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We study identifiability of stochastic differential equations (SDE) under multiple interventions. Our results give the first provable bounds for unique recovery of SDE parameters given samples from their stationary distributions. We give…

Machine Learning · Computer Science 2025-11-18 Aaron Zweig , Zaikang Lin , Elham Azizi , David Knowles

We show that perturbing ill-posed differential equations with (potentially very) smooth random processes can restore well-posedness -- even if the perturbation is (potentially much) more regular than the drift component of the solution. The…

Probability · Mathematics 2024-09-25 Máté Gerencsér

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

McKean-Vlasov SDEs describe systems where the dynamics depend on the law of the process. The corresponding Fokker-Planck equation is a nonlinear, nonlocal PDE for the corresponding measure flow. In the presence of common noise and…

Probability · Mathematics 2025-07-24 Fabio Bugini , Peter K. Friz , Wilhelm Stannat

We obtain uniqueness and existence of a solution $u$ to the following second-order stochastic partial differential equation (SPDE) : \begin{align} \label{abs eqn} du= \left( \bar a^{ij}(\omega,t)u_{x^ix^j}+ f \right)dt + g^k dw^k_t, \quad t…

Probability · Mathematics 2020-11-24 Ildoo Kim

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

We study the interplay between the regularity of paths and Hamiltonians in the theory of pathwise Hamilton-Jacobi equations with the use of interpolation methods. The regularity of the paths is measured with respect to Sobolev, Besov,…

Analysis of PDEs · Mathematics 2021-01-19 Pierre-Louis Lions , Benjamin Seeger , Panagiotis Souganidis

The main goal of this article is to study the effect of small, highly nonlinear, unbounded drifts (small time large deviation principle (LDP) based on exponential equivalence arguments) for a class of stochastic partial differential…

Probability · Mathematics 2022-12-27 Ankit Kumar , Manil T. Mohan

Under the uniform H\"{o}rmander's hypothesis we study smoothness and exponential bounds of the density of the law of the solution of a stochastic differential equation (SDE) with locally Lipschitz drift that satisfy a monotonicity…

Probability · Mathematics 2024-07-23 Cristina Anton

SDE's must be solved in the "anti-Ito" sense when their coefficients are independent. While the "noise-induced drift" matters for the sample paths, it is absent in the Fokker-Planck equation, which takes a particularly simple form and is…

Mathematical Physics · Physics 2016-05-12 Dietrich Ryter

In this paper we prove an approximation result for the viscosity solution of a system of semi-linear partial differential equations with continuous coefficients and nonlinear Neumann boundary condition. The approximation we use is based on…

Probability · Mathematics 2015-10-30 Khaled Bahlali , Lucian Maticiuc , Adrian Zalinescu

We extend our recently introduced stochastic nonlocal traffic flow model to more general random perturbations, including Markovian noise derived from a discretized Jacobi-type stochastic differential equation. Invoking a deterministic…

Numerical Analysis · Mathematics 2026-03-26 Timo Böhme , Simone Göttlich , Andreas Neuenkirch

This thesis is concerned with the asymptotic behavior of solutions of stochastic $p$-Laplace equations driven by non-autonomous forcing on $\mathbb{R}^n$. Two cases are studied, with additive and multiplicative noise respectively. Estimates…

Analysis of PDEs · Mathematics 2014-08-05 Andrew Krause

Modelling statistical relationships beyond the conditional mean is crucial in many settings. Conditional density estimation (CDE) aims to learn the full conditional probability density from data. Though highly expressive, neural network…

Machine Learning · Statistics 2020-02-17 Jonas Rothfuss , Fabio Ferreira , Simon Boehm , Simon Walther , Maxim Ulrich , Tamim Asfour , Andreas Krause

In this paper, we study the existence of random periodic solutions for semilinear stochastic partial differential equations with multiplicative linear noise on a bounded open domain ${\cal O}\subset {\mathbb R}^d$ with smooth boundary. We…

Probability · Mathematics 2018-03-02 Chunrong Feng , Yue Wu , Huaizhong Zhao

We study the second-order quasi-linear stochastic partial differential equations (SPDEs) defined on $C^1$ domains. The coefficients are random functions depending on $t,x$ and the unknown solutions. We prove the uniqueness and existence of…

Probability · Mathematics 2017-05-05 Ildoo Kim , Kyeong-hun Kim

We present a deep recurrent neural network architecture to solve a class of stochastic optimal control problems described by fully nonlinear Hamilton Jacobi Bellmanpartial differential equations. Such PDEs arise when one considers…

Machine Learning · Computer Science 2019-12-24 Marcus A Pereira , Ziyi Wang , Tianrong Chen , Emily Reed , Evangelos A Theodorou

We consider the generalised Surface Quasi-Geostrophic (gSQG) equations in $\mathbb R^2$ with parameter $\beta\in (0,1)$, an active scalar model interpolating between SQG ($\beta=1$) and the 2D Euler equations ($\beta=0$) in vorticity form.…

Probability · Mathematics 2025-03-28 Marco Bagnara , Lucio Galeati , Mario Maurelli

By using a regularity approximation argument, the global existence and uniqueness are derived for a class of nonlinear SPDEs depending on both the whole history and the distribution under strong enough noise. As applications, the global…

Analysis of PDEs · Mathematics 2022-03-04 Panpan Ren , Hao Tang , Feng-Yu Wang

We demonstrate that the conventional path integral formulations generate inconsistent results exemplified by the geometric Brownian motion under the general stochastic interpretation. We thus develop a novel path integral formulation for…

Statistical Mechanics · Physics 2015-06-18 Ying Tang , Ruoshi Yuan , Ping Ao