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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

The paper describes two iterative algorithms for solving general systems of M simultaneous linear algebraic equations (SLAE) with real matrices of coefficients. The system can be determined, underdetermined, and overdetermined. Linearly…

Numerical Analysis · Mathematics 2025-10-20 A. S. Kondratiev , N. P. Polishchuk

We introduce an implicit representation of continuous, bijective, orientation-preserving maps between genus zero surfaces with or without boundary. The distortion of these maps can easily be minimized by optimizing the Ginzburg-Landau…

Graphics · Computer Science 2026-05-05 Etienne Corman , Yousuf Soliman , Robin Magnet , Mark Gillespie

This is the second installment of an exposition of an ACL2 formalization of elementary linear algebra. It extends the results of Part I, which covers the algebra of matrices over a commutative ring, but focuses on aspects of the theory that…

Discrete Mathematics · Computer Science 2025-07-28 David Russinoff

A flexible, scalable and affordable virtual reality software system architecture is proposed. This solution can be easily implemented on different hardware configurations: on a single computer or on a computer cluster. The architecture is…

Graphics · Computer Science 2013-08-28 Stoyan Maleshkov , Dimo Chotrov

This tutorial illustrates how to use Grayson and Stillman's computer algebra system, Macaulay2, to study schemes. The examples are taken from the homework for an algebraic geometry class given at the University of California, Berkeley in…

Algebraic Geometry · Mathematics 2007-05-23 Gregory G. Smith , Bernd Sturmfels

In this paper, we introduce the concept of inner derivations of low-dimensional Zinbiel algebras and investigate their properties. The primary objective of this study is to develop an algorithm to characterize the inner derivations of any…

Rings and Algebras · Mathematics 2024-12-31 Bouzid Mosbahi , Ahmed Zahari

The article presents an algebra to represent two dimensional patterns using reciprocals of polynomials. Such a representation will be useful in neural network training and it provides a method of training patterns that is much more…

Information Theory · Computer Science 2011-02-23 Subhash Kak

This paper presents a quantum algorithm for efficiently computing partial sums and specific weighted partial sums of quantum state amplitudes. Computation of partial sums has important applications, including numerical integration,…

Quantum Physics · Physics 2025-07-15 Alok Shukla , Prakash Vedula

We present the Matlab toolbox MacaulayLab, which implements numerical linear algebra algorithms for solving multivariate polynomial systems and rectangular multiparameter eigenvalue problems. Its structure and functionality are the result…

Mathematical Software · Computer Science 2026-05-21 Christof Vermeersch , Bart De Moor

We give a computational algorithm for computing Ext groups between bounded complexes of coherent sheaves on a projective variety, and we describe an implementation of this algorithm in Macaulay2. In particular, our results yield methods for…

Algebraic Geometry · Mathematics 2025-09-30 Michael K. Brown , Souvik Dey , Guanyu Li , Mahrud Sayrafi

In this paper, we present two fast matrix representation algorithms based on the recursive decomposition of multivectors into specific right and left ideals. We also examine the relation between these two representations. Furthermore, we…

Rings and Algebras · Mathematics 2024-10-10 Gleb Rumyantsev

Two numerical algorithms are proposed for computing an interval matrix containing the matrix gamma function. In 2014, the author presented algorithms for enclosing all the eigenvalues and basis of invariant subspaces of $A \in \mathbb{C}^{n…

Numerical Analysis · Mathematics 2020-01-22 Shinya Miyajima

Recent techniques have been successful in reconstructing surfaces as level sets of learned functions (such as signed distance fields) parameterized by deep neural networks. Many of these methods, however, learn only closed surfaces and are…

Computer Vision and Pattern Recognition · Computer Science 2022-03-23 David Palmer , Dmitriy Smirnov , Stephanie Wang , Albert Chern , Justin Solomon

Bilevel Optimization Programming is used to model complex and conflicting interactions between agents, for example in Robust AI or Privacy-preserving AI. Integrating bilevel mathematical programming within deep learning is thus an essential…

Machine Learning · Computer Science 2023-03-01 Francesco Alesiani

This article presents a class of modified new modulus-based iterative methods to process the large and sparse implicit complementarity problem (ICP). By using two positive diagonal matrices, we formulate a fixed-point equation which is…

Optimization and Control · Mathematics 2023-03-23 Bharat kumar , Deepmala , A. K. Das

We developed an implicit Particle-in-cell/Monte Carlo model in two-dimensional and axisymmetric geometry for the simulations of the radio-frequency discharges, by introducing several numerical schemes which include variable weights,…

Plasma Physics · Physics 2011-04-19 Hong-yu Wang , Wei Jiang , You-nian Wang

In this paper we introduce a family of rational approximations of the reciprocal of a $\phi$-function involved in the explicit solutions of certain linear differential equations, as well as in integration schemes evolving on manifolds. The…

Numerical Analysis · Mathematics 2021-05-18 Paola Boito , Yuli Eidelman , Luca Gemignani

In this paper we continue the description of the possibilities to use numerical simulations for mathematically rigorous computer assisted analysis of integrability of dynamical systems. We sketch some of the algebraic methods of studying…

Dynamical Systems · Mathematics 2014-11-18 Vladimir Salnikov

Representing shapes as level sets of neural networks has been recently proved to be useful for different shape analysis and reconstruction tasks. So far, such representations were computed using either: (i) pre-computed implicit shape…

Machine Learning · Computer Science 2020-07-10 Amos Gropp , Lior Yariv , Niv Haim , Matan Atzmon , Yaron Lipman