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We study existence and regularity of the density for the solution $u(t,x)$ (with fixed $t > 0$ and $x \in D$) of the heat equation in a bounded domain $D \subset \mathbb R^d$ driven by a stochastic inhomogeneous Neumann boundary condition…

Probability · Mathematics 2018-12-27 Stefano Bonaccorsi , Margherita Zanella

We construct solutions to Burgers type equations perturbed by a multiplicative space-time white noise in one space dimension. Due to the roughness of the driving noise, solutions are not regular enough to be amenable to classical methods.…

Probability · Mathematics 2016-06-02 Martin Hairer , Hendrik Weber

We examine the relation between a stochastic version of the rough path integral with the symmetric-Stratonovich integral in the sense of regularization. Under mild regularity conditions in the sense of Malliavin calculus, we establish…

Probability · Mathematics 2023-09-18 Alberto Ohashi , Francesco Russo

In this paper we establish a substitution formula for stochastic differential equation driven by generalized grey noise. We then apply this formula to investigate the absolute continuity of the solution with respect to the Lebesgue measure…

Probability · Mathematics 2014-12-16 José Luís da Silva , Mohamed Erraoui

We prove quantitative convergence rates at which discrete Langevin-like processes converge to the invariant distribution of a related stochastic differential equation. We study the setup where the additive noise can be non-Gaussian and…

Machine Learning · Computer Science 2020-11-20 Xiang Cheng , Dong Yin , Peter L. Bartlett , Michael I. Jordan

In this paper, tight upper and lower bounds are derived on the weighted sum of minimum mean-squared errors for additive Gaussian noise channels. The bounds are obtained by constraining the input distribution to be close to a Gaussian…

Information Theory · Computer Science 2020-01-23 Michael Fauß , Abdelhak M. Zoubir , Alex Dytso , H. Vincent Poor , K. G. Nagananda

We obtain non asymptotic bounds for the Monte Carlo algorithm associated to the Euler discretization of some diffusion processes. The key tool is the Gaussian concentration satisfied by the density of the discretization scheme. This…

Probability · Mathematics 2018-02-20 Vincent Lemaire , Stephane Menozzi

We consider a system of d non-linear stochastic heat equations in spatial dimension 1 driven by d-dimensional space-time white noise. The non-linearities appear both as additive drift terms and as multipliers of the noise. Using techniques…

Probability · Mathematics 2007-05-23 Robert C. Dalang , Davar Khoshnevisan , Eulalia Nualart

In this paper, we study non-asymptotic deviation bounds of the least squares estimator in Gaussian AR($n$) processes. By relying on martingale concentration inequalities and a tail-bound for $\chi^2$ distributed variables, we provide a…

Machine Learning · Statistics 2020-05-26 Rodrigo A. González , Cristian R. Rojas

We study controlled differential equations driven by a rough path (in the sense of T. Lyons) with an additional, possibly unbounded drift term. We show that the equation induces a solution flow if the drift grows at most linearly.…

Probability · Mathematics 2016-05-19 Sebastian Riedel , Michael Scheutzow

We consider a nonlinear filtering problem for a signal-observation system driven by a Volterra-type Gaussian rough path, whose sample paths may exhibit greater roughness than those of Brownian motion. The observation process includes a…

Probability · Mathematics 2025-07-08 Thomas Cass , Dan Crisan , Andrea Iannucci

The aim of this paper is to obtain estimates for the density of the law of a specific nonlinear diffusion process at any positive bounded time. This process is issued from kinetic theory and is called Landau process, by analogy with the…

Probability · Mathematics 2016-08-16 Hélène Guérin , Sylvie Méléard , Eulalia Nualart

Due to their flexibility, Gaussian processes (GPs) have been widely used in nonparametric function estimation. A prior information about the underlying function is often available. For instance, the physical system (computer model output)…

Methodology · Statistics 2017-11-21 Hassan Maatouk

We consider slow-fast systems of differential equations, in which both the slow and fast variables are perturbed by noise. When the deterministic system admits a uniformly asymptotically stable slow manifold, we show that the sample paths…

Probability · Mathematics 2007-05-23 Nils Berglund , Barbara Gentz

We prove three results on the existence of densities for the laws of finite dimensional functionals of the solutions of the stochastic Navier-Stokes equations in dimension 3. In particular, under very mild assumptions on the noise, we prove…

Probability · Mathematics 2012-03-05 Arnaud Debussche , Marco Romito

Due to recent developments of Malliavin calculus for rough differential equations, it is now known that, under natural assumptions, the law of a unique solution at a fixed time has a smooth density function. Therefore, it is quite natural…

Probability · Mathematics 2020-06-18 Yuzuru Inahama , Bin Pei

We study the existence and uniqueness of solutions to stochastic differential equations with Volterra processes driven by L\'evy noise. For this purpose, we study in detail smoothness properties of these processes. Special attention is…

Probability · Mathematics 2020-08-26 Giulia Di Nunno , Yuliya Mishura , Kostiantyn Ralchenko

We consider the one-dimensional stochastic heat and wave equations driven by Gaussian noises with constant initial conditions. We study the spatial average of the solutions on an interval of length $R$ and show that the family of laws of…

Probability · Mathematics 2025-08-05 Masahisa Ebina

We present sufficient conditions for finite controlled rho-variation of the covariance of Gaussian processes with stationary increments, based on concavity or convexity of their variance function. The motivation for this type of conditions…

Probability · Mathematics 2013-11-04 Peter K. Friz , Benjamin Gess , Archil Gulisashvili , Sebastian Riedel

The stochastic partial differential equation analyzed in this work is the Cahn-Hilliard equation perturbed by an additive fractional white noise (fractional in time and white in space). We work in the case of one spatial dimension and apply…

Probability · Mathematics 2026-01-16 Dimitrios Dimitriou , Dimitris Farazakis , Georgia Karali