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We establish the existence of solutions to path-dependent rough differential equations with non-anticipative coefficients. Regularity assumptions on the coefficients are formulated in terms of horizontal and vertical derivatives.

Probability · Mathematics 2020-01-30 Anna Ananova

In this paper, we study reflected differential equations driven by continuous paths with finite $p$-variation ($1\le p<2$) and $p$-rough paths ($2\le p<3$) on domains in Euclidean spaces whose boundaries may not be smooth. We define…

Probability · Mathematics 2015-04-24 Shigeki Aida

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

In this paper, we investigate reflected backward stochastic differential equations driven by rough paths (rough RBSDEs), which can be viewed as probabilistic representations of nonlinear rough partial differential equations (rough PDEs) or…

Probability · Mathematics 2025-01-07 Hanwu Li , Huilin Zhang , Kuan Zhang

We investigate rough differential equations with a time-dependent reflecting lower barrier, where both the driving (rough) path and the barrier itself may have jumps. Assuming the driving signals allow for Young integration, we provide…

Probability · Mathematics 2021-09-21 Andrew L. Allan , Chong Liu , David J. Prömel

We introduce a notion of rough paths on embedded submanifolds and demonstrate that this class of rough paths is natural. On the way we develop a notion of rough integration and an efficient and intrinsic theory of rough differential…

Probability · Mathematics 2017-05-17 Thomas Cass , Bruce K. Driver , Christian Litterer

This paper introduces the path derivatives, in the spirit of Dupire's functional It\^o calculus, for the controlled paths in the rough path theory with possibly non-geometric rough paths. The theory allows us to deal with rough integration…

Probability · Mathematics 2014-12-24 Christian Keller , Jianfeng Zhang

We discuss regular and weak solutions to rough partial differential equations (RPDEs), thereby providing a (rough path-)wise view on important classes of SPDEs. In contrast to many previous works on RPDEs, our definition gives honest…

Probability · Mathematics 2019-02-11 Joscha Diehl , Peter K. Friz , Wilhelm Stannat

In the spirit of Marcus canonical stochastic differential equations, we study a similar notion of rough differential equations (RDEs), notably dropping the assumption of continuity prevalent in the rough path literature. A new metric is…

Probability · Mathematics 2019-02-12 Ilya Chevyrev , Peter K. Friz

We give meaning to linear and semi-linear (possibly degenerate) parabolic partial differential equations with (affine) linear rough path noise and establish stability in a rough path metric. In the case of enhanced Brownian motion (Brownian…

Probability · Mathematics 2013-01-17 Peter Friz , Harald Oberhauser

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 study controlled differential equations driven by a rough path (in the sense of T. Lyons) with an additional, possibly unbounded drift term. We show that the equation induces a solution flow if the drift grows at most linearly.…

Probability · Mathematics 2016-05-19 Sebastian Riedel , Michael Scheutzow

Using rough path techniques, we provide a priori estimates for the output of Deep Residual Neural Networks in terms of both the input data and the (trained) network weights. As trained network weights are typically very rough when seen as…

Machine Learning · Computer Science 2023-02-22 Christian Bayer , Peter K. Friz , Nikolas Tapia

In this note we consider differential equations driven by a signal $x$ which is $\gamma$-H\"older with $\gamma>1/3$, and is assumed to possess a lift as a rough path. Our main point is to obtain existence of solutions when the coefficients…

Probability · Mathematics 2017-08-17 Prakash Chakraborty , Samy Tindel

We study a class of linear first and second order partial differential equations driven by weak geometric $p$-rough paths, and prove the existence of a unique solution for these equations. This solution depends continuously on the driving…

Analysis of PDEs · Mathematics 2008-03-24 Michael Caruana , Peter Friz

In [1], we proved the existence of solutions to reflected rough differential equations based on an idea of Euler approximation of the solutions which is due to Davie [6]. In this paper, we prove the existence theorem under weaker…

Probability · Mathematics 2016-08-29 Shigeki Aida

This paper establishes the existence and uniqueness of solutions for rough differential equations driven by reduced rough paths with low regularity, specifically in the roughness regime $\frac{1}{3} < \alpha \leq \frac{1}{2}$. While the…

Probability · Mathematics 2025-12-02 Nannan Li , Xing Gao

In this paper we review and improve pathwise uniqueness results for some types of one-dimensional stochastic differential equations (SDE) involving the local time of the unknown process. The diffusion coefficient of the SDEs we consider is…

Probability · Mathematics 2018-11-07 Olivier Menoukeu-Pamen , Youssef Ouknine , Ludovic Tangpi

We prove existence and uniqueness of the solution of a one-dimensional rough differential equation driven by a step-2 rough path and reflected at zero. In order to deal with the lack of control of the reflection measure the proof uses some…

Probability · Mathematics 2016-10-25 Aurelien Deya , Massimiliano Gubinelli , Martina Hofmanova , Samy Tindel

The theory of rough paths arose from a desire to establish continuity properties of ordinary differential equations involving terms of low regularity. While essentially an analytic theory, its main motivation and applications are in…

Classical Analysis and ODEs · Mathematics 2025-01-28 Ilya Chevyrev
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