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We derive moment estimates and a strong limit theorem for space inverses of stochastic flows generated by jump SDEs with adapted coefficients in weighted H\"older norms using the Sobolev embedding theorem and the change of variable formula.…

Probability · Mathematics 2014-11-25 James-Michael Leahy , Remigijus Mikulevicius

In this work we show that rough stochastic differential equations (RSDEs), as introduced by Friz, Hocquet, and L\^e (2021), are Malliavin differentiable. We use this to prove existence of a density when the diffusion coefficients satisfies…

Probability · Mathematics 2024-02-20 Fabio Bugini , Michele Coghi , Torstein Nilssen

We study the adapted solution, numerical methods, and related convergence analysis for a unified backward stochastic partial differential equation (B-SPDE). The equation is vector-valued, whose drift and diffusion coefficients may involve…

Probability · Mathematics 2024-02-21 Wanyang Dai

Let $(W,H,\mu)$ be the classical Wiener space on $\R^d$. Assume that $X=(X_t(x))$ is a diffusion process satisfying the stochastic differential equation with diffusion and drift coefficients $\sigma: \R^n\to \R^n\otimes \R^d$, $b: \R^n\to…

Probability · Mathematics 2024-01-29 Ali Süleyman Üstünel

This is the second of two works concerning the Sobolev calculus on metric measure spaces and its applications. In this work, we focus on several approaches to vector calculus in the non-smooth setting of complete and separable metric spaces…

Functional Analysis · Mathematics 2025-10-15 Luigi Ambrosio , Toni Ikonen , Danka Lučić , Enrico Pasqualetto

This work concerns continuous-time, continuous-space stochastic dynamical systems described by stochastic differential equations (SDE). It presents a new approach to compute probabilistic safety regions, namely sets of initial conditions of…

Probability · Mathematics 2023-01-12 Francesco Cosentino , Harald Oberhauser , Alessandro Abate

We introduce a new framework based on Malliavin calculus to derive exact analytical expressions for the score function $\nabla \log p_t(x)$, i.e., the gradient of the log-density associated with the solution to stochastic differential…

Machine Learning · Computer Science 2025-11-25 Ehsan Mirafzali , Utkarsh Gupta , Patrick Wyrod , Frank Proske , Daniele Venturi , Razvan Marinescu

In this paper we present a new method for the construction of strong solutions of SDE's with merely integrable drift coefficients driven by a multidimensional fractional Brownian motion with Hurst parameter H < 1/2. Furthermore, we prove…

Probability · Mathematics 2018-05-30 David Baños , Torstein Nilssen , Frank Proske

We consider measurable $F: \Omega \times \mathbb{R}^d \to \mathbb{R}$ where $F(\cdot, x)$ belongs for any $x$ to the Malliavin Sobolev space $\mathbb{D}_{1,2}$ (with respect to a L\'evy process) and provide sufficient conditions on $F$ and…

Probability · Mathematics 2016-09-26 Christel Geiss , Alexander Steinicke

We introduce a new method for analyzing midpoint discretizations of stochastic differential equations (SDEs), which are frequently used in Markov chain Monte Carlo (MCMC) methods for sampling from a target measure $\pi \propto \exp(-V)$.…

Numerical Analysis · Mathematics 2025-07-18 Matthew S. Zhang

We investigate the problem of the equivalence of $L^q$-Sobolev norms in Malliavin spaces for $q\in [1,\infty)$, focusing on the graph norm of the $k$-th Malliavin derivative operator and the full Sobolev norm involving all derivatives up to…

Functional Analysis · Mathematics 2021-08-27 Davide Addona , Matteo Muratori , Maurizia Rossi

In this paper a Malliavin calculus for L\'evy processes based on a family of true derivative operators is developed. The starting point is an extension to L\'evy processes of the pioneering paper by Carlen and Pardoux [8] for the Poisson…

Probability · Mathematics 2012-10-04 Jorge A. León , Josep L. Solé , Frederic Utzet , Josep Vives

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

By using the Malliavin calculus, the Driver-type integration by parts formula is established for the semigroup associated to to SPDEs with Multiplicative Noise. Moreover, estimates on the density of heat kernel w.r.t. Lebesgue measure are…

Probability · Mathematics 2016-10-11 Xing Huang , Shao-Qin Zhang , Li-Xia Liu

Let $(X_t)_{t \ge 0}$ be solution of a one-dimensional stochastic differential equation. Our aim is to study the convergence rate for the estimation of the invariant density in intermediate regime, assuming that a discrete observation of…

Statistics Theory · Mathematics 2024-03-04 Chiara Amorino , Arnaud Gloter

We consider the class of non-linear stochastic partial differential equations studied in \cite{conusdalang}. Equivalent formulations using integration with respect to a cylindrical Brownian motion and also the Skorohod integral are…

Probability · Mathematics 2015-03-25 Marta Sanz-Solé , André Süß

We study stochastic differential equations driven by finite-order chaos processes on abstract Wiener spaces, with pathwise Riemann-Stieltjes integration. The driving noise is an $\mathbb{R}^m$-valued chaotic process given by multiple…

Probability · Mathematics 2026-04-28 Laurent Loosveldt , Yassine Nachit , Ivan Nourdin

We show regularity properties of local densities of solutions of stochastic differential equations (SDEs) with the Fourier analytic approach. With this simple method, statements that were previously derived with approaches using Malliavin…

Probability · Mathematics 2025-05-01 Simon Ellinger

For degenerate stochastic differential equations driven by fractional Brownian motions with Hurst parameter $H>1/2$, the derivative formulas are established by using Malliavin calculus and coupling method, respectively. Furthermore, we find…

Probability · Mathematics 2018-03-02 Xiliang Fan

In this paper we study the existence and uniqueness of the strong solution of following d dimensional stochastic differential equation (SDE) driven by Brownian motion: dX(t)=b(t,X(t))dt+a(t,X(t))dB(t), X(0)= x, where B is a d-dimensional…

Probability · Mathematics 2024-07-26 Yaozhong Hu , Qun Shi