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In this article we consider a method for proving a class of analytical inequalities via minimax rational approximations. All numerical calculations in this paper are given by Maple computer program.

Classical Analysis and ODEs · Mathematics 2007-05-23 Branko J. Malesevic

In this paper, we present an algorithm which computes a fundamental matrix of formal solutions of completely integrable Pfaffian systems with normal crossings in two variables, based on (Barkatou, 1997). A first step was set in…

Analysis of PDEs · Mathematics 2014-01-22 Moulay Barkatou , Suzy S. Maddah , Hassan Abbas

The approach to curve implicitization through Sylvester and Bezout resultant matrices and bivariate interpolation in the usual power basis is extended to the case of Bernstein-Bezoutian matrices constructed when the polynomials are given in…

Numerical Analysis · Mathematics 2007-05-23 Ana Marco , Jose-Javier Martinez

We present different methods for symbolic computer algebra computations in higher dimensional (\ge9) Clifford algebras using the \Clifford\ and \Bigebra\ packages for \Maple(R). This is achieved using graded tensor decompositions,…

Mathematical Physics · Physics 2012-06-19 Rafal Ablamowicz , Bertfried Fauser

This paper presents a generalised symbolic algorithm for solving systems of linear algebraic equations with multi-diagonal coefficient matrices. The algorithm is given in a pseudocode. A theorem which gives the condition for correctness of…

Symbolic Computation · Computer Science 2026-05-22 Milena Veneva

In this paper we report on an application of computer algebra in which mathematical puzzles are generated of a type that had been widely used in mathematics contests by a large number of participants worldwide. The algorithmic aspect of our…

Symbolic Computation · Computer Science 2016-08-03 Thomas Wolf , Chimaobi Amadi

This paper reviews gradient-based techniques to solve bilevel optimization problems. Bilevel optimization is a general way to frame the learning of systems that are implicitly defined through a quantity that they minimize. This…

Machine Learning · Computer Science 2023-05-26 Nicolas Zucchet , João Sacramento

Tropical implicitization means computing the tropicalization of a unirational variety from its parametrization. In the case of a hypersurface, this amounts to finding the Newton polytope of the implicit equation, without computing its…

Algebraic Geometry · Mathematics 2023-06-23 Kemal Rose , Bernd Sturmfels , Simon Telen

We present the $\textit{NumericalImplicitization}$ package for $\textit{Macaulay2}$, which allows for user-friendly computation of the invariants of the image of a polynomial map, such as dimension, degree, and Hilbert function values. This…

Algebraic Geometry · Mathematics 2019-10-16 Justin Chen , Joe Kileel

We report on the computation of invariants, covariants, and contravariants of cubic surfaces. All algorithms are implemented in the computer algebra system magma.

Algebraic Geometry · Mathematics 2019-09-04 Andreas-Stephan Elsenhans , Jörg Jahnel

A matrix-compression algorithm is derived from a novel isogenic block decomposition for square matrices. The resulting compression and inflation operations possess strong functorial and spectral-permanence properties. The basic observation…

Rings and Algebras · Mathematics 2022-11-01 Alexander Belton , Dominique Guillot , Apoorva Khare , Mihai Putinar

Neural implicit surface representations have recently emerged as popular alternative to explicit 3D object encodings, such as polygonal meshes, tabulated points, or voxels. While significant work has improved the geometric fidelity of these…

Graphics · Computer Science 2023-06-27 Yanran Guan , Andrei Chubarau , Ruby Rao , Derek Nowrouzezahrai

We introduce an efficient algorithmic procedure for implementing the direct formula that represents the product of splines in the B-spline basis. We first demonstrate the relevance of this direct approach through numerical evidence showing…

Numerical Analysis · Mathematics 2026-05-14 Francesco Patrizi , Alessandra Sestini

We study a general class of bilevel problems, consisting in the minimization of an upper-level objective which depends on the solution to a parametric fixed-point equation. Important instances arising in machine learning include…

Machine Learning · Statistics 2020-07-13 Riccardo Grazzi , Luca Franceschi , Massimiliano Pontil , Saverio Salzo

In this paper, a class of smoothing modulus-based iterative method was presented for solving implicit complementarity problems. The main idea was to transform the implicit complementarity problem into an equivalent implicit fixed-point…

Numerical Analysis · Mathematics 2023-06-09 Cong Guo , Chenliang Li , Tao Luo

We explain a Macaulay2 implementation of a construction, which appeared in [Holweck-Oeding arXiv:2206.13662], of a graded algebra structure on the direct sum of a Lie algebra $\mathfrak{g}$ (typically $\mathfrak{sl}_n$) and a…

Algebraic Geometry · Mathematics 2025-11-26 Luke Oeding

A new fast algebraic method for obtaining an $\mathcal{H}^2$-approximation of a matrix from its entries is presented. The main idea behind the method is based on the nested representation and the maximum-volume principle to select…

Numerical Analysis · Mathematics 2015-11-17 A. Yu Mikhalev , I. V. Oseledets

Matrix operations such as matrix inversion, eigenvalue decomposition, singular value decomposition are ubiquitous in real-world applications. Unfortunately, many of these matrix operations so time and memory expensive that they are…

Mathematical Software · Computer Science 2015-11-04 Shusen Wang

We give an overview of the Macaulay2 package Matroids, which contains functionality to create and compute with matroids. Examples highlighting the use of all major functions in the package are provided, along with explanations of some of…

Combinatorics · Mathematics 2019-10-16 Justin Chen

Recent advances in implicit neural representations show great promise when it comes to generating numerical solutions to partial differential equations. Compared to conventional alternatives, such representations employ parameterized neural…

Machine Learning · Computer Science 2021-11-29 Jonas Zehnder , Yue Li , Stelian Coros , Bernhard Thomaszewski