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We consider a d-dimensional stochastic differential equation with additive noise and a drift coefficient which is assumed only to be a bounded Borel function. We show that, for almost all choices of the driving Brownian path, the equation…

Probability · Mathematics 2007-09-27 A. M. Davie

We consider one-dimensional stochastic differential equations with jumps in the general case. We introduce new technics based on local time and we prove new results on pathwise uniqueness and comparison theorems. Our approach are very easy…

Probability · Mathematics 2011-08-22 M. Benabdallah , S. Bouhadou , Y. Ouknine

By establishing a local version of Bismut formula for Dirichlet semigroups on a regular domain, gradient estimates are derived for killed SDEs with singular drifts. As an application, the total variation distance between two solutions of…

Probability · Mathematics 2026-03-30 Feng-Yu Wang , Xiao-Yu Zhao

Concept drift -- the change of the distribution over time -- poses significant challenges for learning systems and is of central interest for monitoring. Understanding drift is thus paramount, and drift localization -- determining which…

Machine Learning · Computer Science 2026-04-22 Fabian Hinder , Valerie Vaquet , Johannes Brinkrolf , Barbara Hammer

We obtain $T_2(C)$ for stochastic differential equations with Dini continuous drift and $T_1(C)$ stochastic differential equations with singular coefficients.

Probability · Mathematics 2020-07-30 Yongqiang Suo , Chenggui Yuan , Shao-Qin Zhang

We study the estimation of time-homogeneous drift functions in multivariate stochastic differential equations with known diffusion coefficient, from multiple trajectories observed at high frequency over a fixed time horizon. We formulate…

Machine Learning · Statistics 2026-02-23 Marcos Tapia Costa , Nikolas Kantas , George Deligiannidis

It is generally understood that a given one-dimensional diffusion may be transformed by Cameron-Martin-Girsanov measure change into another one-dimensional diffusion with the same volatility but a different drift. But to achieve this we…

Mathematical Finance · Quantitative Finance 2020-12-08 Sascha Desmettre , Gunther Leobacher , L. C. G. Rogers

We study the convergence of a generic tamed Euler-Maruyama (EM) scheme for the kinetic type stochastic differential equations (SDEs) (also known as second order SDEs) with singular coefficients in both weak and strong probabilistic senses.…

Probability · Mathematics 2024-09-10 Zimo Hao , Khoa Lê , Chengcheng Ling

Moment estimation for stochastic differential equations (SDEs) is fundamental to the formal reasoning and verification of stochastic dynamical systems, yet remains challenging and is rarely available in closed form. In this paper, we study…

Systems and Control · Electrical Eng. & Systems 2026-03-04 Shenghua Feng , Jie An , Naijun Zhan , Fanjiang Xu

Large-time asymptotic properties of solutions to a class of semilinear stochastic wave equations with damping in a bounded domain are considered. First an energy inequality and the exponential bound for a linear stochastic equation are…

Probability · Mathematics 2007-05-23 Pao-Liu Chow

We propose a probabilistic definition of solutions of semilinear elliptic equations with (possibly nonlocal) operators associated with regular Dirichlet forms and with measure data. Using the theory of backward stochastic differential…

Analysis of PDEs · Mathematics 2013-06-25 Tomasz Klimsiak , Andrzej Rozkosz

By using a change of scale and space, we study a class of stochastic differential equations (SDEs) whose solutions are drift--perturbed and exhibit behaviour analogous to standard Brownian motion including to the Law of the Iterated…

Probability · Mathematics 2013-10-11 John A. D. Appleby , Huizhong Appleby-Wu

A general formalism to solve nonlinear differential equations is given. Solutions are found and reduced to those of second order nonlinear differential equations in one variable. The approach is uniformized in the geometry and solves…

General Physics · Physics 2007-05-23 Gordon Chalmers

This work is concerned with existence of weak solutions to discon- tinuous stochastic differential equations driven by multiplicative Gaus- sian noise and sliding mode control dynamics generated by stochastic differential equations with…

Optimization and Control · Mathematics 2015-04-27 Viorel Barbu , Stefano Bonaccorsi , Luciano Tubaro

The goal of this paper is to clarify when the solutions to stochastic partial differential equations stay close to a given subset of the state space for starting points which are close as well. This includes results for deterministic…

Probability · Mathematics 2024-10-10 Toshiyuki Nakayama , Stefan Tappe

It is well-known that a stochastic differential equation (sde) on a Euclidean space driven by a (possibly infinite-dimensional) Brownian motion with Lipschitz coefficients generates a stochastic flow of homeomorphisms. If the Lipschitz…

Probability · Mathematics 2016-03-23 Michael Scheutzow , Susanne Schulze

In studying randomized search heuristics, a frequent quantity of interest is the first time a (real-valued) stochastic process obtains (or passes) a certain value. The processes under investigation commonly show a bias towards this goal,…

Probability · Mathematics 2024-06-24 Timo Kötzing

A useful approach is investigated in order to analyze a class of a stochastic differential equations that can be encountered in quantum optics problems, especially, in the case of two photon losses on the driven cavity mode. The passage to…

Quantum Physics · Physics 2017-09-27 Smail Bougouffa , Lazhar Bougoffa

We develop the rough path counterpart of It\^o stochastic integration and - differential equations driven by general semimartingales. This significantly enlarges the classes of (It\^o / forward) stochastic differential equations treatable…

Probability · Mathematics 2017-09-18 Peter K. Friz , Huilin Zhang

We explore the limit of stochastic differential equations driven by some random processes satisfying singularly perturbed second order stochastic differential equations. The main tool we employ is the universal limit theorem in rough path…

Probability · Mathematics 2026-04-08 Qingming Zhao , Xueru Liu , Wei Wang
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