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Related papers: On the Generalized Borel Transform and its Applica…

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In this paper, we present a new approach to the discrete version of the Wormlike Chain Model (WCM) of semiflexible polymers. Our solution to the model is based on a new computational technique called the Generalized Borel Transform (GBT)…

Soft Condensed Matter · Physics 2007-05-23 Marcelo Marucho , Gustavo A. Carri

We present the Generalized Borel Transform (GBT). This new approach allows one to obtain approximate solutions of Laplace/Mellin transform valid in both, perturbative and non perturbative regimes. We compare the results provided by the GBT…

High Energy Physics - Theory · Physics 2016-08-16 L. N. Epele , H. Fanchiotti , C. A. García Canal , M. Marucho

Parker and L\^e introduced random butterfly transforms (RBTs) as a preprocessing technique to replace pivoting in dense LU factorization. Unfortunately, their FFT-like recursive structure restricts the dimensions of the matrix. Furthermore,…

Numerical Analysis · Mathematics 2024-10-14 Neil Lindquist , Piotr Luszczek , Jack Dongarra

The Poisson-binomial distribution is useful in many applied problems in engineering, actuarial science, and data mining. The Poisson-binomial distribution models the distribution of the sum of independent but not identically distributed…

Computation · Statistics 2017-02-07 Man Zhang , Yili Hong , Narayanaswamy Balakrishnan

Paraxial diffraction modeling based on the Fourier transform has seen widespread implementation for simulating the response of a diffraction-limited optical system. For systems where the paraxial assumption is not sufficient, a class of…

Machine learning algorithms for generating molecular structures offer a promising new approach to drug discovery. We cast molecular optimization as a translation problem, where the goal is to map an input compound to a target compound with…

Machine Learning · Computer Science 2019-12-24 Farhan Damani , Vishnu Sresht , Stephen Ra

Contemporary graph learning algorithms are not well-defined for large molecules since they do not consider the hierarchical interactions among the atoms, which are essential to determine the molecular properties of macromolecules. In this…

Machine Learning · Computer Science 2023-08-02 Nhat Khang Ngo , Truong Son Hy , Risi Kondor

The principle of Random Galilean Transformation (RGT) Invariance is applied to the random motion of particles in a turbulent gas to construct a kinetic equation for the transport of the particle phase space probability…

Fluid Dynamics · Physics 2023-04-25 Michael W Reeks , Sean McKee

This work introduces a method for generating generalized structures of amorphous polymers using simulated polymerization and molecular dynamics equilibration, with a particular focus on amorphous polymers. The techniques and algorithms used…

Soft Condensed Matter · Physics 2024-04-04 Jianchuan Liu , Haiyan Lin , Xun Li

A generalization of the generalized inverse Weibull distribution so-called transmuted generalized inverse Weibull dis- tribution is proposed and studied. We will use the quadratic rank transmutation map (QRTM) in order to generate a…

Methodology · Statistics 2013-09-16 Faton Merovci , Ibrahim Elbatal , Alaa Ahmed

Discrete transforms, such as the discrete Fourier transform, are widely used in machine learning to improve model performance by extracting meaningful features. However, with numerous transforms available, selecting an appropriate one often…

Machine Learning · Computer Science 2025-05-09 Gekko Budiutama , Shunsuke Daimon , Hirofumi Nishi , Yu-ichiro Matsushita

We introduce the lifted Generalized Belief Propagation (GBP) message passing algorithm, for the computation of sum-product queries in Probabilistic Relational Models (e.g. Markov logic network). The algorithm forms a compact region graph…

Artificial Intelligence · Computer Science 2016-10-06 Udi Apsel

We derive the form of reciprocal generalized radiative transfer (RGRT) that includes the Levermore-Pomraning attenuation law for paths leaving a deterministic origin. The resulting model describes linear transport within multi-dimensional…

Statistical Mechanics · Physics 2019-03-22 Eugene d'Eon

In this paper we study a parametric class of stochastic processes to model both fast and slow anomalous diffusion. This class, called generalized grey Brownian motion (ggBm), is made up off self-similar with stationary increments processes…

Mathematical Physics · Physics 2009-11-13 Antonio Mura , Gianni Pagnini

The generalized number-theoretic transformation (NPT) is formulated on the basis of the exponential function theorem, which allows us to replace operations modulo the expression as a whole by modulo operations on the exponent of this…

General Mathematics · Mathematics 2020-11-24 M. V. Semotiuk

A brief survey of the theory of soliton perturbations is presented. The focus is on the usefulness of the so-called Generalised Fourier Transform (GFT). This is a method that involves expansions over the complete basis of `squared olutions`…

Exactly Solvable and Integrable Systems · Physics 2009-07-30 Georgi G. Grahovski , Rossen I. Ivanov

In this paper, we introduce a new four-parameter generalized version of the Gompertz model which is called Beta-Gompertz (BG) distribution. It includes some well-known lifetime distributions such as beta-exponential and generalized Gompertz…

Statistics Theory · Mathematics 2014-07-04 Ali Akbar Jafari , Saeid Tahmasebi , Morad Alizadeh

We introduce a novel framework for Generalized Tensor Transforms (GTTs), constructed through an $n$-fold tensor product of an arbitrary $b \times b$ unitary matrix $W$. This construction generalizes many established transforms, by providing…

Quantum Physics · Physics 2025-07-11 Alok Shukla , Prakash Vedula

Using tools from representation theory, we derive expressions for the coincidence rate of partially-distinguishable particles in an interferometry experiment. Our expressions are valid for either bosons or fermions, and for any number of…

Quantum Physics · Physics 2022-05-04 Dylan Spivak , Murphy Yuezhen Niu , Barry C. Sanders , Hubert de Guise

Meta-analytical models are typically formulated as a mixed-effects model where the sampling variances of the effect sizes are treated as known. In principle, such models could be fitted with standard mixed-modelling software such as the…

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