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The integral image, an intermediate image representation, has found extensive use in multi-scale local feature detection algorithms, such as Speeded-Up Robust Features (SURF), allowing fast computation of rectangular features at constant…

Computer Vision and Pattern Recognition · Computer Science 2015-10-20 Shoaib Ehsan , Adrian F. Clark , Naveed ur Rehman , Klaus D. McDonald-Maier

We present algorithms to work with iterated Eisenstein integrals that have recently appeared in the computation of multi-loop Feynman integrals. These algorithms allow one to analytically continue these integrals to all regions of the…

High Energy Physics - Theory · Physics 2020-03-18 Claude Duhr , Lorenzo Tancredi

The aim of these notes is to provide a reasonably short and "hands-on" introduction to the differential calculus on associative algebras over a field of characteristic zero. Following a suggestion of Ginzburg's we call the resulting theory…

Mathematical Physics · Physics 2017-06-28 Alberto Tacchella

We introduce a general class of algorithms and supply a number of general results useful for analysing these algorithms when applied to regular graphs of large girth. As a result, we can transfer a number of results proved for random…

Combinatorics · Mathematics 2017-03-06 Carlos Hoppen , Nicholas Wormald

Symbolic summation as an active research topic of symbolic computation provides efficient algorithmic tools for evaluating and simplifying different types of sums arising from mathematics, computer science, physics and other areas. Most of…

Symbolic Computation · Computer Science 2025-03-18 Shaoshi Chen , Lixin Du , Hanqian Fang

Education in the practical applications of logic and proving such as the formal specification and verification of computer programs is substantially hampered by the fact that most time and effort that is invested in proving is actually…

Logic in Computer Science · Computer Science 2018-03-06 Wolfgang Schreiner , Alexander Brunhuemer , Christoph Fürst

Recent algorithmic advances in algebraic automata theory drew attention to semigroupoids (semicategories). These are mathematical descriptions of typed computational processes, but they have not been studied systematically in the context of…

Formal Languages and Automata Theory · Computer Science 2025-09-30 Attila Egri-Nagy , Chrystopher L. Nehaniv

This work presents a brief discussion and a plan towards the analytical solving of Partial Differential Equations (PDEs) using symbolic computing, as well as an implementation of part of this plan as the PDEtools software-package of…

General Relativity and Quantum Cosmology · Physics 2016-03-23 E. S. Cheb-Terrab , K. von Bulow

Discrete abstractions of continuous and hybrid systems have recently been the topic of great interest from both the control systems and the computer science communities, because they provide a sound mathematical framework for analysing and…

Optimization and Control · Mathematics 2010-06-16 Giordano Pola , Alessandro Borri , Maria D. Di Benedetto

We consider the problem of symbolic-numeric integration of symbolic functions, focusing on rational functions. Using a hybrid method allows the stable yet efficient computation of symbolic antiderivatives while avoiding issues of…

Symbolic Computation · Computer Science 2018-10-26 Robert M. Corless , Robert H. C. Moir , Marc Moreno Maza , Ning Xie

In the last decade major steps towards an algorithmic treatment of orthogonal polynomials and special functions (OP & SF) have been made, notably Zeilberger's brilliant extension of Gosper's algorithm on algorithmic definite hypergeometric…

Classical Analysis and ODEs · Mathematics 2007-05-23 Wolfram Koepf

Differentially-algebraic (D-algebraic) functions are solutions of polynomial equations in the function, its derivatives, and the independent variables. We revisit closure properties of these functions by providing constructive proofs. We…

Algebraic Geometry · Mathematics 2024-08-27 Rida Ait El Manssour , Anna-Laura Sattelberger , Bertrand Teguia Tabuguia

We introduce Exhaustive Symbolic Integration (ESI), a method that enumerates all symbolic functions up to a given complexity $k$ within a specified operator basis and determines which admit closed-form antiderivatives within the same class.…

Symbolic Computation · Computer Science 2026-05-07 Harry Desmond

Compact closed categories provide a foundational formalism for a variety of important domains, including quantum computation. These categories have a natural visualisation as a form of graphs. We present a formalism for equational reasoning…

Symbolic Computation · Computer Science 2009-02-04 Lucas Dixon , Ross Duncan

By using Cauchy integral formula in the theory of complex functions, the authors establish some integral representations for the principal branches of several complex functions involving the logarithmic function, find some properties, such…

Classical Analysis and ODEs · Mathematics 2016-08-22 Feng Qi , Wen-Hui Li

Hashing algorithm of dynamical set of distances is described. Proposed hashing function is residual. Data structure which implementation accelerates computations is presented

Data Structures and Algorithms · Computer Science 2019-01-30 I. A. Junussov

Analytical solutions to differential equations offer exact, interpretable insight but are rarely available because discovering them requires expert intuition or exhaustive search of combinatorial spaces. We introduce SIGS, a neuro-symbolic…

Machine Learning · Computer Science 2026-05-22 Orestis Oikonomou , Levi Lingsch , Dana Grund , Siddhartha Mishra , Georgios Kissas

In this article we give an algorithm for computing the integral closure of a reduced Noetherian ring R, in case this integral closure is finitely generated over R.

alg-geom · Mathematics 2008-02-03 Theo de Jong

We review our algebraic framework for linear boundary problems (concentrating on ordinary differential equations). Its starting point is an appropriate algebraization of the domain of functions, which we have named integro-differential…

Symbolic Computation · Computer Science 2012-10-11 Markus Rosenkranz , Georg Regensburger , Loredana Tec , Bruno Buchberger

We introduce an Invertible Symbolic Regression (ISR) method. It is a machine learning technique that generates analytical relationships between inputs and outputs of a given dataset via invertible maps (or architectures). The proposed ISR…

Machine Learning · Computer Science 2024-05-14 Tony Tohme , Mohammad Javad Khojasteh , Mohsen Sadr , Florian Meyer , Kamal Youcef-Toumi