English
Related papers

Related papers: Stable High Order Quadrature Rules for Scattered D…

200 papers

Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for large scattered (unordered) datasets in d-dimensional space. This approach is useful for a higher…

Numerical Analysis · Computer Science 2018-06-21 Zuzana Majdisova , Vaclav Skala

In this paper we revisit some quadrature methods for highly oscillatory integrals of the form $\int_{-1}^1f(x)e^{{\rm i}\omega x}dx, \omega>0$. Exponentially Fitted (EF) rules depend on frequency dependent nodes which start off at the…

Numerical Analysis · Mathematics 2014-06-24 Veerle Ledoux , Marnix Van Daele

This paper provides a product integration rule for highly oscillating integrands, based on equally spaced nodes. The stability and the error estimate are proven in the space of continuous functions, and some numerical tests which confirm…

Numerical Analysis · Mathematics 2022-07-20 Luisa Fermo , Domenico Mezzanotte , Donatella Occorsio

Gaussian process (GP) models have received increasing attention in recent years due to their superb prediction accuracy and modeling flexibility. To address the computational burdens of GP models for large-scale datasets, distributed…

Machine Learning · Statistics 2026-02-11 Haoyuan Chen , Rui Tuo

Generalized dimensions of multifractal measures are usually seen as static objects, related to the scaling properties of suitable partition functions, or moments of measures of cells. When these measures are invariant for the flow of a…

Dynamical Systems · Mathematics 2019-10-02 Théophile Caby , Davide Faranda , Giorgio Mantica , Sandro Vaienti , Pascal Yiou

Gauss-Lobatto quadrature nodes and weights are optimal for closed summation-by-parts (SBP) formulations based on polynomial approximation spaces in the sense that for a prescribed function space they yield an SBP operator of minimal…

Numerical Analysis · Mathematics 2026-04-28 Nicholas Hale , Charis Harley , Prince Nchupang , Jan Nordström

We provide the first stochastic convergence rates for a family of adaptive quadrature rules used to normalize the posterior distribution in Bayesian models. Our results apply to the uniform relative error in the approximate posterior…

Methodology · Statistics 2022-10-27 Blair Bilodeau , Alex Stringer , Yanbo Tang

We propose and experimentally demonstrate a universal quantum averaging process implementing the harmonic mean of quadrature variances. The harmonic mean protocol can be used to efficiently stabilize a set of fragile squeezed light sources…

Quantum Physics · Physics 2015-05-18 Mikael Lassen , Lars Skovgaard Madsen , Metin Sabuncu , Radim Filip , Ulrik L. Andersen

An important question in the theory of approximate integration is to study the conditions on the nodes $x_{k,n}$ and weights $w_{k,n}$ that allow an estimate of the form $$ \sup_{f\in \mathcal{B}_\gamma}|\sum_k…

Numerical Analysis · Mathematics 2017-09-06 Hrushikesh N. Mhaskar

Many applications require multi-dimensional numerical integration, often in the form of a cubature formula. These cubature formulas are desired to be positive and exact for certain finite-dimensional function spaces (and weight functions).…

Numerical Analysis · Mathematics 2022-05-27 Jan Glaubitz

This article reviews and studies the properties of Bayesian quadrature weights, which strongly affect stability and robustness of the quadrature rule. Specifically, we investigate conditions that are needed to guarantee that the weights are…

Statistics Theory · Mathematics 2019-08-05 Toni Karvonen , Motonobu Kanagawa , Simo Särkkä

Discretizing an analytic function on a uniform real-space grid is often done via a straightforward collocation method. This is ubiquitous in all areas of computational physics and quantum chemistry. An example in Density Functional Theory…

Computational Physics · Physics 2016-01-20 Luigi Genovese , Thierry Deutsch

This paper proposes a generalization of Gaussian mixture models, where the mixture weight is allowed to behave as an unknown function of time. This model is capable of successfully capturing the features of the data, as demonstrated by…

Methodology · Statistics 2022-09-09 Michel H. Montoril , Leandro T. Correia , Helio S. Migon

Approximation using Fourier features is a popular technique for scaling kernel methods to large-scale problems, with myriad applications in machine learning and statistics. This method replaces the integral representation of a…

Machine Learning · Statistics 2024-08-26 Ayoub Belhadji , Qianyu Julie Zhu , Youssef Marzouk

This paper presents novel methodologies for the numerical simulation of scattering of elastic waves by both closed and open surfaces in three-dimensional space. The proposed approach utilizes new integral formulations as well as an…

Computational Physics · Physics 2020-04-22 Oscar P. Bruno , Tao Yin

In the real world, experimental data are rarely, if ever, distributed as a normal (Gaussian) distribution. As an example, a large set of data--such as the cross sections for particle scattering as a function of energy contained in the…

Data Analysis, Statistics and Probability · Physics 2009-11-11 Martin M. Block

State space subspace algorithms for input-output systems have been widely applied but also have a reasonably well-developedasymptotic theory dealing with consistency. However, guaranteeing the stability of the estimated system matrix is a…

Systems and Control · Electrical Eng. & Systems 2024-08-19 Xinhui Rong , Victor Solo

We give a full description of the numerical solution of a general charge transport model for doped disordered semiconductors with arbitrary field- and density-dependent mobilities. We propose a suitable scaling scheme and generalize the…

Computational Physics · Physics 2012-12-13 S. Stodtmann , R. M. Lee , C. K. F. Weiler , A. Badinski

We consider the problem of computing the joint distribution of order statistics of stochastically independent random variables in one- and two-group models. While recursive formulas for evaluating the joint cumulative distribution function…

Computation · Statistics 2018-12-24 Jonathan von Schroeder , Thorsten Dickhaus

The implementation of the finite element method for linear elliptic equations requires to assemble the stiffness matrix and the load vector. In general, the entries of this matrix-vector system are not known explicitly but need to be…

Numerical Analysis · Mathematics 2019-08-26 Raphael Kruse , Nick Polydorides , Yue Wu