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We introduce a functional calculus with simple syntax and operational semantics in which the calculi introduced so far in the Curry-Howard correspondence for Classical Logic can be faithfully encoded. Our calculus enjoys confluence without…

Logic in Computer Science · Computer Science 2013-04-01 Alberto Carraro , Thomas Ehrhard , Antonino Salibra

Factorization of polynomials is one of the foundations of symbolic computation. Its applications arise in numerous branches of mathematics and other sciences. However, the present advanced programming languages such as C++ and J++, do not…

Algebraic Geometry · Mathematics 2010-08-24 Yong Feng , Wenyuan Wu , Jingzhong Zhang

Previous math word problem solvers following the encoder-decoder paradigm fail to explicitly incorporate essential math symbolic constraints, leading to unexplainable and unreasonable predictions. Herein, we propose Neural-Symbolic Solver…

Computation and Language · Computer Science 2021-07-06 Jinghui Qin , Xiaodan Liang , Yining Hong , Jianheng Tang , Liang Lin

The paper develops a symbolic calculus for Fourier integral operators associated with canonical transformations.

Analysis of PDEs · Mathematics 2013-08-20 Yuri Safarov

In the paper which inspired the SC-Square project, [E. Abraham, Building Bridges between Symbolic Computation and Satisfiability Checking, Proc. ISSAC '15, pp. 1-6, ACM, 2015] the author identified the use of sophisticated heuristics as a…

Symbolic Computation · Computer Science 2017-03-14 Matthew England , James H. Davenport

Machine-learning methods are gradually being adopted in a wide variety of social, economic, and scientific contexts, yet they are notorious for struggling with exact mathematics. A typical example is computer algebra, which includes tasks…

Machine Learning · Computer Science 2024-11-06 Lennart Dabelow , Masahito Ueda

Cartogram drawing is a technique for showing geography-related statistical information, such as demographic and epidemiological data. The idea is to distort a map by resizing its regions according to a statistical parameter by keeping the…

Computation · Statistics 2018-08-30 Christian Panse

Over the last decades, deep neural networks based-models became the dominant paradigm in machine learning. Further, the use of artificial neural networks in symbolic learning has been seen as increasingly relevant recently. To study the…

Machine Learning · Computer Science 2025-06-03 João Flach , Alvaro F. Moreira , Luis C. Lamb

Template metaprogramming is a popular technique for implementing compile time mechanisms for numerical computing. We demonstrate how expression templates can be used for compile time symbolic differentiation of algebraic expressions in C++…

Symbolic Computation · Computer Science 2017-05-05 Drosos Kourounis , Leonidas Gergidis , Michael Saunders , Andrea Walther , Olaf Schenk

This article introduces the Mathematica package \emph{HEPMath} which provides a number of utilities and algorithms for High Energy Physics computations in Mathematica. Its functionality is similar to packages like FormCalc or FeynCalc, but…

High Energy Physics - Phenomenology · Physics 2015-07-08 Martin Wiebusch

In the present paper by using Mathematica system a symbolic programming method for generation of the expressions of the expansion terms of atomic stationary perturbation theory (PT) is presented. For this purpose, the package named as…

Atomic Physics · Physics 2010-04-30 Rytis Jursenas , Gintaras Merkelis

This paper develops new combinatorial approaches to analyze and compute special set partitions, called complementary set partitions, which are fundamental in the study of generalized cumulants. Moving away from traditional graph-based and…

Statistics Theory · Mathematics 2025-05-20 Elvira Di Nardo , Giuseppe Guarino

Symbolic computation, powered by modern computer algebra systems, has important applications in mathematical reasoning through exact deep computations. The efficiency of symbolic computation is largely constrained by such deep computations…

Symbolic Computation · Computer Science 2026-01-21 Rui-Juan Jing , Yuegang Zhao , Changbo Chen

The Functional Machine Calculus (Heijltjes 2022) is a new approach to unifying the imperative and functional programming paradigms. It extends the lambda-calculus, preserving the key features of confluent reduction and typed termination, to…

Programming Languages · Computer Science 2026-03-03 Willem Heijltjes

Symbolic integration over the Haar measure of compact groups is a computational cornerstone in quantum information science and random matrix theory. We present \texttt{IntegrateUnitary.jl}, a comprehensive Julia package for computing exact…

Quantum Physics · Physics 2026-05-25 Łukasz Pawela , Zbigniew Puchała

This paper presents a series of general properties of the r-Complexity calculus, a complexity measurement for assessing the performance and asymptotic behaviour of real-world algorithms. This research describes characteristics such as…

Computational Complexity · Computer Science 2026-01-27 Rares Folea , Emil Slusanschi

In this article, we present a recently released R package for Bayesian calibration. Many industrial fields are facing unfeasible or costly field experiments. These experiments are replaced with numerical/computer experiments which are…

Computation · Statistics 2018-08-30 Mathieu Carmassi , Pierre Barbillon , Matthieu Chiodetti , Merlin Keller , Eric Parent

In this paper, we briefly discuss the dynamic and functional approach to computer symbolic tensor analysis. The ccgrg package for Wolfram Language/Mathematica is used to illustrate this approach. Some examples of applications are attached.

Symbolic Computation · Computer Science 2016-03-21 A. Woszczyna , P. Plaszczyk , W. Czaja , Z. A. Golda

This document is the manual for a free Mathematica package for computing with harmonic functions. This package allows the user to make calculations that would take a prohibitive amount of time if done without a computer. For example, the…

Mathematical Software · Computer Science 2016-11-08 Sheldon Axler

Taylor series methods show a newfound promise for the solution of non-stiff ordinary differential equations (ODEs) given the rise of new compiler-enhanced techniques for calculating high order derivatives. In this paper we detail a new…

Numerical Analysis · Mathematics 2026-02-20 Songchen Tan , Oscar Smith , Christopher Rackauckas