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Related papers: SDEs Driven by SDE Solutions

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Stochastic differential equations (SDEs) are well suited to modelling noisy and irregularly sampled time series found in finance, physics, and machine learning. Traditional approaches require costly numerical solvers to sample between…

Machine Learning · Computer Science 2025-10-30 Naoki Kiyohara , Edward Johns , Yingzhen Li

Let $u$ be the solution to the following stochastic evolution equation (1) du(t,x)& = &A u(t,x) dt + B \sigma(u(t,x)) dL(t),\quad t>0; u(0,x) = x taking values in an Hilbert space $\HH$, where $L$ is a $\RR$ valued L\'evy process, $A:H\to…

Probability · Mathematics 2015-07-06 Erika Hausenblas , Paul Andre Razafimandimby

Using the method of Krylov's estimates, we prove the existence of weak solutions of stochastic differential equations driven by purely discontinuous Levy processes satisfying an additional assumption. The diffusion coefficient is assumed to…

Probability · Mathematics 2007-05-23 V. P. Kurenok

We consider a stable driven degenerate stochastic differential equation, whose coefficients satisfy a kind of weak H{\"o}rmander condition. Under mild smoothness assumptions we prove the uniqueness of the martingale problem for the…

Probability · Mathematics 2015-03-06 Lorick Huang , Stephane Menozzi

In this article we study the differentiability of solutions of parabolic semilinear stochastic evolution equations (SEEs) with respect to their initial values. We prove that if the nonlinear drift coefficients and the nonlinear diffusion…

Probability · Mathematics 2021-11-02 Adam Andersson , Arnulf Jentzen , Ryan Kurniawan , Timo Welti

In this paper, we deal with a class of backward doubly stochastic differential equations (BDSDEs, in short) involving subdifferential operator of a convex function and driven by Teugels martingales associated with a L\'evy process. We show…

Probability · Mathematics 2011-08-04 Yon Ren , Auguste Aman

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

In this paper, we investigate stochastic differential equations(SDEs) driven by a class of supercritical $\alpha$-stable process(including the rotational symmetric $\alpha-$stable process) with drift $b$. The weak well-posedness is proved,…

Probability · Mathematics 2020-09-17 Guohuan Zhao

We study functional stochastic differential equations with a locally unbounded, functional drift focusing on well-posedness, stability and the strong Feller property. Following the non-functional case, we only consider integrability…

Probability · Mathematics 2020-09-08 Stefan Bachmann

In this paper, a class of non-Markovian forward-backward doubly stochastic systems is studied. By using the technique of functional It\^o (or path-dependent) calculus, the relationship between the systems and related path-dependent…

Probability · Mathematics 2022-06-14 Yufeng Shi , Jiaqiang Wen , Jie Xiong

Stochastic solutions provide new rigorous results for nonlinear PDE's and, through its local non-grid nature, are a natural tool for parallel computation. There are two different approaches for the construction of stochastic solutions:…

Mathematical Physics · Physics 2012-09-17 Rui Vilela Mendes

In this article we develop a method for the strong approximation of stochastic differential equations (SDEs) driven by L\'evy processes or general semimartingales. The main ingredients of our method is the perturbation of the SDE and the…

Probability · Mathematics 2015-03-13 Antonis Papapantoleon , Maria Siopacha

We demonstrate that stochastic differential equations (SDEs) driven by fractional Brownian motion with Hurst parameter H > 1/2 have similar ergodic properties as SDEs driven by standard Brownian motion. The focus in this article is on…

Probability · Mathematics 2010-05-14 Martin Hairer , Natesh S. Pillai

We present an algorithm for the efficient sampling of conditional paths of stochastic differential equations (SDEs). While unconditional path sampling of SDEs is straightforward, albeit expensive for high dimensional systems of SDEs,…

Numerical Analysis · Mathematics 2011-02-11 Panagiotis Stinis

We deal with a class of fully coupled forward-backward stochastic differential equations (FBSDE for short), driven by Teugels martingales associated with some L\'evy process. Under some assumptions on the derivatives of the coefficients, we…

Probability · Mathematics 2017-01-31 Dalila Guerdouh , Nabil Khelfallah , Brahim Mezerdi

Strong Feller property and irreducibility are study for a class of non-linear monotone stochastic partial differential equations with multiplicative noise. H\"older continuity of the associated Markov semigroups are discussed in some…

Probability · Mathematics 2014-08-01 Shao-Qin Zhang

This paper is interested in semilinear stochastic equations having unbounded nonlinear perturbations in the deterministic part and/or in the random part. Moreover, the linear part of these equations is governed by a not necessarily analytic…

Probability · Mathematics 2021-12-16 Mohamed Fkirine , Said Hadd

The paper studies the rate of convergence of the weak Euler approximation for solutions to SDEs driven by Levy processes, with Hoelder-continuous coefficients. It investigates the dependence of the rate on the regularity of coefficients and…

Probability · Mathematics 2013-05-14 R. Mikulevicius , C. Zhang

We prove existence (and simpleness) of the trace for both forward and backward Loewner chains under fairly general conditions on semimartingale drivers. As an application, we show that stochastic Komatu-Loewner evolutions SKLE$_{\alpha,b}$…

Probability · Mathematics 2025-02-17 Vlad Margarint , Atul Shekhar , Yizheng Yuan

For $\alpha \in (1,2)$, we study the following stochastic differential equation driven by a non-degenerate symmetric $\alpha$-stable process in $\mathbb{R}^d$: \begin{align*} {\rm d} X_t=b(t,X_t){\mathord{{\rm d}}}…

Probability · Mathematics 2025-08-08 Zimo Hao , Mingyan Wu