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In this paper, we study direct and inverse images for fractional stochastic tangent sets and we establish the deterministic necessary and sufficient conditions that guarantee that the solution of a given stochastic differential equation…

Dynamical Systems · Mathematics 2010-06-11 Tianyang Nie , Aurel Rascanu

We study stochastic differential equations (SDEs) whose drift and diffusion coefficients are path-dependent and controlled. We construct a value process on the canonical path space, considered simultaneously under a family of singular…

Probability · Mathematics 2012-05-08 Marcel Nutz

In this paper, we investigate the well-posedness of quadratic backward stochastic differential equations driven by G-Brownian motion (referred to as G-BSDEs) with double mean reflections. By employing a representation of the solution via…

Probability · Mathematics 2025-08-27 Wei He , Qiangjun Tang

We consider rough differential equations whose coefficients contain path-dependent bounded variation terms and prove the existence and a priori estimate of solutions. These equations include classical path-dependent SDEs containing running…

Probability · Mathematics 2024-03-12 Shigeki Aida

Pairwise comparison data are widely used to infer latent rankings in areas such as sports, social choice, and machine learning. The Bradley-Terry model provides a foundational probabilistic framework but inherently assumes transitive…

Methodology · Statistics 2026-01-13 Hisaya Okahara , Tomoyuki Nakagawa , Shonosuke Sugasawa

By the methods of probability and duality technique, we give some comparison theorems for the solutions of infinite horizon forward-backwad stochastic differential equations.

Probability · Mathematics 2010-05-25 Liangquan Zhang , Yufeng Shi

Causal inference is a crucial goal of science, enabling researchers to arrive at meaningful conclusions regarding the predictions of hypothetical interventions using observational data. Path models, Structural Equation Models (SEMs), and,…

Machine Learning · Statistics 2024-01-11 Matthew J. Vowels

Signature stochastic differential equations (SDEs) constitute a large class of stochastic processes, here driven by Brownian motions, whose characteristics are linear maps of their own signature, i.e. of iterated integrals of the process…

Probability · Mathematics 2025-02-04 Christa Cuchiero , Sara Svaluto-Ferro , Josef Teichmann

The conformal invariance of Brownian motion is used to give a short proof of the Open Mapping Theorem for analytic functions.

Complex Variables · Mathematics 2019-02-20 Greg Markowsky

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 consider a system of stochastic differential equations driven by a standard n-dimensional Brownian motion where the drift coefficient satisfies a Novikov-type condition while the diffusion coefficient is the identity matrix. We define a…

Probability · Mathematics 2013-07-15 Alberto Lanconelli

In this paper, we study the well-posedness of multi-dimensional backward stochastic differential equations driven by $G$-Brownian motion ($G$-BSDEs) with diagonal generators, the $z$ parts of whose $l$-th components only depend on the…

Probability · Mathematics 2020-02-18 Guomin Liu

We show that any stochastic differential equation (SDE) driven by Brownian motion with drift satisfying the Krylov-R\"ockner condition has exactly one solution in an ordinary sense for almost every trajectory of the Brownian motion.…

Probability · Mathematics 2025-07-09 Lukas Anzeletti , Khoa Lê , Chengcheng Ling

Let $X$ be a regular one-dimensional transient diffusion and $L^y$ be its local time at $y$. The stochastic differential equation (SDE) whose solution corresponds to the process $X$ conditioned on $[L^y_{\infty}=a]$ for a given $a\geq 0$ is…

Probability · Mathematics 2017-12-29 Umut Çetin

In many scientific fields imaging is used to relate a certain physical quantity to other dependent variables. Therefore, images can be considered as a map from a real-world coordinate system to the non-negative measurements being acquired.…

Computer Vision and Pattern Recognition · Computer Science 2018-04-18 Liam Cattell , Gustavo K. Rohde

Extensions and variants are given for the well-known comparison principle for Gaussian processes based on ordering by pairwise distance.

Probability · Mathematics 2007-05-23 Richard A. Vitale

The problem of model selection in the context of a system of stochastic differential equations (SDEs) has not been touched upon in the literature. Indeed, properties of Bayes factors have not been studied even in single SDE based model…

Statistics Theory · Mathematics 2018-04-18 Trisha Maitra , Sourabh Bhattacharya

Under certain mild conditions, some limit theorems for functionals of two independent Gaussian processes are obtained. The results apply to general Gaussian processes including fractional Brownian motion, sub-fractional Brownian motion and…

Probability · Mathematics 2018-01-30 Jian Song , Fangjun Xu , Qian Yu

In terms of a nice reference probability measure, integrability conditions on the path-dependent drift are presented for (infinite-dimensional) degenerate PDEs to have regular positive solutions. To this end, the corresponding stochastic…

Probability · Mathematics 2018-01-26 Feng-Yu Wang

We construct the conditional version of $k$ independent and identically distributed random walks on $\R$ given that they stay in strict order at all times. This is a generalisation of so-called non-colliding or non-intersecting random…

Probability · Mathematics 2007-05-23 Peter Eichelsbacher , Wolfgang Konig