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In this manuscript we establish local H\"older regularity estimates for bounded solutions of a certain class of doubly degenerate evolution PDEs. By making use of intrinsic scaling techniques and geometric tangential methods, we derive…

Analysis of PDEs · Mathematics 2021-03-17 J. V. Silva , Elzon C. Júnior , Gleydson C. Ricarte

We consider a class of stochastic PDEs of Burgers type in spatial dimension 1, driven by space-time white noise. Even though it is well known that these equations are well posed, it turns out that if one performs a spatial discretization of…

Probability · Mathematics 2012-07-31 Martin Hairer , Jan Maas

Stochastic quantization in physics has been considered to provide a path integral representation of a probability distribution for Ito processes. It has been indicated that the stochastic quantization can involve a potential term, if the…

Systems and Control · Computer Science 2020-05-05 Masakazu Sano

We prove the Ito-Tanaka formula and the existence of pathwise stochastic integrals for a wide class of Gaussian processes. Motivated by financial applications, we define the stochastic integrals as forward-type pathwise integrals introduced…

Probability · Mathematics 2014-12-05 Tommi Sottinen , Lauri Viitasaari

I propose a novel framework that integrates stochastic differential equations (SDEs) with deep generative models to improve uncertainty quantification in machine learning applications involving structured and temporal data. This approach,…

Machine Learning · Statistics 2026-01-09 James Rice

After defining non-Gaussian L\'evy processes for two-sided time, stochastic differential equations with such L\'evy processes are considered. Solution paths for these stochastic differential equations have countable jump discontinuities in…

Probability · Mathematics 2012-10-03 Huijie Qiao , Jinqiao Duan

We study a numerical method to compute probability density functions of solutions of stochastic differential equations. The method is sometimes called the numerical path integration method and has been shown to be fast and accurate in…

Dynamical Systems · Mathematics 2016-11-29 Linghua Chen , Espen Robstad Jakobsen , Arvid Naess

In this article, we give a new proof of the It\^o formula for some integral processes related to the space-time L\'evy white noise introduced in Balan (2015) as an alternative for the Gaussian white noise perturbing an SPDE. We discuss two…

Probability · Mathematics 2015-05-19 Raluca M. Balan , Cheikh B. Ndongo

*The gradient discretisation method (GDM) is a generic framework, covering many classical methods (Finite Elements, Finite Volumes, Discontinuous Galerkin, etc.), for designing and analysing numerical schemes for diffusion models. In this…

Numerical Analysis · Mathematics 2021-01-01 Jerome Droniou , Beniamin Goldys , Kim-Ngan Le

We investigate several aspects of solutions to stochastic evolution equations in Hilbert spaces driven by a standard symmetric $\alpha$-stable cylindrical noise. Similarly to cylindrical Brownian motion or Gaussian white noise, standard…

Probability · Mathematics 2024-02-05 Gergely Bodó , Ondřej Týbl , Markus Riedle

This paper deals with the drift estimation in linear stochastic evolution equations (with emphasis on linear SPDEs) with additive fractional noise (with Hurst index ranging from 0 to 1) via least-squares procedure. Since the least-squares…

Probability · Mathematics 2022-03-11 Pavel Kříž , Jana Šnupárková

This paper introduces a comprehensive extension of the path integral formalism to model stochastic processes with arbitrary multiplicative noise. To do so, It\^o diffusive process is generalized by incorporating a multiplicative noise term…

Mathematical Physics · Physics 2025-03-06 F. S. Abril-Bermúdez , C. J. Quimbay , J. E. Trinidad-Segovia , M. A Sánchez-Granero

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

We view the classical Lindeberg principle in a Markov process setting to establish a probability approximation framework by the associated It\^{o}'s formula and Markov operator. As applications, we study the error bounds of the following…

Probability · Mathematics 2022-06-15 Peng Chen , Qi-Man Shao , Lihu Xu

The time evolution problem for non-self adjoint second order differential operators is studied by means of the path integral formulation. Explicit computation of the path integral via the use of certain underlying stochastic differential…

Mathematical Physics · Physics 2021-07-20 Anastasia Doikou , Simon J. A. Malham , Anke Wiese

In this paper we extend an inequality of Lenglart, L\'epingle and Pratelli \cite[Lemma 1.1]{LLP} to general continuous adapted stochastic processes with values in topology spaces. By this inequality we show Burkholder-Davies-Gundy's…

Probability · Mathematics 2016-06-15 Yingchao Xie , Xicheng Zhang

We prove a new Burkholder-Rosenthal type inequality for discrete-time processes taking values in a 2-smooth Banach space. As a first application we prove that if $(S(t,s))_{0\leq s\leq T}$ is a $C_0$-evolution family of contractions on a…

Probability · Mathematics 2021-07-13 Jan van Neerven , Mark Veraar

Given a Gaussian stationary increment processes with spectral density, we show that a Wick-Ito integral with respect to this process can be naturally obtained using Hida's white noise space theory. We use the Bochner-Minlos theorem to…

Probability · Mathematics 2012-02-09 Daniel Alpay , Alon Kipnis

The present article delves into the investigation of observability inequalities pertaining to backward stochastic evolution equations. We employ a combination of spectral inequalities, interpolation inequalities, and the telegraph series…

Optimization and Control · Mathematics 2023-08-23 Yuanhang Liu , Weijia Wu , Donghui Yang , Jie Zhong

This paper develops a systematic parametric method for analyzing stochastic systems under volatility uncertainty within the $G$-expectation framework. Leveraging the dual representation of the $G$-expectation as a supremum over a family of…

Probability · Mathematics 2025-11-27 Guangqian Zhao
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