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Related papers: Quadrature Points via Heat Kernel Repulsion

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We revisit the problem of extending quadrature formulas for general weight functions, and provide a generalization of Patterson's method for the constant weight function. The method can be used to compute a nested sequence of quadrature…

Numerical Analysis · Mathematics 2016-04-22 Sanjay Mehrotra , Dávid Papp

Well-conditioned boundary integral methods for the solution of elliptic boundary value problems (BVPs) are powerful tools for static and dynamic physical simulations. When there are many close-to-touching boundaries (eg, in complex fluids)…

Numerical Analysis · Mathematics 2021-09-21 David B. Stein , Alex H. Barnett

Given a collection of points $S \subset \mathbb{R}^N$, which is partitioned into $M$ overlapping subsets $\{S_i\}_{i=1}^M$, and approximate data $\{D_i\}_{i=1}^M$ associated with the subsets, one may seek a consistent merged dataset $D$…

Image and Video Processing · Electrical Eng. & Systems 2024-05-14 Matthew T. Calef , Kelly M. Olsen , Piyush S. Agram

We study a quadrature, proposed by Ermakov and Zolotukhin in the sixties, through the lens of kernel methods. The nodes of this quadrature rule follow the distribution of a determinantal point process, while the weights are defined through…

Numerical Analysis · Mathematics 2023-09-06 Ayoub Belhadji

This article introduces a new data-driven approach that leverages a manifold embedding generated by the invertible neural network to improve the robustness, efficiency, and accuracy of the constitutive-law-free simulations with limited…

Machine Learning · Computer Science 2022-05-19 Bahador Bahmani , WaiChing Sun

This paper is motivated by Davenport's problem and the subsequent work regarding badly approximable points in submanifolds of a Euclidian space. We study the problem in the area of twisted Diophantine approximation and present two different…

Number Theory · Mathematics 2017-05-17 Paloma Bengoechea , Nikolay Moshchevitin , Natalia Stepanova

In this paper, we show that efficient separated sum-of-exponentials approximations can be constructed for the heat kernel in any dimension. In one space dimension, the heat kernel admits an approximation involving a number of terms that is…

Numerical Analysis · Mathematics 2013-08-20 Shidong Jiang , Leslie Greengard , Shaobo Wang

Persistence diagrams are efficient descriptors of the topology of a point cloud. As they do not naturally belong to a Hilbert space, standard statistical methods cannot be directly applied to them. Instead, feature maps (or representations)…

Probability · Mathematics 2020-12-01 Vincent Divol , Wolfgang Polonik

In this paper, we begin by introducing a well-known geometry concept: the Fermat point in a triangle. Then, we generalize the problem and propose an iterative algorithm based on gradient descent to the weighted form in Lp space. We also…

Optimization and Control · Mathematics 2016-11-18 Shikun Liu

Precise asymptotics have revealed many surprises in high-dimensional regression. These advances, however, have not extended to perhaps the simplest estimator: direct Nadaraya-Watson (NW) kernel smoothing. Here, we describe how one can use…

Disordered Systems and Neural Networks · Physics 2025-01-23 Jacob A. Zavatone-Veth , Cengiz Pehlevan

Handling an infinite number of inequality constraints in infinite-dimensional spaces occurs in many fields, from global optimization to optimal transport. These problems have been tackled individually in several previous articles through…

Optimization and Control · Mathematics 2024-02-22 Pierre-Cyril Aubin-Frankowski , Alessandro Rudi

An approach for solving scattering problems, based on two quantum field theory methods, the heat kernel method and the scattering spectral method, is constructed. This approach converts a method of calculating heat kernels into a method of…

High Energy Physics - Theory · Physics 2015-07-06 Wen-Du Li , Wu-Sheng Dai

Kernel-based methods are heavily used in machine learning. However, they suffer from $O(N^2)$ complexity in the number $N$ of considered data points. In this paper, we propose an approximation procedure, which reduces this complexity to…

Numerical Analysis · Mathematics 2024-11-20 Johannes Hertrich

Firstly, a systematic procedure is derived for obtaining three-dimensional bound-state equations from four-dimensional ones. Unlike ``quasi-potential approaches'' this procedure does not involve the use of delta-function constraints on the…

Nuclear Theory · Physics 2008-11-26 D. R. Phillips , S. J. Wallace

For classification problems, feature extraction is a crucial process which aims to find a suitable data representation that increases the performance of the machine learning algorithm. According to the curse of dimensionality theorem, the…

Machine Learning · Computer Science 2010-10-12 Ilknur Icke , Andrew Rosenberg

This article aims to develop a direct numerical approach to solve the space-fractional partial differential equations (PDEs) based on a new differential quadrature (DQ) technique. The fractional derivatives are approximated by the weighted…

Numerical Analysis · Mathematics 2017-01-24 X. G. Zhu , Y. F. Nie

The $f$ sum rule is derived in a non-relativistic frame and connected, via Ward Identities, to the low energy Thomson scattering. A generalisation to isospin symmetry in the nuclear case is discussed and linked to the Meson Exchange…

Nuclear Theory · Physics 2009-11-06 Rinaldo Cenni

In this article, we give an explicit calculation of the partial Fourier transform of the $\Box_b$-heat equation on quadric submanifolds of $M\subset C^n\times C^m$. As a consequence, we can also compute the heat kernel associated to the…

Complex Variables · Mathematics 2012-08-13 Albert Boggess , Andrew Raich

We suggest a method for simultaneously generating high order quadrature weights for integrals over Lipschitz domains and their boundaries that requires neither meshing nor moment computation. The weights are determined on pre-defined…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov , Bruno Degli Esposti

We propose a new 2D shape decomposition method based on the short-cut rule. The short-cut rule originates from cognition research, and states that the human visual system prefers to partition an object into parts using the shortest possible…

Computer Vision and Pattern Recognition · Computer Science 2015-06-22 Lei Luo , Chunhua Shen , Xinwang Liu , Chunyuan Zhang