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We are mainly concerned with equations of the form $-Lu=f(x,u)+\mu$, where $L$ is an operator associated with a quasi-regular possibly nonsymmetric Dirichlet form, $f$ satisfies the monotonicity condition and mild integrability conditions,…

Analysis of PDEs · Mathematics 2016-06-17 Tomasz Klimsiak , Andrzej Rozkosz

In these notes we propose and analyze an inertial type method for obtaining stable approximate solutions to nonlinear ill-posed operator equations. The method is based on the Levenberg-Marquardt (LM) iteration. The main obtained results…

Numerical Analysis · Mathematics 2024-06-12 Antonio Leitão , Joel C. Rabelo , Dirk A. Lorenz , Maximilian Winkler

We consider adaptive finite element methods for second-order elliptic PDEs, where the arising discrete systems are not solved exactly. For contractive iterative solvers, we formulate an adaptive algorithm which monitors and steers the…

Numerical Analysis · Mathematics 2021-07-14 Gregor Gantner , Alexander Haberl , Dirk Praetorius , Stefan Schimanko

We establish some existence and regularity results to the Dirichlet problem, for a class of quasilinear elliptic equations involving a partial differential operator, depending on the gradient of the solution. Our results are formulated in…

Analysis of PDEs · Mathematics 2022-07-22 Giuseppina Barletta , Elisabetta Tornatore

This paper considers the quantile regression approach for partially linear spatial autoregressive models with possibly varying coefficients. B-spline is employed for the approximation of varying coefficients. The instrumental variable…

Methodology · Statistics 2016-08-08 Xiaowen Dai , Shaoyang Li , Maozai Tian

In this paper, we discuss the solution of certain matrix-valued partial differential equations. Such PDEs arise, for example, when constructing a Riemannian contraction metric for a dynamical system given by an autonomous ODE. We develop…

Numerical Analysis · Mathematics 2017-06-29 Peter Giesl , Holger Wendland

Recent work on Path-Dependent Partial Differential Equations (PPDEs) has shown that PPDE solutions can be approximated by a probabilistic representation, implemented in the literature by the estimation of conditional expectations using…

Machine Learning · Computer Science 2022-10-05 Jiang Yu Nguwi , Nicolas Privault

In this paper, we consider an elliptic operator obtained as the superposition of a classical second-order differential operator and a nonlocal operator of fractional type. Though the methods that we develop are quite general, for…

Analysis of PDEs · Mathematics 2020-06-11 Stefano Biagi , Serena Dipierro , Enrico Valdinoci , Eugenio Vecchi

For weak dispersion and weak dissipation cases, the (1+1)-dimensional KdV-Burgers equation is investigated in terms of approximate symmetry reduction approach. The formal coherence of similarity reduction solutions and similarity reduction…

Exactly Solvable and Integrable Systems · Physics 2015-05-13 Xiaoyu Jiao , Ruoxia Yao , Shunli Zhang , S. Y. Lou

In this article, we analyze the approximation properties of the new family of Durrmeyer type exponential sampling operators. We derive the point-wise and uniform approximation theorem and Voronovskaya type theorem for these generalized…

Functional Analysis · Mathematics 2020-08-11 Shivam Bajpeyi , A. Sathish Kumar

We study elliptic gradient systems with fractional laplacian operators on the whole space $$ (- \Delta)^\mathbf s \mathbf u =\nabla H (\mathbf u) \ \ \text{in}\ \ \mathbf{R}^n,$$ where $\mathbf u:\mathbf{R}^n\to \mathbf{R}^m$, $H\in…

Analysis of PDEs · Mathematics 2015-11-16 Mostafa Fazly , Yannick Sire

This paper is aimed to prove a quantitative estimate (in terms of the modulus of continuity) for the convergence in the nonlinear version of Korovkin's theorem for sequences of weakly nonlinear and monotone operators defined on spaces of…

Functional Analysis · Mathematics 2024-04-18 Sorin G. Gal , Constantin P. Niculescu

Kernel theorems, in general, provide a convenient representation of bounded linear operators. For the operator acting on a concrete function space, this means that its action on any element of the space can be expressed as a generalised…

Functional Analysis · Mathematics 2024-05-22 Dimitri Bytchenkoff , Michael Speckbacher , Peter Balazs

In this paper, we propose a low rank approximation method for efficiently solving stochastic partial differential equations. Specifically, our method utilizes a novel low rank approximation of the stiffness matrices, which can significantly…

Numerical Analysis · Mathematics 2023-10-20 Yujun Zhu , Ju Ming , Jie Zhu , Zhongming Wang

We provide a new method to approximate a (possibly discontinuous) function using Christoffel-Darboux kernels. Our knowledge about the unknown multivariate function is in terms of finitely many moments of the Young measure supported on the…

Optimization and Control · Mathematics 2021-04-09 Swann Marx , Edouard Pauwels , Tillmann Weisser , Didier Henrion , Jean Lasserre

Recent advances in the theory of Neural Operators (NOs) have enabled fast and accurate computation of the solutions to complex systems described by partial differential equations (PDEs). Despite their great success, current NO-based…

Machine Learning · Computer Science 2024-03-18 Ashutosh Singh , Ricardo Augusto Borsoi , Deniz Erdogmus , Tales Imbiriba

This article is about the (minimal) sector containing the numerical range of the principal part of a linear second-order elliptic differential operator defined by a form on closed subspaces V of the first-order Sobolev space…

Functional Analysis · Mathematics 2025-10-28 Hannes Meinlschmidt , Joachim Rehberg

The purpose of this work is to investigate root finding problems defined on (quasi-)metric spaces, and ranging in Euclidean spaces. The motivation for this line of inquiry stems from recent models in biology and phylogenetics, where…

Optimization and Control · Mathematics 2025-10-28 Titus Pinta

In this paper, we establish a comprehensive characterization of the generalized Lipschitz classes through the study of the rate of convergence of a family of semi-discrete sampling operators, of Durrmeyer type, in $L^p$-setting. To achieve…

Functional Analysis · Mathematics 2025-11-14 Danilo Costarelli , Michele Piconi , Gianluca Vinti

We provide a framework for the sparse approximation of multilinear problems and show that several problems in uncertainty quantification fit within this framework. In these problems, the value of a multilinear map has to be approximated…

Numerical Analysis · Mathematics 2018-07-17 Fabio Nobile , Raul Tempone , Soeren Wolfers
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