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In this paper we consider the nonparametric functional estimation of the drift of Gaussian processes using Paley-Wiener and Karhunen-Lo\`eve expansions. We construct efficient estimators for the drift of such processes, and prove their…

Statistics Theory · Mathematics 2018-08-20 Nicolas Privault , Anthony Reveillac

We consider the transport equation driven by the fractional Brownian motion. We study the existence and the uniqueness of the weak solution and, by using the tools of the Malliavin calculus, we prove the existence of the density of the…

Probability · Mathematics 2014-08-28 Christian Olivera , Ciprian Tudor

As a general rule, differential equations driven by a multi-dimensional irregular path $\Gamma$ are solved by constructing a rough path over $\Gamma$. The domain of definition ? and also estimates ? of the solutions depend on upper bounds…

Probability · Mathematics 2009-05-07 Jérémie Unterberger

We study the one-dimensional stochastic heat equation with unbounded, nonlinear,Lipschitz coefficients with Dirichlet boundary conditions. Using Malliavin calculus, we construct a piecewise approximation of the solution u and establish…

Analysis of PDEs · Mathematics 2025-02-27 D. Farazakis , G. Karali , A. Stavrianidi

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

In this paper, we establish existence, uniqueness, and regularity properties of the solutions to multi-dimensional backward stochastic Volterra integral equations (BSVIEs), whose (possibly random) generator reflects nonlinear dependence on…

Probability · Mathematics 2025-01-09 Qian Lei , Chi Seng Pun

Based on the notion of paracontrolled distributions, we provide existence and uniqueness results for rough Volterra equations of convolution type with potentially singular kernels and driven by the newly introduced class of convolutional…

Probability · Mathematics 2021-09-21 David J. Prömel , Mathias Trabs

We provide an existence and uniqueness result for mild solutions to rough partial differential equations in the framework of the semigroup approach. Applications to stochastic partial differential equations driven by infinite dimensional…

Probability · Mathematics 2025-11-24 Stefan Tappe

We derive quantitative criteria for the existence of density for stochastic line integrals and iterated line integrals along solutions of hypoelliptic differential equations driven by fractional Brownian motion. As an application, we also…

Probability · Mathematics 2022-02-08 Xi Geng , Sheng Wang

The existence of unique solutions is established for rough differential equations (RDEs) with path-dependent coefficients and driven by c\`adl\`ag rough paths. Moreover, it is shown that the associated solution map, also known as…

Probability · Mathematics 2025-08-26 Anna P. Kwossek , Andreas Neuenkirch , David J. Prömel

In this article we investigate the rough paths structure of a process $X_t$ living in a fixed Wiener chaos. Specifically, we formulate various types of rough lifts of $X_t$ and study their properties. As application, we study the…

Probability · Mathematics 2023-03-17 Guang Yang

The stochastic rotational invariance of an integration by parts formula inspired by the Bismut approach to Malliavin calculus is proved in the framework of the Lie symmetry theory of stochastic differential equations. The non-trivial effect…

Probability · Mathematics 2025-06-16 Susanna Dehò , Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

This paper is devoted to a study on SDEs with a bounded Borel drift b. We first remark that the original integration by parts formula due to P. Malliavin can be used to deal with derivatives with respect to space variables, then we obtain a…

Probability · Mathematics 2025-07-21 Shizan Fang , Rongrong Tian

The It\^o formula, also known as the change-of-variables formula, is a cornerstone of It\^o stochastic calculus. Over time, this formula has been extended to apply to random processes for which classical calculus is insufficient. Since…

Probability · Mathematics 2025-09-30 Nannan Li , Xing Gao

An implicit Euler--Maruyama method with non-uniform step-size applied to a class of stochastic partial differential equations is studied. A spectral method is used for the spatial discretization and the truncation of the Wiener process. A…

Numerical Analysis · Mathematics 2018-04-11 Yoshihito Kazashi

We construct an explicit one-to-one correspondence between non-relativistic stochastic processes and solutions of the Schrodinger equation and between relativistic stochastic processes and solutions of the Klein-Gordon equation. The…

Quantum Physics · Physics 2023-06-21 Folkert Kuipers

We study several important fine properties for the family of fractional Brownian motions with Hurst parameter $H$ under the $(p,r)$-capacity on classical Wiener space introduced by Malliavin. We regard fractional Brownian motions as Wiener…

Probability · Mathematics 2025-06-11 Jiawei Li , Zhongmin Qian

This paper investigates solvability of fully coupled systems of forward-backward stochastic differential equations (FBSDEs) with irregular coefficients. In particular, we assume that the coefficients of the FBSDEs are merely measurable and…

Probability · Mathematics 2020-04-02 Peng Luo , Olivier Menoukeu-Pamen , Ludovic Tangpi

Optimal paths for the classical Onsager-Machlup function determining most probable paths between points on a manifold are only explicitly identified for specific processes, for example the Riemannian Brownian motion. This leaves out large…

Probability · Mathematics 2026-03-19 Erlend Grong , Stefan Sommer

We consider a class of degenerate equations satisfying a parabolic H\"ormander condition, with coefficients that are measurable in time and H\"older continuous in the space variables. By utilizing a generalized notion of strong solution, we…

Analysis of PDEs · Mathematics 2023-05-04 Giacomo Lucertini , Stefano Pagliarani , Andrea Pascucci