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We present a rigorous convergence analysis for cylindrical approximations of nonlinear functionals, functional derivatives, and functional differential equations (FDEs). The purpose of this analysis is twofold: first, we prove that…

Numerical Analysis · Mathematics 2021-03-17 Daniele Venturi , Alec Dektor

When numerically solving partial differential equations (PDEs), the first step is often to discretize the geometry using a mesh and to solve a corresponding discretization of the PDE. Standard finite and spectral element methods require…

Analysis of PDEs · Mathematics 2018-03-30 Aaron Yeiser , Advisor Alex Townsend

We develop a new meshfree geometric multilevel (MGM) method for solving linear systems that arise from discretizing elliptic PDEs on surfaces represented by point clouds. The method uses a Poisson disk sampling-type technique for coarsening…

Numerical Analysis · Mathematics 2022-04-14 Grady B. Wright , Andrew M. Jones , Varun Shankar

We propose and analyse a novel surface finite element method that preserves the invariant regions of systems of semilinear parabolic equations on closed compact surfaces in $\mathbb{R}^3$ under discretisation. We also provide a…

Numerical Analysis · Mathematics 2020-01-20 Massimo Frittelli , Anotida Madzvamuse , Ivonne Sgura , Chandrasekhar Venkataraman

We present in this paper a rigorous theoretical framework to show stability, convergence and accuracy of improved edge-based and face-based smoothed finite element methods (bESFEM and bFS-FEM) for nearly-incompressible elasticity problems.…

Numerical Analysis · Mathematics 2016-11-26 Thanh Hai Ong , Claire E. Heaney , Chang-Kye Lee , G. R. Liu , H. Nguyen-Xuan

In this paper, we propose a general approach called Generalized Multiscale Finite Element Method (GMsFEM) for performing multiscale simulations for problems without scale separation over a complex input space. As in multiscale finite…

Numerical Analysis · Mathematics 2015-06-12 Yalchin Efendiev , Juan Galvis , Thomas Y. Hou

A fundamental problem in modern supervised learning is computing reliable conditional prediction intervals in high-dimensional settings: existing methods often rely on restrictive modelling assumptions, do not scale as predictor dimension…

Machine Learning · Statistics 2026-02-24 Daniel Salnikov , Dan Leonte , Kevin Michalewicz

This paper considers flow problems in multiscale heterogeneous porous media. The multiscale nature of the modeled process significantly complicates numerical simulations due to the need to compute huge and ill-conditioned sparse matrices,…

Numerical Analysis · Mathematics 2024-10-16 Djulustan Nikiforov , Leonardo A. Poveda , Dmitry Ammosov , Yesy Sarmiento , Juan Galvis

Based on the radial basis function (RBF), non-singular general solution and dual reciprocity method (DRM), this paper presents an inherently meshless, integration-free, boundary-only RBF collocation techniques for numerical solution of…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 W. Chen , M. Tanaka

This work is concerned with the formulation of a general framework for the analysis of meshfree approximation schemes and with the convergence analysis of the Local Maximum-Entropy (LME) scheme as a particular example. We provide conditions…

Numerical Analysis · Mathematics 2011-08-01 Agustin Bompadre , Bernd Schmidt , Michael Ortiz

We develop a sparse hierarchical $hp$-finite element method ($hp$-FEM) for the Helmholtz equation with variable coefficients posed on a two-dimensional disk or annulus. The mesh is an inner disk cell (omitted if on an annulus domain) and…

Numerical Analysis · Mathematics 2025-07-10 Ioannis P. A. Papadopoulos , Sheehan Olver

Lensless imaging stands out as a promising alternative to conventional lens-based systems, particularly in scenarios demanding ultracompact form factors and cost-effective architectures. However, such systems are fundamentally governed by…

Image and Video Processing · Electrical Eng. & Systems 2025-05-06 Jiesong Bai , Yuhao Yin , Yihang Dong , Xiaofeng Zhang , Chi-Man Pun , Xuhang Chen

This paper proposes a mesh-free computational framework and machine learning theory for solving elliptic PDEs on unknown manifolds, identified with point clouds, based on diffusion maps (DM) and deep learning. The PDE solver is formulated…

Numerical Analysis · Mathematics 2024-02-28 Senwei Liang , Shixiao W. Jiang , John Harlim , Haizhao Yang

Recent developments in mechanical, aerospace, and structural engineering have driven a growing need for efficient ways to model and analyse structures at much larger and more complex scales than before. While established numerical methods…

Machine Learning · Computer Science 2025-07-29 Rui Wu , Nikola Kovachki , Burigede Liu

Strong-form meshless methods received much attention in recent years and are being extensively researched and applied to a wide range of problems in science and engineering. However, the solution of elasto-plastic problems has proven to be…

Numerical Analysis · Mathematics 2023-10-02 Gašper Vuga , Boštjan Mavrič , Božidar Šarler

This article introduces a general purpose framework and software to approximate partial differential equations (PDEs). The sparsity patterns of finite element discretized operators is identified automatically using the tools from…

Numerical Analysis · Mathematics 2024-10-17 Kiefer Green , Harbir Antil

Particle-based shape modeling (PSM) is a popular approach to automatically quantify shape variability in populations of anatomies. The PSM family of methods employs optimization to automatically populate a dense set of corresponding…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Hong Xu , Shireen Y. Elhabian

The pseudopotential model within the Lattice Boltzmann Method (LBM) framework has emerged as a prominent approach in computational fluid dynamics due to its dual strengths in physical intuitiveness and computational tractability. However,…

Fluid Dynamics · Physics 2025-09-03 Yizhong Chen , Zhibin Wang

Meshfree solution schemes for the incompressible Navier--Stokes equations are usually based on algorithms commonly used in finite volume methods, such as projection methods, SIMPLE and PISO algorithms. However, drawbacks of these algorithms…

Numerical Analysis · Mathematics 2018-02-02 Pratik Suchde , Joerg Kuhnert , Sudarshan Tiwari

This paper reviews standard oversampling strategies as performed in the Multiscale Finite Element Method (MsFEM). Common to those approaches is that the oversampling is performed in the full space restricted to a patch but including coarse…

Numerical Analysis · Mathematics 2014-04-16 Patrick Henning , Daniel Peterseim