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The stochastic partial differential equation (SPDE) approach is widely used for modeling large spatial datasets. It is based on representing a Gaussian random field $u$ on $\mathbb{R}^d$ as the solution of an elliptic SPDE $L^\beta u =…

Methodology · Statistics 2023-07-31 David Bolin , Alexandre B. Simas , Zhen Xiong

Nonlocal quantum theory of one-component scalar field in $D$-dimensional Euclidean spacetime is studied in representations of $\mathcal{S}$-matrix theory for both polynomial and nonpolynomial interaction Lagrangians. The theory is…

High Energy Physics - Theory · Physics 2019-02-22 I. V. Chebotarev , V. A. Guskov , S. L. Ogarkov , M. Bernard

We propose a general analytical framework for single-facility continuous location problems under spatial demand uncertainty. In contrast to classical formulations based on discrete or regionally aggregated demands, the proposed model…

Optimization and Control · Mathematics 2025-11-05 Víctor Blanco , Miguel Martínez-Antón

This paper introduces a set of numerical methods for Riemannian shape analysis of 3D surfaces within the setting of invariant (elastic) second-order Sobolev metrics. More specifically, we address the computation of geodesics and geodesic…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Emmanuel Hartman , Yashil Sukurdeep , Eric Klassen , Nicolas Charon , Martin Bauer

The classical local Neumann problem is well studied and solutions of this problem lie, in general, in a Sobolev space. In this work, we focus on nonlocal Neumann problems with measurable, nonnegative kernels, whose solutions require less…

Analysis of PDEs · Mathematics 2022-08-11 Leonhard Frerick , Christian Vollmann , Michael Vu

Many inverse problems arising in engineering and applied sciences involve unknown quantities with pronounced spatial inhomogeneity, such as localized defects or spatially varying material properties, making reliable uncertainty…

Numerical Analysis · Mathematics 2026-02-10 Babak Maboudi Afkham , Tomas Soto , Mirza Karamehmedovic , Lassi Roininen

This paper addresses the inference of spatial dependence in the context of a recently proposed framework. More specifically, the paper focuses on the estimation of model parameters for a class of generalized Gibbs random fields, i.e.,…

Statistics Theory · Mathematics 2007-06-13 Samuel Elogne , Dionisis Hristopulos

We deal with the Sobolev space theory for the stochastic partial differential equation (SPDE) driven by Wiener processes $$ \partial_{t}^{\alpha}u=\left( \phi(\Delta) u +f(u) \right) + \partial_t^\beta \sum_{k=1}^\infty \int_0^t…

Probability · Mathematics 2022-05-24 Kyeong-Hun Kim , Daehan Park , Junhee Ryu

In this paper we study parabolic stochastic partial differential equations defined on arbitrary bounded domain $\cO \subset \bR^d$ allowing Hardy inequality: $$ \int_{\cO}|\rho^{-1}g|^2\,dx\leq C\int_{\cO}|g_x|^2 dx, \quad \forall g\in…

Probability · Mathematics 2011-09-23 Kyeong-Hun Kim

We develop a variational framework for addressing two-dimensional non-integrable quantum field theories through the exact structure of their integrable counterparts. Concentrating on the $\varphi^4$ Landau-Ginzburg model, we use the…

High Energy Physics - Theory · Physics 2025-12-19 Arthur Hutsalyuk , Márton Lájer , Giuseppe Mussardo , Andrea Stampiggi

The parabolic integro-differential Cauchy problem with spatially dependent coefficients is considered in generalized Bessel potential spaces where smoothness is defined by L\'evy measures with O-regularly varying profile. The coefficients…

Analysis of PDEs · Mathematics 2023-08-31 Sutawas Janreung , Tatpon Siripraparat , Chukiat Saksurakan

This paper develops the necessary ingredients for the variational approach of initial boundary-value problems of parabolic partial differential equations on a fixed spatial domain containing evolving subdomains. In particular, we introduce…

Analysis of PDEs · Mathematics 2025-10-17 Van Chien Le , Karel Van Bockstal

We establish Schauder-type estimates for linear parabolic systems driven by variable-coefficient nonlocal pseudo-differential operators of order $s>0$. These estimates are formulated in critical time-weighted H\"older/Besov-type spaces and…

Analysis of PDEs · Mathematics 2026-04-14 Ke Chen , Ruilin Hu , Quoc-Hung Nguyen

There exists a plethora of parametric models for positive definite kernels, and their use is ubiquitous in disciplines as diverse as statistics, machine learning, numerical analysis, and approximation theory. Usually, the kernel parameters…

Machine Learning · Statistics 2025-01-06 Xavier Emery , Emilio Porcu , Moreno Bevilacqua

Series expansions of isotropic Gaussian random fields on $\mathbb{S}^2$ with independent Gaussian coefficients and localized basis functions are constructed. Such representations with multilevel localised structure provide an alternative to…

Probability · Mathematics 2022-06-27 Markus Bachmayr , Ana Djurdjevac

In this paper, we develop some properties of the $a_{x,y}(\cdot)$-Neumann derivative for the nonlocal $s(\cdot,\cdot)$-order operator in fractional Musielak-Sobolev spaces with variable $s(\cdot,\cdot)-$order. Therefore we prove the basic…

Analysis of PDEs · Mathematics 2024-12-17 Mohammed Srati

This paper investigates the mathematical properties and numerical approximation of a class of nonlocal elliptic partial differential equations of the form \begin{equation*} -\Delta u + \lambda \, G(u) = f, \end{equation*} where $\Delta$…

Analysis of PDEs · Mathematics 2026-02-09 Dragos-Patru Covei

While General Fractional Calculus has successfully expanded the scope of memory operators beyond power-laws, standard formulations remain predominantly restricted to the half-line via Riemann-Liouville or Caputo definitions. This constraint…

Functional Analysis · Mathematics 2026-01-16 Gustavo Dorrego

This paper investigates the numerical approximation of integrals for functions in fractional Gaussian Sobolev spaces $W^s_{p}(\mathbb{R}^d,\gamma)$ with dominating mixed smoothness defined via kernel related to the fractional…

Numerical Analysis · Mathematics 2026-04-21 Van Kien Nguyen

We propose and analyse a new type of fully discrete finite element approximation of a class of linear stochastic parabolic evolution equations with additive noise. Our discretization differs from previous ones in that we use a finite…

Numerical Analysis · Mathematics 2025-01-23 Øyvind Stormark Auestad , Geir-Arne Fuglstad , Espen Robstad Jakobsen , Annika Lang
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