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Generalized Brown-Resnick processes form a flexible class of stationary max-stable processes based on Gaussian random fields. With regard to applications fast and accurate simulation of these processes is an important issue. In fact,…

Probability · Mathematics 2010-09-30 Marco Oesting

In many real-world applications we are interested in approximating costly functions that are analytically unknown, e.g. complex computer codes. An emulator provides a fast approximation of such functions relying on a limited number of…

Methodology · Statistics 2020-10-02 Hossein Mohammadi , Peter Challenor , Marc Goodfellow , Daniel Williamson

In this paper, we obtain uniform bounds for a number of expressions that involve derivatives and integrals of modified Bessel functions. These uniform bounds are motivated by the need to bound such expressions in the study of variance-gamma…

Classical Analysis and ODEs · Mathematics 2017-03-21 Robert E. Gaunt

A fundamental problem in numerical analysis and approximation theory is approximating smooth functions by polynomials. A much harder version under recent consideration is to enforce bounds constraints on the approximating polynomial. In…

Numerical Analysis · Mathematics 2021-12-28 Larry Allen , Robert C. Kirby

Gaussian Belief Propagation (BP) algorithm is one of the most important distributed algorithms in signal processing and statistical learning involving Markov networks. It is well known that the algorithm correctly computes marginal density…

Machine Learning · Statistics 2019-03-08 Zhaorong Zhang , Minyue Fu

In a complete metric space that is equipped with a doubling measure and supports a Poincar\'e inequality, we show that functions of bounded variation (BV functions) can be approximated in the strict sense and pointwise uniformly by special…

Metric Geometry · Mathematics 2018-06-13 Panu Lahti

Recent years have seen a growing interest in the use of belief propagation - an algorithm originally introduced for performing statistical inference on graphical models - for approximate, but highly efficient, tensor network contraction.…

Quantum Physics · Physics 2026-04-28 Joseph Tindall , Grace M. Sommers , Hilbert Kappen

We find a recursive expression for the Bessel function of S. I. Gelfand for irreducible generic representations of $\operatorname{GL}_n\left(\mathbb{F}_q\right)$. We show that special values of the Bessel function can be realized as the…

Representation Theory · Mathematics 2024-01-03 Elad Zelingher

It is known from the Runge approximation theorem that every function which is holomorphic in a neighborhood of a compact polynomially convex set $K\subset \complexes^{n}$ can be approximated uniformly on $K$ by analytic polynomials. We…

Complex Variables · Mathematics 2007-05-23 Youssef Alaoui , My Abdelhakim El Idrissi Saad

In this paper our aim is to present some subordination and superordination results, by using an operator, which involves the normalized form of the generalized Bessel functions of first kind. These results are obtained by investigating some…

Complex Variables · Mathematics 2016-11-26 Arpad Baricz , Erhan Deniz , Murat Caglar , Halit Orhan

Elliptic partial differential equations with diffusion coefficients of lognormal form, that is $a=exp(b)$, where $b$ is a Gaussian random field, are considered. We study the $\ell^p$ summability properties of the Hermite polynomial…

Numerical Analysis · Mathematics 2015-09-24 Markus Bachmayr , Albert Cohen , Ronald DeVore , Giovanni Migliorati

We show that, for $0<s<1$, $0<p<\infty$, $0<q<\infty$, Haj\l asz-Besov and Haj\l asz-Triebel-Lizorkin functions can be approximated in the norm by discrete median convolutions. This allows us to show that, for these functions, the limit of…

Functional Analysis · Mathematics 2015-05-22 Toni Heikkinen , Pekka Koskela , Heli Tuominen

Factor graphs are important models for succinctly representing probability distributions in machine learning, coding theory, and statistical physics. Several computational problems, such as computing marginals and partition functions, arise…

Machine Learning · Computer Science 2017-08-09 Damian Straszak , Nisheeth K. Vishnoi

We introduce and study the approximation properties of $g$-polynomials, defined as linear combinations of iterated Stieltjes integrals of a constant function. Focusing on the case where the derivator $g$ has finitely many discontinuities,…

Classical Analysis and ODEs · Mathematics 2025-07-08 Víctor Cora , F. Adrián F. Tojo

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

We study fine potential theory and in particular partitions of unity in quasiopen sets in the case $p=1$. Using these, we develop an analog of the discrete convolution technique in quasiopen (instead of open) sets. We apply this technique…

Metric Geometry · Mathematics 2018-12-31 Panu Lahti

We consider Bayesian inference problems with computationally intensive likelihood functions. We propose a Gaussian process (GP) based method to approximate the joint distribution of the unknown parameters and the data. In particular, we…

Computation · Statistics 2018-03-15 Hongqiao Wang , Jinglai Li

We obtain the estimates of steady rates of deviations of the de Vall\'{e}e Poussin sums and interpolation analogues of sums of Vall\'{e}e Poussin from the functions that belong to the space $C_{\bar{\beta}}^\psi L_s, \ 1\leq s\leq\infty$…

Classical Analysis and ODEs · Mathematics 2013-08-22 V. A. Voitovych , A. P. Musienko

The ill-posed analytic continuation problem for Green's functions and self-energies is investigated by revisiting the Pad\'{e} approximants technique. We propose to remedy the well-known problems of the Pad\'{e} approximants by performing…

Strongly Correlated Electrons · Physics 2016-08-22 J. Schött , I. L. M. Locht , E. Lundin , O. Grånäs , O. Eriksson , I. Di Marco

We derive normal approximation results for a class of stabilizing functionals of binomial or Poisson point process, that are not necessarily expressible as sums of certain score functions. Our approach is based on a flexible notion of the…

Probability · Mathematics 2022-10-20 Zhaoyang Shi , Krishnakumar Balasubramanian , Wolfgang Polonik