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The Gaussian product inequality (GPI) conjecture is one of the most famous inequalities associated with Gaussian distributions and has attracted a lot of concerns. In this note, we investigate the quantitative versions of the…

Probability · Mathematics 2022-07-21 Ze-Chun Hu , Han Zhao , Qian-Qian Zhou

Gaussian Quadrature is a well known technique for numerical integration. Recently Gaussian quadrature with respect to discrete measures corresponding to finite sums have found some new interest. In this paper we apply these ideas to…

Numerical Analysis · Mathematics 2007-05-23 Hartmut Monien

Electronic structure calculations are routinely carried out within the framework of density-functional theory, often with great success. For electrons in reduced dimensions, however, there is still a need for better approximations to the…

Strongly Correlated Electrons · Physics 2009-09-22 S. Pittalis , E. Rasanen , E. K. U. Gross

In this communication, one shows that there exists in the literature a certain form of deformed derivative that can here be identified as the dual of conformable derivative. The deformed subtraction is used here, together with the duality…

Mathematical Physics · Physics 2018-11-14 Wanderson Rosa , José Weberszpil

A lower bound for the Gaussian Q-function is presented in the form of a single exponential function with parametric order and weight. We prove the lower bound by introducing two functions, one related to the Q-function and the other…

Probability · Mathematics 2012-03-23 François D. Côté , Ioannis N. Psaromiligkos , Warren J. Gross

Fourier feature approximations have been successfully applied in the literature for scalable Gaussian Process (GP) regression. In particular, Quadrature Fourier Features (QFF) derived from Gaussian quadrature rules have gained popularity in…

Machine Learning · Statistics 2023-10-24 Kevin Li , Max Balakirsky , Simon Mak

A new method for approximating fractional derivatives of the Gaussian function and Dawson's integral are presented. Unlike previous approaches, which are dominantly based on some discretization of Riemann-Liouville integral using polynomial…

Numerical Analysis · Mathematics 2017-09-08 Can Evren Yarman

Derivation of two-time second-order correlation function by following approaches such as stochastic differential equation, coherent-state propagator, and quasi-statistical distribution function is presented. In the process, the time…

Quantum Physics · Physics 2024-06-18 Sintayehu Tesfa

The bilateral filter is a versatile non-linear filter that has found diverse applications in image processing, computer vision, computer graphics, and computational photography. A widely-used form of the filter is the Gaussian bilateral…

Computer Vision and Pattern Recognition · Computer Science 2016-11-15 Kunal N. Chaudhury

This work is devoted in the derivation of novel upper and lower bounds for the Rice $Ie$-function. These bounds are expressed in closed-form and are shown to be quite tight. This is particularly evident by the fact that for a certain range…

Information Theory · Computer Science 2015-05-18 Paschalis C. Sofotasios , Steven Freear

Exactly solvable two-dimensional polygon models, counted by perimeter and area, are described by $q$-algebraic functional equations. We provide techniques to extract the scaling behaviour of these models up to arbitrary order and apply them…

Statistical Mechanics · Physics 2008-08-28 Christoph Richard

Full-sampling (e.g., Q-learning) and pure-expectation (e.g., Expected Sarsa) algorithms are efficient and frequently used techniques in reinforcement learning. Q$(\sigma,\lambda)$ is the first approach unifies them with eligibility trace…

Machine Learning · Computer Science 2019-09-09 Long Yang , Yu Zhang , Qian Zheng , Pengfei Li , Gang Pan

The (2+1)-dimensional Thirring model is studied by using the Gaussian approximation method in the functional Schr\"odinger picture. Although the dynamical symmetry breaking does not occur in the large N limit, it does occur in the Gaussian…

High Energy Physics - Theory · Physics 2009-10-28 S. J. Hyun , G. H. Lee , J. H. Yee

We investigate training and using Gaussian kernel SVMs by approximating the kernel with an explicit finite- dimensional polynomial feature representation based on the Taylor expansion of the exponential. Although not as efficient as the…

Artificial Intelligence · Computer Science 2011-09-22 Andrew Cotter , Joseph Keshet , Nathan Srebro

Due to their flexibility, Gaussian processes (GPs) have been widely used in nonparametric function estimation. A prior information about the underlying function is often available. For instance, the physical system (computer model output)…

Methodology · Statistics 2017-11-21 Hassan Maatouk

Two approximations of the integral of a class of sinusoidal composite functions, for which an explicit form does not exist, are derived. Numerical experiments show that the proposed approximations yield an error that does not depend on the…

Numerical Analysis · Mathematics 2024-01-17 Alberto Costa

We appeal to a complex q-Fourier transform as a generalization of the (real) one analyzed in [Milan J. Math. {\bf 76} (2008) 307]. By recourse to tempered ultra-distributions we are able to show that the q-Gaussian distribution can be…

Mathematical Physics · Physics 2015-06-12 A. Plastino , M. C. Rocca

An analysis of the characteristic function of Gaussian quadratic forms is presented in [1] to study the performance of multichannel communication systems. This technical report reviews this analysis, obtaining alternative expressions to…

Information Theory · Computer Science 2012-12-04 Unai Fernández-Plazaola , Eduardo Martos-Naya , José F. Paris , José T. Entrambasaguas

Gaussian quadrature rules are a classical tool for the numerical approximation of integrals with smooth integrands and positive weight functions. We derive and expicitly list asymptotic expressions for the points and weights of Gaussian…

Numerical Analysis · Mathematics 2022-08-25 Peter Opsomer , Daan Huybrechs

It is a consensus in signal processing that the Gaussian kernel and its partial derivatives enable the development of robust algorithms for feature detection. Fourier analysis and convolution theory have central role in such development. In…

Computer Vision and Pattern Recognition · Computer Science 2016-05-03 Paulo Sérgio Silva Rodrigues , Gilson Antonio Giraldi