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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 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

Stochastic differential equations (SDEs) are popular tools to analyse time series data in many areas, such as mathematical finance, physics, and biology. They provide a mechanistic description of the phenomeon of interest, and their…

Methodology · Statistics 2021-02-01 Théo Michelot , Richard Glennie , Catriona Harris , Len Thomas

We are interested in (uniformly) parabolic PDEs with a nonlinear dependance of the leading-order coefficients, driven by a rough right hand side. For simplicity, we consider a space-time periodic setting with a single spatial variable:…

Analysis of PDEs · Mathematics 2018-11-07 Felix Otto , Hendrik Weber

We consider differential equations driven by rough paths and study the regularity of the laws and their long time behavior. In particular, we focus on the case when the driving noise is a rough path valued fractional Brownian motion with…

Probability · Mathematics 2013-07-25 Martin Hairer , Natesh S. Pillai

In this paper we investigate two variants of $\alpha$-stable processes, namely tempered stable subordinators and modified tempered stable process as well as their renormalization. We study the weak convergence in the Skorohod space and…

Probability · Mathematics 2017-08-23 Jose Luis da Silva , Mohamed Erraoui

In this paper, we deal with Reflected Backward Stochastic Differential Equations for which the constraint is not on the paths of the solution but on its law as introduced by Briand, Elie and Hu in [3]. We extend the recent work [2] of…

Probability · Mathematics 2021-08-20 Philippe Briand , Hélène Hibon

We show well-posedness for McKean--Vlasov equations with rough common noise and progressively measurable coefficients. Our results are valid under natural regularity assumptions on the coefficients, in agreement with the respective…

Probability · Mathematics 2025-07-18 Peter K. Friz , Antoine Hocquet , Khoa Lê

The regularity and characterization of solutions to degenerate, quasilinear SPDE is studied. Our results are two-fold: First, we prove regularity results for solutions to certain degenerate, quasilinear SPDE driven by Lipschitz continuous…

Probability · Mathematics 2014-05-23 Benjamin Gess , Michael Röckner

A new explicit stabilized scheme of weak order one for stiff and ergodic stochastic differential equations (SDEs) is introduced. In the absence of noise, the new method coincides with the classical deterministic stabilized scheme (or…

Numerical Analysis · Mathematics 2018-06-28 Assyr Abdulle , Ibrahim Almuslimani , Gilles Vilmart

In the recent article [Jentzen, A., M\"uller-Gronbach, T., and Yaroslavtseva, L., Commun. Math. Sci., 14(6), 1477--1500, 2016] it has been established that for every arbitrarily slow convergence speed and every natural number $d \in…

Numerical Analysis · Mathematics 2020-06-04 Máté Gerencsér , Arnulf Jentzen , Diyora Salimova

We study distribution dependent stochastic differential equation driven by a continuous process, without any specification on its law, following the approach initiated in [16]. We provide several criteria for existence and uniqueness of…

Probability · Mathematics 2022-03-07 Lucio Galeati , Fabian A. Harang , Avi Mayorcas

Stochastic partial differential equations (SPDEs) are ubiquitous in engineering and computational sciences. The stochasticity arises as a consequence of uncertainty in input parameters, constitutive relations, initial/boundary conditions,…

Data Analysis, Statistics and Probability · Physics 2020-01-29 Sharmila Karumuri , Rohit Tripathy , Ilias Bilionis , Jitesh Panchal

In the study of partial differential equations (PDEs) with random initial data and singular stochastic PDEs with random forcing, we typically decompose a classically ill-defined solution map into two steps, where, in the first step, we use…

Analysis of PDEs · Mathematics 2024-09-12 Tadahiro Oh , Mamoru Okamoto , Oana Pocovnicu , Nikolay Tzvetkov

Mechanistic knowledge about the physical world is virtually always expressed via partial differential equations (PDEs). Recently, there has been a surge of interest in probabilistic PDE solvers -- Bayesian statistical models mostly based on…

Machine Learning · Computer Science 2025-03-12 Tim Weiland , Marvin Pförtner , Philipp Hennig

In this paper, we accomplish the existence and stability of the solution of a class of delay rough partial differential equations (DRPDEs). Moreover, we prove that the solution of DRPDEs can converge to that of RPDEs in sense of some…

Probability · Mathematics 2024-08-19 Shiduo Qu , Hongjun Gao

This paper presents theoretical advances in the application of the Stochastic Partial Differential Equation (SPDE) approach in geostatistics. We show a general approach to construct stationary models related to a wide class of linear SPDEs,…

Statistics Theory · Mathematics 2018-07-30 Ricardo Carrizo Vergara , Denis Allard , Nicolas Desassis

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

Using purely probabilistic methods, we prove the existence and the uniqueness of solutions fora system of coupled forward-backward stochastic differential equations (FBSDEs) with measurable, possibly discontinuous coefficients. As a…

Probability · Mathematics 2021-10-12 Kihun Nam , Yunxi Xu

This paper studies stabilities of stochastic differential equation (SDE) driven by time-changed L\'evy noise in both probability and moment sense. This provides more flexibility in modeling schemes in application areas including physics,…

Probability · Mathematics 2016-04-27 Erkan Nane , Yinan Ni