied in a general way, but non-linear models require a more specific analysis. The model…

Probability · Mathematics 2021-11-05 Soveny Solís , Vicente Vergara

We present an investigation of stochastic evolution in which a family of evolution equations in $L^1$ are driven by continuous-time Markov processes. These are examples of so-called piecewise deterministic Markov processes (PDMP's) on the…

Probability · Mathematics 2020-12-01 Paweł Klimasara , Michael C. Mackey , Andrzej Tomski , Marta Tyran-Kamińska

In this paper, we develop a universal, conceptually simple and systematic method to prove well-posedness to Cauchy problems for weak solutions of parabolic equations with non-smooth, time-dependent, elliptic part having a variational…

Analysis of PDEs · Mathematics 2025-06-25 Pascal Auscher , Khalid Baadi

The goal of this review article is to provide a survey about the foundations of semilinear stochastic partial differential equations. In particular, we provide a detailed study of the concepts of strong, weak and mild solutions, establish…

Probability · Mathematics 2025-11-21 Stefan Tappe

We consider the boundary value problems (BVPs) for linear secondorder ODEs with a strongly positive operator coefficient in a Banach space. The solutions are given in the form of the infinite series by means of the Cayley transform of the…

Numerical Analysis · Mathematics 2020-07-06 V. L. Makarov , N. V. Mayko

We consider the problem of constructing Lyapunov functions for linear differential equations with delays. For such systems it is known that exponential stability implies the existence of a positive Lyapunov function which is quadratic on…

Dynamical Systems · Mathematics 2007-07-03 Matthew M. Peet , Antonis Papachristodoulou , Sanjay Lall

In the article, integration of temporal functions in (possibly non-UMD) Banach spaces with respect to (possibly non-Gaussian) fractional processes from a finite sum of Wiener chaoses is treated. The family of fractional processes that is…

Probability · Mathematics 2020-12-18 Petr Čoupek , Bohdan Maslowski , Martin Ondreját

We consider the Cauchy problem for a semilinear stochastic differential inclusion in a Hilbert space. The linear operator generates a strongly continuous semigroup and the nonlinear term is multivalued and satisfies a condition which is…

Probability · Mathematics 2007-05-23 Adam Jakubowski , Mikhail Kamenskii , Paul Raynaud De Fitte

This paper introduces a novel theoretical framework for the analysis of vector-valued neural networks through the development of vector-valued variation spaces, a new class of reproducing kernel Banach spaces. These spaces emerge from…

Machine Learning · Statistics 2024-08-21 Joseph Shenouda , Rahul Parhi , Kangwook Lee , Robert D. Nowak

We obtain estimates on the first-order Malliavin derivative of mild solutions, evaluated at fixed points in time and space, to a class of parabolic dissipative stochastic PDEs on bounded domain of $\mathbb{R}^d$. In particular, such…

Probability · Mathematics 2022-01-04 Carlo Marinelli