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We investigate the regularity of linear stochastic parabolic equations with zero Dirichlet boundary condition on bounded Lipschitz domains $O \subset R^d$ with both theoretical and numerical purpose. We use N.V. Krylov's framework of…

Probability · Mathematics 2016-03-31 Petru A. Cioica , Kyeong-Hun Kim , Kijung Lee , Felix Lindner

Gaussian processes are arguably the most important class of spatiotemporal models within machine learning. They encode prior information about the modeled function and can be used for exact or approximate Bayesian learning. In many…

Multivariate Bessel processes $(X_{t,k})_{t\ge0}$ describe interacting particle systems of Calogero-Moser-Sutherland type and are related with $\beta$-Hermite and $\beta$-Laguerre ensembles. They depend on a root system and a multiplicity…

Probability · Mathematics 2020-09-30 Michael Voit , Jeannette H. C. Woerner

This paper considers the properties of Dirichlet Spaces of Homogeneous type which consist of band limited functions that are nearly exponential localizations on $\mathbb{R}^k.$ This is a powerful tool in harmonic analysis and it makes…

Functional Analysis · Mathematics 2025-12-23 J. I. Opadara , M. E. Egwe

We study Cauchy problems associated to elliptic operators acting on vector-valued functions and coupled up to the first-order. We prove pointwise estimates for the spatial derivatives of the semigroup associated to these problems in the…

Analysis of PDEs · Mathematics 2024-12-31 Luciana Angluli , Simone Ferrari , Luca Lorenzi

We propose a principled way to define Gaussian process priors on various sets of unweighted graphs: directed or undirected, with or without loops. We endow each of these sets with a geometric structure, inducing the notions of closeness and…

Machine Learning · Statistics 2023-02-28 Viacheslav Borovitskiy , Mohammad Reza Karimi , Vignesh Ram Somnath , Andreas Krause

In this paper, we present more regularity conditions which ensure the boundedness of dilation operators on Besov and Triebel-Lizorkin spaces equiped with general weights.

Functional Analysis · Mathematics 2020-09-09 Douadi Drihem

The present article is concerned with the nonlinear approximation of functions in the Sobolev space H^q with respect to a tensor-product, or hyperbolic wavelet basis on the unit n-cube. Here, q is a real number, which is not necessarily…

Functional Analysis · Mathematics 2025-11-04 Helmut Harbrecht , Remo von Rickenbach

This paper investigates the traces of functions belonging to the inhomogeneous Besov spaces B $\xi$ p,q , where $\xi$ is a product of capacities defined as powers of Gibbs measures. We first establish that the traces of functions in B $\xi$…

Functional Analysis · Mathematics 2026-03-27 Quentin Rible , Stéphane Seuret

Suppose that P_{\theta}(g) is a linear functional of a Dirichlet process with shape \theta H, where \theta >0 is the total mass and H is a fixed probability measure. This paper describes how one can use the well-known Bayesian prior to…

Statistics Theory · Mathematics 2007-06-13 Lancelot F. James

We study the regularity properties of Gaussian fields defined over spheres cross time. In particular, we consider two alternative spectral decompositions for a Gaussian field on $\mathbb{S}^d \times \mathbb{R}$. For each decomposition, we…

Probability · Mathematics 2018-01-25 Jorge Clarke de La Cerda , Alfredo Alegría , Emilio Porcu , Jorge De La Cerda

Let $\mu$ be a positive finite measure on the unit circle. The Dirichlet type space $\mathcal{D}(\mu)$, associated to $\mu$, consists of holomorphic functions on the unit disc whose derivatives are square integrable when weighted against…

Complex Variables · Mathematics 2014-11-05 O. El-Fallah , Y. Elmadani , K. Kellay

The focus of this work is the convergence of non-stationary and deep Gaussian process regression. More precisely, we follow a Bayesian approach to regression or interpolation, where the prior placed on the unknown function $f$ is a…

Statistics Theory · Mathematics 2025-03-19 Conor Osborne , Aretha L. Teckentrup

This work studies finite sample approximations of the exact and entropic regularized Wasserstein distances between centered Gaussian processes and, more generally, covariance operators of functional random processes. We first show that…

Machine Learning · Statistics 2021-04-27 Minh Ha Quang

We present a novel kernel over the space of probability measures based on the dual formulation of optimal regularized transport. We propose an Hilbertian embedding of the space of probabilities using their Sinkhorn potentials, which are…

Machine Learning · Statistics 2022-10-14 François Bachoc , Louis Béthune , Alberto Gonzalez-Sanz , Jean-Michel Loubes

This work contributes in two areas, with sharp results, to the current investigation of regularity of solutions of heat equations (*) $Pu+\partial_tu=f$ on $\Omega\times I $, where $P$ is a nonlocal operator, and $\Omega \subset R^n$,…

Analysis of PDEs · Mathematics 2018-01-03 Gerd Grubb

Besov spaces with dominating mixed smoothness, on the product of the real line and the torus as well as bounded domains, are studied. A characterization of these function spaces in terms of differences is provided. Applications to random…

Classical Analysis and ODEs · Mathematics 2025-07-30 Paul Nikolaev , David J. Prömel , Mathias Trabs

Roughly speaking, the regular subspace of a Dirichlet form is also a regular Dirichlet form on the same state space. It inherits the same form of original Dirichlet form but possesses a smaller domain. What we are concerned in this paper…

Probability · Mathematics 2015-06-19 Liping Li , Jiangang Ying

We study the Besov regularity of wavelet series on $\mathbb{R}^d$ with randomly chosen coefficients. More precisely, each coefficient is a product of a random factor and a parameterized deterministic factor (decaying with the scale $j$ and…

Probability · Mathematics 2024-11-28 Andreas Horst , Thomas Jahn , Felix Voigtlaender

{We provide a probabilistic approach in order to investigate the smoothness of the solution to the Poisson and Dirichlet problems in $L$-shaped domains. In particular, we obtain (probabilistic) integral representations for the solution. We…

Probability · Mathematics 2017-09-19 Victoria Knopova , René L. Schilling