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We study the problem of space and time efficient evaluation of a nonparametric estimator that approximates an unknown density. In the regime where consistent estimation is possible, we use a piecewise multivariate polynomial interpolation…

Statistics Theory · Mathematics 2020-11-11 Paxton Turner , Jingbo Liu , Philippe Rigollet

We present a simple, PDE-based proof of the result [M. Johnson, 2001] that the error estimates of [J. Duchon, 1978] for thin plate spline interpolation can be improved by $h^{1/2}$. We illustrate that ${\mathcal H}$-matrix techniques can…

Numerical Analysis · Mathematics 2018-08-20 M. Loehndorf , J. M. Melenk

In this paper, we employ Bayesian optimization to concurrently explore the optimal values for both the shape parameter and the radius in the partition of unity interpolation using radial basis functions. Bayesian optimization is a…

Numerical Analysis · Mathematics 2023-11-09 Roberto Cavoretto , Alessandra De Rossi , Sandro Lancellotti , Federico Romaniello

This article presents novel proof methods for estimating interpolation errors, predicated on the understanding that one has already studied foundational error analysis using the finite element method.

Numerical Analysis · Mathematics 2025-04-23 Hiroki Ishizaka

Fast and accurate computations of the power spectrum of cosmic microwave background fluctuations are essential for comparing current and upcoming data sets with the large parameter space of viable cosmological models. The most efficient…

Astrophysics · Physics 2007-05-23 Arthur Kosowsky

We present a new rational approximation algorithm based on the empirical interpolation method for interpolating a family of parametrized functions to rational polynomials with invariant poles, leading to efficient numerical algorithms for…

Numerical Analysis · Mathematics 2025-01-23 Aidi Li , Yuwen Li

This paper deals with the kernel-based approximation of a multivariate periodic function by interpolation at the points of an integration lattice -- a setting that, as pointed out by Zeng, Leung, Hickernell (MCQMC2004, 2006) and Zeng,…

Numerical Analysis · Mathematics 2022-01-25 Vesa Kaarnioja , Yoshihito Kazashi , Frances Y. Kuo , Fabio Nobile , Ian H. Sloan

In contemporary deep learning practice, models are often trained to near zero loss i.e. to nearly interpolate the training data. However, the number of parameters in the model is usually far more than the number of data points n, the…

Machine Learning · Computer Science 2025-11-04 Santanu Das , Jatin Batra , Piyush Srivastava

Structured kernel interpolation (SKI) accelerates Gaussian process (GP) inference by interpolating the kernel covariance function using a dense grid of inducing points, whose corresponding kernel matrix is highly structured and thus…

Machine Learning · Computer Science 2023-05-26 Mohit Yadav , Daniel Sheldon , Cameron Musco

In mesh-based numerical simulations, the interpolation of mesh-defined functions across different meshes is a critical task, and achieving high-precision interpolation is of great significance for improving the computational efficiency and…

Numerical Analysis · Mathematics 2026-04-15 Jiaxiong Hao , Yunqing Huang , Nianyu Yi

The approximation properties of a quadratic iso-parametric finite element method for a typical cavitation problem in nonlinear elasticity are analyzed. More precisely, (1) the finite element interpolation errors are established in terms of…

Numerical Analysis · Mathematics 2017-01-06 Chunmei Su , Zhiping Li

Following the pioneering work of H. Reiss [1], we provide a covariant calculation of the charged scalar particle pair production. The calculation is facilitated by the use of two-dimensional Bessel functions and light-font coordinates.

High Energy Physics - Phenomenology · Physics 2013-09-26 M. Onirban Islam , Md. Galib Hassan , M. Arshad Momen

This paper develops a unified theoretical framework for constructing B-spline basis function spaces with structural equivalence to finite element spaces. The theory rigorously establishes that these bases emerge as explicit linear…

Numerical Analysis · Mathematics 2026-01-29 Peng Yang , Maodong Pan , Falai Chen , Zhimin Zhang

In this paper, the construction of $C^{1}$ cubic quasi-interpolants on a three-direction mesh of $\RR^{2}$ is addressed. The quasi-interpolating splines are defined by directly setting their Bernstein-B\'{e}zier coefficients relative to…

Numerical Analysis · Mathematics 2024-05-01 Domingo Barrera , Salah Eddargani , María José Ibáñez , Sara Remogna

Energy minimizing BPS equations and solutions are obtained for a class of models in Maxwell-scalar theory, where an abelian electric charge is immersed in an effective dielectric of a real scalar field. The first order BPS equations are…

High Energy Physics - Theory · Physics 2022-02-09 J. R. Morris

The main purpose of this work is the one of providing an efficient scheme for constructing reduced interpolation models for kernel bases. In literature such problem is mainly addressed via the well-established knot insertion or knot removal…

Numerical Analysis · Mathematics 2021-07-14 Francesco Marchetti , Emma Perracchione

In this paper, we investigate the approximation properties of two types of multiscale finite element methods with oversampling as proposed in [Hou \& Wu, {\textit{J. Comput. Phys.}}, 1997] and [Efendiev, Hou \& Wu, \textit{SIAM J. Numer.…

Numerical Analysis · Mathematics 2025-07-22 Guanglian Li

Consider the Poisson equation with the Dirichlet boundary condition on a three-dimensional polyhedral domain. For singular solutions from the non-smoothness of the domain boundary, we propose new anisotropic tetrahedral mesh refinement…

Numerical Analysis · Mathematics 2016-12-21 Hengguang Li

This paper proposes an image interpolation algorithm exploiting sparse representation for natural images. It involves three main steps: (a) obtaining an initial estimate of the high resolution image using linear methods like FIR filtering,…

Computer Vision and Pattern Recognition · Computer Science 2013-08-07 H. Lakshman , W. -Q Lim , H. Schwarz , D. Marpe , G. Kutyniok , T. Wiegand

Generative models based on normalizing flows are very successful in modeling complex data distributions using simpler ones. However, straightforward linear interpolations show unexpected side effects, as interpolation paths lie outside the…

Machine Learning · Statistics 2025-04-09 Samuel G. Fadel , Sebastian Mair , Ricardo da S. Torres , Ulf Brefeld
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