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Related papers: Recurrence Relations and Benford's Law

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In this paper, we study the behaviour of TF-isomorphisms, a natural generalisation of isomorphisms. TF-isomorphisms allow us to simplify the approach to seemingly unrelated problems. In particular, we mention the Neighbourhood…

Combinatorics · Mathematics 2014-03-04 Josef Lauri , Russell Mizzi , Raffaele Scapellato

Sums of the form $\sum_{N_m=q}^{n}{\cdots \sum_{N_1=q}^{N_2}{a_{(m);N_m}\cdots a_{(1);N_1}}}$ where the $a_{(k);N_k}$'s are same or distinct sequences appear quite often in mathematics. We will refer to them as recurrent sums. In this…

Number Theory · Mathematics 2022-04-25 Roudy El Haddad

We present the theory of multifunctions applied to graphs. Its interesting feature is that walks are recognized as iterations. We consider the graphs with arbitrary number of vertices which are determined by multifunctions. The mutually…

General Mathematics · Mathematics 2017-11-02 Artur Gizycki

Tensor-power (TP) recurrent model is a family of non-linear dynamical systems, of which the recurrence relation consists of a p-fold (a.k.a., degree-p) tensor product. Despite such the model frequently appears in the advanced recurrent…

Machine Learning · Computer Science 2021-03-03 Hejia Qiu , Chao Li , Ying Weng , Zhun Sun , Xingyu He , Qibin Zhao

We develop two complementary generative mechanisms that explain when and why Benford's first-digit law arises. First, a probabilistic Turing machine (PTM) ensemble induces a geometric law for codelength. Maximizing its entropy under a…

Information Theory · Computer Science 2025-11-25 Alexander Kolpakov , Aidan Rocke

Social science theories often postulate causal relationships among a set of variables or events. Although directed acyclic graphs (DAGs) are increasingly used to represent these theories, their full potential has not yet been realized in…

Machine Learning · Statistics 2024-01-17 Sourabh Balgi , Adel Daoud , Jose M. Peña , Geoffrey T. Wodtke , Jesse Zhou

Linear differential equations and recurrences reveal many properties about their solutions. Therefore, these equations are well-suited for representing solutions and computing with special functions. We identify a large class of existing…

Symbolic Computation · Computer Science 2026-01-14 Louis Gaillard

Assuming sufficiently many terms of a n-dimensional table defined over a field are given, we aim at guessing the linear recurrence relations with either constant or polynomial coefficients they satisfy. In many applications, the table terms…

Symbolic Computation · Computer Science 2021-11-19 Jérémy Berthomieu , Mohab Safey El Din

Working with generating functions, the combinatorics of a recurrence relation can be expressed in a way that allows for more efficient calculation of the quantity. This is true of the Catalan numbers for an ordered binary tree…

Combinatorics · Mathematics 2025-03-05 David Serena , William J Buchanan

Nonextensive statistics, characterized by a nonextensive parameter $q$, is a promising and practically useful generalization of the Boltzmann statistics to describe power-law behaviors from physical and social observations. We here explore…

Data Analysis, Statistics and Probability · Physics 2011-03-07 Lijing Shao , Bo-Qiang Ma

We study arithmetic distribution relations and the inverse function theorem in algebraic and arithmetic geometry, with an emphasis on versions that can be applied uniformly across families of varieties and maps. In particular, we prove two…

Number Theory · Mathematics 2020-08-20 Yohsuke Matsuzawa , Joseph H. Silverman

The Newcomb-Benford Law, which is also called the first digit phenomenon, has applications in diverse phenomena ranging from social and computer networks, engineering systems, natural sciences, and accounting. In forensics, it has been used…

Physics and Society · Physics 2018-06-19 Subhash Kak

Exponential growth occurs when the growth rate of a given quantity is proportional to the quantity's current value. Surprisingly, when exponential growth data is plotted as a simple histogram disregarding the time dimension, a remarkable…

Statistics Theory · Mathematics 2019-01-08 Alex Ely Kossovsky

We compute the divisor of the modular equation on the modular curve $\Gamma_0(N) \backslash \mathbb H^*$ and then find recurrence relations satisfied by the modular traces of the Hauptmodul for any congruence subgroup $\Gamma_0(N)$ of genus…

Number Theory · Mathematics 2020-02-07 Bumkyu Cho

In pioneering work from 2019, Barcel\'o and coauthors identified logics that precisely match the expressive power of constant iteration-depth graph neural networks (GNNs) relative to properties definable in first-order logic. In this…

Logic in Computer Science · Computer Science 2025-05-05 Veeti Ahvonen , Damian Heiman , Antti Kuusisto , Carsten Lutz

Let $f$ be a measurable, real function defined in a neighbourhood of infinity. The function $f$ is said to be of generalised regular variation if there exist functions $h \not\equiv 0$ and $g > 0$ such that $f(xt) - f(t) = h(x) g(t) +…

Classical Analysis and ODEs · Mathematics 2009-01-13 Edward Omey , Johan Segers

We propose a method to search for signs of causal structure in spatiotemporal data making minimal a priori assumptions about the underlying dynamics. To this end, we generalize the elementary concept of recurrence for a point process in…

Data Analysis, Statistics and Probability · Physics 2016-09-08 J. Davidsen , P. Grassberger , M. Paczuski

A phenomenological law, called Benford's law, states that the occurrence of the first digit, i.e., $1,2,...,9$, of numbers from many real world sources is not uniformly distributed, but instead favors smaller ones according to a logarithmic…

High Energy Physics - Phenomenology · Physics 2010-04-22 Lijing Shao , Bo-Qiang Ma

The Prime Numbers are well-known for their paradoxical stand regarding Benford's Law. On one hand they adamantly refuse to obey the law of Benford in the usual sense, namely that of a normal density of the proportion of primes with d as the…

General Mathematics · Mathematics 2016-03-29 Alex Ely Kossovsky

It is widely believed that deep neural networks contain layer specialization, wherein neural networks extract hierarchical features representing edges and patterns in shallow layers and complete objects in deeper layers. Unlike common…

Machine Learning · Computer Science 2022-03-04 Avi Schwarzschild , Arjun Gupta , Amin Ghiasi , Micah Goldblum , Tom Goldstein
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