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Related papers: A Differentiation Theory for It\^o's Calculus

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Under the framework of G-expectation and G-Brownian motion, we introduce It\^o's integral for stochastic processes without assuming quasi-continuity. Then we can obtain It\^o's integral on stopping time interval. This new formulation…

Probability · Mathematics 2011-04-07 Xinpeng Li , Shige Peng

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

Stochastic mechanics---the study of classical stochastic systems governed by things like master equations and Fokker-Planck equations---exhibits striking mathematical parallels to quantum mechanics. In this article, we make those parallels…

Statistical Mechanics · Physics 2019-10-01 John J. Vastola , William R. Holmes

We consider a system of multiscale stochastic differential equations whose slow component is drivenby a fractional Brownian motion with Hurst parameter H greater than 1/2. Under ergodic assumptions ensuring the applicability of the…

Probability · Mathematics 2025-12-10 Xue-Mei Li , Colin Piernot , Szymon Sobczak , Kexing Ying

Averaging is an important method to extract effective macroscopic dynamics from complex systems with slow modes and fast modes. This article derives an averaged equation for a class of stochastic partial differential equations without any…

Analysis of PDEs · Mathematics 2009-04-10 W. Wang , A. J. Roberts

Let $(\mathcal{E},D(\mathcal{E}))$ be a quasi-regular semi-Dirichlet form and $(X_t)_{t\geq0}$ be the associated Markov process. For $u\in D(\mathcal{E})_{loc}$, denote $A_t^{[u]}:=\tilde{u}(X_{t})-\tilde{u}(X_{0})$ and…

Probability · Mathematics 2014-06-11 Chuan-Zhong Chen , Li Ma , Wei Sun

We use the theory of regularity structures to develop an It\^o formula for $u$, the solution of the one dimensional stochastic heat equation driven by space-time white noise with periodic boundary conditions. In particular for any smooth…

Probability · Mathematics 2024-03-13 Carlo Bellingeri

Taking the Fourier integral theorem as our starting point, in this paper we focus on natural Monte Carlo and fully nonparametric estimators of multivariate distributions and conditional distribution functions. We do this without the need…

Methodology · Statistics 2021-06-15 Nhat Ho , Stephen G. Walker

We develop an operator-theoretic formulation of stochastic calculus for fractional Brownian motion with Hurst parameter H in (0, 1/2). The approach is based on adjointness between stochastic integration and differentiation in the…

Probability · Mathematics 2026-01-30 Ramiro Fontes

In 1990, in It\^o's stochastic calculus framework, Aubin and Da Prato established a necessary and sufficient condition of invariance of a nonempty compact or convex subset $C$ of $\mathbb R^d$ ($d\in\mathbb N^*$) for stochastic differential…

Probability · Mathematics 2019-01-16 Laure Coutin , Nicolas Marie

Mathematical models are sometime given as functions of independent input variables and equations or inequations connecting the input variables. A probabilistic characterization of such models results in treating them as functions with…

Optimization and Control · Mathematics 2023-04-13 Matieyendou Lamboni

We point out the relevance of the Differential Galois Theory of linear differential equations for the exact semiclassical computations in path integrals in quantum mechanics. The main tool will be a necessary condition for complete…

Mathematical Physics · Physics 2020-06-24 Juan J. Morales-Ruiz

In this paper we study a stochastic differential equation driven by a fractional Brownian motion with a discontinuous coefficient. We also give an approximation to the solution of the equation. This is a first step to define a fractional…

Probability · Mathematics 2016-07-25 Johanna Garzón , Jorge A. León , Soledad Torres

We develop the foundations of Algebraic Stochastic Calculus, with an aim to replacing what is typically referred to as Stochastic Calculus by a purely categorical version thereof. We first give a sheaf theoretic reinterpretation of…

Algebraic Geometry · Mathematics 2014-07-28 Renaud Gauthier

A large deviation principle is derived for stochastic partial differential equations with slow-fast components. The result shows that the rate function is exactly that of the averaged equation plus the fluctuating deviation which is a…

Probability · Mathematics 2010-01-28 Wei Wang , A. J. Roberts , Jinqiao Duan

We develop a practical framework for distinguishing diffusive stochastic processes from deterministic signals using only a single discrete time series. Our approach is based on classical excursion and crossing theorems for continuous…

Machine Learning · Statistics 2026-05-19 Sunia Tanweer , Firas A. Khasawneh

Fractional Brownian motions(fBMs) are not semimartingales so the classical theory of It\^o integral can't apply to fBMs. Wick integration as one of the applications of Malliavin calculus to stochastic analysis is a fine definition for fBMs.…

Probability · Mathematics 2025-04-01 Chunhao Cai , Cong Zhang

By using Malliavin calculus and multiple Wiener-It\^o integrals, we study the existence and the regularity of stochastic currents defined as Skorohod (divergence) integrals with respect to the Brownian motion and to the fractional Brownian…

Probability · Mathematics 2010-09-17 Franco Flandoli , Ciprian Tudor

Modern problems in AI or in numerical analysis require nonsmooth approaches with a flexible calculus. We introduce generalized derivatives called conservative fields for which we develop a calculus and provide representation formulas.…

Optimization and Control · Mathematics 2020-04-10 Jérôme Bolte , Edouard Pauwels

We prove It{\^o}'s formula for the flow of measures associated with a jump process defined by a drift, an integral with respect to a Poisson random measure and with respect to the associated compensated Poisson random measure. We work in…

Probability · Mathematics 2022-11-30 Thomas Cavallazzi