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In this article, we describe a function fitting method that has potential applications in machine learning and also prove relevant theorems. The described function fitting method is a convex minimization problem and can be solved using a…

Analysis of PDEs · Mathematics 2019-12-17 Rajesh Dachiraju

In this paper, a novel $h$-adaptive isogeometric solver utilizing high-order hierarchical splines is proposed to solve the all-electron Kohn--Sham equation. In virtue of the smooth nature of Kohn--Sham wavefunctions across the domain,…

Computational Physics · Physics 2024-12-18 Tao Wang , Yang Kuang , Ran Zhang , Guanghui Hu

In the frame of isogeometric analysis, we consider a Galerkin boundary element discretization of the hyper-singular integral equation associated with the 2D Laplacian. We propose and analyze an adaptive algorithm which locally refines the…

Numerical Analysis · Mathematics 2020-03-03 Gregor Gantner , Dirk Praetorius , Stefan Schimanko

We propose a predictor-corrector adaptive method for the simulation of hyperbolic partial differential equations (PDEs) on networks under general uncertainty in parameters, initial conditions, or boundary conditions. The approach is based…

Numerical Analysis · Mathematics 2024-03-26 Jake J. Harmon , Svetlana Tokareva , Anatoly Zlotnik

As the resolution of digital images increase significantly, the processing of images becomes more challenging in terms of accuracy and efficiency. In this paper, we consider image segmentation by solving a partial differentiation equation…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Karrar Abbas , Xianping Li

Image segmentation is an inherently ill-posed problem and thus requires regularization in order to limit the search space to reasonable solutions. A majority of segmentation methods integrates these regularization terms in one way or the…

Numerical Analysis · Mathematics 2018-10-31 Uri Nahum , Philippe C. Cattin

We present a trust-region-based adaptive finite-element algorithm for numerically solving a class of nonsmooth PDE-constrained optimization problems that includes problems with sparsifying regularizers and convex constraints. In particular,…

Optimization and Control · Mathematics 2026-04-28 Harbir Antil , Robert J. Baraldi , Rohit Khandelwal , Drew P. Kouri

This paper investigates solution strategies for nonlinear problems in Hilbert spaces, such as nonlinear partial differential equations (PDEs) in Sobolev spaces, when only finite measurements are available. We formulate this as a nonlinear…

Numerical Analysis · Mathematics 2025-06-06 Daozhe Lin , Qiang Du

This paper reviews the state of the art and discusses recent developments in the field of adaptive isogeometric analysis, with special focus on the mathematical theory. This includes an overview of available spline technologies for the…

Numerical Analysis · Mathematics 2022-11-18 Annalisa Buffa , Gregor Gantner , Carlotta Giannelli , Dirk Praetorius , Rafael Vázquez

Mainstream numerical Partial Differential Equation (PDE) solvers require discretizing the physical domain using a mesh. Mesh movement methods aim to improve the accuracy of the numerical solution by increasing mesh resolution where the…

Geometry Independent Field approximaTion (GIFT) was proposed as a generalization of Isogeometric analysis (IGA), where different types of splines are used for the parameterization of the computational domain and approximation of the unknown…

Computational Engineering, Finance, and Science · Computer Science 2022-10-11 Javier Videla , Ahmed Mostafa Shaaban , Elena Atroshchenko

In this contribution, we coupled the isogeometric analysis to a reduced order modelling technique in order to provide a computationally efficient solution in parametric domains. In details, we adopt the free-form deformation method to…

Numerical Analysis · Mathematics 2020-11-23 Fabrizio Garotta , Nicola Demo , Marco Tezzele , Massimo Carraturo , Alessandro Reali , Gianluigi Rozza

The isogeometric approximation of the Stokes problem in a trimmed domain is studied. This setting is characterized by an underlying mesh unfitted with the boundary of the physical domain making the imposition of the essential boundary…

Numerical Analysis · Mathematics 2022-02-02 Riccardo Puppi

This paper is concerned with the numerical minimization of energy functionals in Hilbert spaces involving convex constraints coinciding with a semi-norm for a subspace. The optimization is realized by alternating minimizations of the…

Numerical Analysis · Mathematics 2007-12-17 Massimo Fornasier , Carola-Bibiane Schönlieb

We present a new isogeometric method for the discretization of the Reissner-Mindlin plate bending problem. The proposed scheme follows a recent theoretical framework that makes possible to construct a space of smooth discrete deflections…

Numerical Analysis · Mathematics 2015-05-28 L. Beirão da Veiga , A. Buffa , C. Lovadina , M. Martinelli , G. Sangalli

The perfectly matched layer (PML) formulation is a prominent way of handling radiation problems in unbounded domain and has gained interest due to its simple implementation in finite element codes. However, its simplicity can be advanced…

Numerical Analysis · Mathematics 2022-10-04 Jon Vegard Venås , Trond Kvamsdal

We develop a new spatial semidiscrete multiscale method based upon the edge multiscale methods to solve semilinear parabolic problems with heterogeneous coefficients and smooth initial data. This method allows for a cheap spatial…

Numerical Analysis · Mathematics 2025-12-16 Leonardo A. Poveda , Shubin Fu , Guanglian Li , Eric Chung

We consider geometric multigrid methods for the solution of linear systems arising from isogeometric discretizations of elliptic partial differential equations. For classical finite elements, such methods are well known to be fast solvers…

Numerical Analysis · Mathematics 2017-05-16 Clemens Hofreither , Stefan Takacs , Walter Zulehner

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It…

Numerical Analysis · Mathematics 2019-01-23 Anthony Nouy , Florent Pled

In this paper we investigate and compare different gradient algorithms designed for the domain expression of the shape derivative. Our main focus is to examine the usefulness of kernel reproducing Hilbert spaces for PDE constrained shape…

Optimization and Control · Mathematics 2016-04-20 Martin Eigel , Kevin Sturm
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