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We construct explicitly Pad\'e approximations of the second kind for a special class of G-functions. These are then applied to prove a Baker-type lower bound for linear forms in the p-adic values of these functions. Moreover, we consider…

Number Theory · Mathematics 2018-07-27 Keijo Väänänen

This article is about both approximation theory and the numerical solution of partial differential equations (PDEs). First we introduce the notion of {\em reciprocal-log} or {\em log-lightning approximation} of analytic functions with…

Numerical Analysis · Mathematics 2020-10-06 Yuji Nakatsukasa , Lloyd N. Trefethen

In this paper, we propose a new and simple approach to the approximation algorithms that are modified and improved from our published results. The computational and graphical examples are presented with the aid of Maple procedures.

Numerical Analysis · Mathematics 2025-06-24 Quan Le Phuong

Pad\'e approximants are rational functions whose series expansion match a given series as far as possible. These approximants are usually written under a rational form. In this paper, we will show how to write them also under two different…

Numerical Analysis · Mathematics 2014-04-29 Claude Brezinski , Michela Redivo-Zaglia

We consider approximating analytic functions on the interval $[-1,1]$ from their values at a set of $m+1$ equispaced nodes. A result of Platte, Trefethen \& Kuijlaars states that fast and stable approximation from equispaced samples is…

Numerical Analysis · Mathematics 2022-03-08 Ben Adcock , Alexei Shadrin

Several numerical approximation strategies for the expectation-propagation algorithm are studied in the context of large-scale learning: the Laplace method, a faster variant of it, Gaussian quadrature, and a deterministic version of…

Computation · Statistics 2016-11-16 Alexis Roche

In this article, we construct new Pad\'{e} approximations for the \emph{product} of binomial functions and powers of logarithmic functions. While several explicit Pad\'{e} approximants are known for powers of exponential functions, binomial…

Number Theory · Mathematics 2025-11-14 Makoto Kawashima

The problem of reconstructing functions from their asymptotic expansions in powers of a small variable is addressed by deriving a novel type of approximants. The derivation is based on the self-similar approximation theory, which presents…

Statistical Mechanics · Physics 2009-11-07 S. Gluzman , V. I. Yukalov , D. Sornette

This paper presents new uniform Gaussian strong approximations for empirical processes indexed by classes of functions based on $d$-variate random vectors ($d\geq1$). First, a uniform Gaussian strong approximation is established for general…

Statistics Theory · Mathematics 2024-11-14 Matias D. Cattaneo , Ruiqi Rae Yu

This paper addresses a multi-scale finite element method for second order linear elliptic equations with arbitrarily rough coefficient. We propose a local oversampling method to construct basis functions that have optimal local…

Numerical Analysis · Mathematics 2015-08-04 Thomas Y. Hou , Pengfei Liu

The Laplace approximation calls for the computation of second derivatives at the likelihood maximum. When the maximum is found by the EM-algorithm, there is a convenient way to compute these derivatives. The likelihood gradient can be…

Machine Learning · Statistics 2014-01-27 Niko Brümmer

The article presents mathematical generalization of results which originated as solutions of practical problems, in particular, the modeling of transitional processes in electrical circuits and problems of resource allocation. However, the…

Classical Analysis and ODEs · Mathematics 2012-11-27 Yuri Shestopaloff

Generalized additive models (GAMs) are a well-established statistical tool for modeling complex nonlinear relationships between covariates and a response assumed to have a conditional distribution in the exponential family. In this article,…

Methodology · Statistics 2021-03-02 Oswaldo Gressani , Philippe Lambert

A fast approximation to the Boys functions (related to the lower incomplete gamma function of half-integer parameter) by a single closed-form analytical expression for all argument values have been developed and tested. Besides the…

Numerical Analysis · Mathematics 2025-07-09 Dimitri N. Laikov

A method for sequential inference of the fixed parameters of a dynamic latent Gaussian models is proposed and evaluated that is based on the iterated Laplace approximation. The method provides a useful trade-off between computational…

Methodology · Statistics 2015-09-29 Tiep Mai , Simon Wilson

The use of approximants of Pad\`e type are employed to develop a method aimed at opening new perspectives in the theory of Appell polynomials $a_n(x)$, specified by the generating function \sum_{n=0}^{\infty} \frac{t^n}{n!} a_n(x) = A(t)…

Classical Analysis and ODEs · Mathematics 2025-09-04 Giuseppe Dattoli , Subuhi Khan , Ujair Ahmad

In this paper, we introduce a method known as polynomial frame approximation for approximating smooth, multivariate functions defined on irregular domains in $d$ dimensions, where $d$ can be arbitrary. This method is simple, and relies only…

Numerical Analysis · Mathematics 2020-05-27 Ben Adcock , Daan Huybrechs

This paper introduces a new numerical method for approximating the Lambert W function in the real domain. The method transforms the function into a simpler form that allows iterative refinement of an initial guess. Two iterative strategies…

Numerical Analysis · Mathematics 2025-11-25 Narinder Kumar Wadhawan

We seek random versions of some classical theorems on complex approximation by polynomials and rational functions, as well as investigate properties of random compact sets in connection to complex approximation.

Complex Variables · Mathematics 2017-09-26 Simon St-Amant , Jérémie Turcotte

In this paper we consider a family of algorithms for approximate implicitization of rational parametric curves and surfaces. The main approximation tool in all of the approaches is the singular value decomposition, and they are therefore…

Numerical Analysis · Mathematics 2016-05-30 Oliver J. D. Barrowclough , Tor Dokken