English
Related papers

Related papers: An Overview of Meshfree Collocation Methods

200 papers

In this paper, we propose a point cloud classification method based on graph neural network and manifold learning. Different from the conventional point cloud analysis methods, this paper uses manifold learning algorithms to embed point…

Computer Vision and Pattern Recognition · Computer Science 2020-10-19 Dinghao Yang , Wei Gao

This contribution presents a method that aims at the numerical analysis of solids represented by oriented point clouds. The proposed approach is based on the Finite Cell Method, a high-order immersed boundary technique that computes on a…

Computational Engineering, Finance, and Science · Computer Science 2024-09-23 László Kudela , Stefan Kollmannsberger , Umut Almac , Ernst Rank

This paper provides a general mathematical optimization based framework to incorporate fairness measures from the facilities' perspective to Discrete and Continuous Maximal Covering Location Problems. The main ingredients to construct a…

Optimization and Control · Mathematics 2022-11-17 Víctor Blanco , Ricardo Gázquez

We develop a mesh-free, derivative-free, matrix-free, and highly parallel localized stochastic method for high-dimensional semilinear parabolic PDEs. The efficiency of the proposed method is built upon four essential components: (i) a…

Numerical Analysis · Mathematics 2025-10-14 Shuixin Fang , Changtao Sheng , Bihao Su , Tao Zhou

This paper solves the two-dimensional Dirichlet problem for the Monge-Amp\`ere equation by a strong meshless collocation technique that uses a polynomial trial space and collocation in the domain and on the boundary. Convergence rates may…

Numerical Analysis · Mathematics 2017-12-27 Klaus Böhmer , Robert Schaback

In this paper, we exploit the theory of dense graph limits to provide a new framework to study the stability of graph partitioning methods, which we call structural consistency. Both stability under perturbation as well as asymptotic…

Combinatorics · Mathematics 2016-08-15 Peter Diao , Dominique Guillot , Apoorva Khare , Bala Rajaratnam

Approximating differential operators defined on two-dimensional surfaces is an important problem that arises in many areas of science and engineering. Over the past ten years, localized meshfree methods based on generalized moving least…

Numerical Analysis · Mathematics 2023-09-11 Andrew M. Jones , Peter A. Bosler , Paul A. Kuberry , Grady B. Wright a

Smoothing is omnipresent in astronomy, because almost always measurements performed at discrete positions in the sky need to be interpolated into a smooth map for subsequent analysis. Still, the statistical properties of different…

Astrophysics · Physics 2009-11-07 Marco Lombardi

We provide a primer to numerical methods based on Taylor series expansions such as generalized finite difference methods and collocation methods. We provide a detailed benchmarking strategy for these methods as well as all data files…

Solutions of partial differential equations (PDEs) on manifolds have provided important applications in different fields in science and engineering. Existing methods are majorly based on discretization of manifolds as implicit functions,…

Numerical Analysis · Mathematics 2017-08-03 Rongjie Lai , Jia Li

Many real-world physics and engineering problems arise in geometrically complex domains discretized by meshes for numerical simulations. The nodes of these potentially irregular meshes naturally form point clouds whose limited tractability…

Machine Learning · Computer Science 2025-06-17 Shirin Hosseinmardi , Ramin Bostanabad

This work presents a high-accuracy, mesh-free, generalized Stokes theorem-based numerical quadrature scheme for integrating functions over trimmed parametric surfaces and volumes. The algorithm relies on two fundamental steps: (1) We…

Numerical Analysis · Mathematics 2022-01-04 David Gunderman , Kenneth Weiss , John A. Evans

In this paper we present a novel particle method for the Vlasov--Poisson equation. Unlike in conventional particle methods, the particles are not interpreted as point charges, but as point values of the distribution function. In between the…

Numerical Analysis · Mathematics 2022-11-04 Rostislav-Paul Wilhelm , Matthias Kirchhart

Context: Calculating stellar pulsations requires a sufficient accuracy to match the quality of the observations. Many current pulsation codes apply a second order finite-difference scheme, combined with Richardson extrapolation to reach…

Solar and Stellar Astrophysics · Physics 2015-06-16 D. R. Reese

First-order automatic differentiation is a ubiquitous tool across statistics, machine learning, and computer science. Higher-order implementations of automatic differentiation, however, have yet to realize the same utility. In this paper I…

Computation · Statistics 2019-01-01 Michael Betancourt

Geometrical Volume-of-Fluid (VoF) methods mainly support structured meshes, and only a small number of contributions in the scientific literature report results with unstructured meshes and three spatial dimensions. Unstructured meshes are…

Computational Physics · Physics 2024-02-07 Tomislav Maric , Douglas B. Kothe , Dieter Bothe

In this paper, we propose a low-rank coordinate descent approach to structured semidefinite programming with diagonal constraints. The approach, which we call the Mixing method, is extremely simple to implement, has no free parameters, and…

Optimization and Control · Mathematics 2026-05-12 Po-Wei Wang , Wei-Cheng Chang , J. Zico Kolter

We utilize generalized moving least squares (GMLS) to develop meshfree techniques for discretizing hydrodynamic flow problems on manifolds. We use exterior calculus to formulate incompressible hydrodynamic equations in the Stokesian regime…

Numerical Analysis · Mathematics 2023-02-28 B. J. Gross , N. Trask , P. Kuberry , P. J. Atzberger

When studying a metastable dynamical system, a prime concern is how to decompose the phase space into a set of metastable states. Unfortunately, the metastable state decomposition based on simulation or experimental data is still a…

Machine Learning · Computer Science 2015-01-05 Hao Wu

This paper aims at reviewing nonlinear methods for model order reduction of structures with geometric nonlinearity, with a special emphasis on the techniques based on invariant manifold theory. Nonlinear methods differ from linear based…

Numerical Analysis · Mathematics 2022-05-26 Cyril Touzé , Alessandra Vizzaccaro , Olivier Thomas