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The Stochastic Partial Differential Equation (SPDE) approach, now commonly used in spatial statistics to construct Gaussian random fields, is revisited from a mechanistic perspective based on the movement of microscopic particles, thereby…

Methodology · Statistics 2021-11-11 Lionel Roques , Denis Allard , Samuel Soubeyrand

We have previously observed that the theory of solutions of partial differential equations, regarded as diffieties inside jet bundles, acquires a powerful comonadic formulation after passage from the category of Fr\'echet smooth manifolds…

Differential Geometry · Mathematics 2026-01-23 Grigorios Giotopoulos , Igor Khavkine , Hisham Sati , Urs Schreiber

Stochastic difference equations and a stochastic partial differential equation (SPDE) are simultaneously derived for the time-dependent neutron angular density in a general three-dimensional medium where the neutron angular density is a…

Numerical Analysis · Mathematics 2010-04-16 Edward J. Allen

In this paper we present a scheme for the numerical solution of one-dimensional stochastic differential equations (SDEs) whose drift belongs to a fractional Sobolev space of negative regularity (a subspace of Schwartz distributions). We…

Probability · Mathematics 2022-09-21 Tiziano De Angelis , Maximilien Germain , Elena Issoglio

We provide necessary and sufficient conditions for stochastic invariance of finite dimensional submanifolds for solutions of stochastic partial differential equations (SPDEs) in continuously embedded Hilbert spaces with non-smooth…

Probability · Mathematics 2025-11-21 Rajeev Bhaskaran , Stefan Tappe

We study two-dimensional stochastic differential equations (SDEs) of McKean--Vlasov type in which the conditional distribution of the second component of the solution given the first enters the equation for the first component of the…

Probability · Mathematics 2019-05-16 Daniel Lacker , Mykhaylo Shkolnikov , Jiacheng Zhang

Multidimensional magneto-hydrodynamical (MHD) simulations coupled with stochastic differential equations (SDEs) adapted to test particle acceleration and transport in complex astrophysical flows are presented. The numerical scheme allows…

Astrophysics · Physics 2009-11-07 F. Casse , A. Marcowith

We consider stochastic differential equations (SDEs) driven by Feller processes which are themselves solutions of multivariate Levy driven SDEs. The solutions of these 'iterated SDEs' are shown to be non-Markovian. However, the process…

Probability · Mathematics 2015-03-19 Alexander Schnurr

A new class of stochastic field models is constructed using nested stochastic partial differential equations (SPDEs). The model class is computationally efficient, applicable to data on general smooth manifolds, and includes both the…

Applications · Statistics 2011-04-19 David Bolin , Finn Lindgren

In this paper we consider multidimensional stochastic differential equations (SDEs) with discontinuous drift and possibly degenerate diffusion coefficient. We prove an existence and uniqueness result for this class of SDEs and we present a…

Numerical Analysis · Mathematics 2018-12-12 Gunther Leobacher , Michaela Szölgyenyi

We obtain a stochastic differential equation (SDE) satisfied by the first $n$ coordinates of a Brownian motion on the unit sphere in $\mathbb{R}^{n+\ell}$. The SDE has non-Lipschitz coefficients but we are able to provide an analysis of…

Probability · Mathematics 2018-09-14 Aleksandar Mijatović , Veno Mramor , Gerónimo Uribe Bravo

This is a review of some coordinate-free calculi of pseudodifferential operators developed in the last years. As an application, we use a coordinate-free calculus to obtain new results on the behaviour of the spectral projections of a…

Analysis of PDEs · Mathematics 2011-06-21 P. Mckeag , Y. Safarov

In this article we prove that stochastic differential equation (SDE) with Sobolev drift on compact Riemannian manifold admits a unique $\nu$-almost everywhere stochastic invertible flow, where $\nu$ is the Riemannian measure, which is…

Probability · Mathematics 2010-07-12 Xicheng Zhang

We study derivations and differential forms on the arithmetic jet spaces of smooth schemes, relative to several primes. As applications we give a new interpretation of arithmetic Laplacians and we discuss the de Rham cohomology of some…

Number Theory · Mathematics 2009-08-19 James Borger , Alexandru Buium

Using parametrized curves (Section 1) or parametrized sheets (Section 3), and suitable metrics, we treat the jet bundle of order one as a semi-Riemann manifold. This point of view allows the description of solutions of DEs as pregeodesics…

Dynamical Systems · Mathematics 2016-09-07 Constantin Udriste

Deterministic flow models, such as rectified flows, offer a general framework for learning a deterministic transport map between two distributions, realized as the vector field for an ordinary differential equation (ODE). However, they are…

Machine Learning · Computer Science 2024-10-04 Saurabh Singh , Ian Fischer

We formulate and prove a {\it Local Stable Manifold Theorem\/} for stochastic differential equations (sde's) that are driven by spatial Kunita-type semimartingales with stationary ergodic increments. Both Stratonovich and It\^o-type…

Probability · Mathematics 2016-09-07 Salah-Eldin A. Mohammed , Michael K. R. Scheutzow

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

Stochastic symmetries and related invariance properties of finite dimensional SDEs driven by general cadlag semimartingales taking values in Lie groups are defined and investigated. The considered set of SDEs, first introduced by S. Cohen,…

Probability · Mathematics 2020-08-04 Sergio Albeverio , Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

The manifold hypothesis suggests that high-dimensional neural time series lie on a low-dimensional manifold shaped by simpler underlying dynamics. To uncover this structure, latent dynamical variable models such as state-space models,…

Machine Learning · Computer Science 2025-07-30 Pedram Rajaei , Maryam Ostadsharif Memar , Navid Ziaei , Behzad Nazari , Ali Yousefi