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Due to the occurrence of large exceptional Lie groups in supergravity, calculations involving explicit Lie algebra and Lie group element manipulations easily become very complicated and hence also error-prone if done by hand. Research on…

High Energy Physics - Theory · Physics 2007-05-23 Thomas Fischbacher

Algorithm parameters, in particular hyperparameters of machine learning algorithms, can substantially impact their performance. To support users in determining well-performing hyperparameter configurations for their algorithms, datasets and…

This preprint contains a description of a package for Mathematica called EinS. This package allows one to perform various calculations with indexed objects.

General Relativity and Quantum Cosmology · Physics 2007-05-23 Sergei A. Klioner

We present the Mathematica package MultivariateResidues, which allows for the efficient evaluation of multivariate residues based on methods from computational algebraic geometry. Multivariate residues appear in several contexts of…

High Energy Physics - Theory · Physics 2018-10-04 Kasper J. Larsen , Robbert Rietkerk

I present a brief overview of a variety of computational tools for supersymmetry calculations, including: spectrum generators, cross section and branching fraction calculators, low energy constraints, general purpose event generators,…

High Energy Physics - Phenomenology · Physics 2016-12-21 Howard Baer

Sparse models, including sparse Mixture-of-Experts (MoE) models, have emerged as an effective approach for scaling Transformer models. However, they often suffer from computational inefficiency since a significant number of parameters are…

Machine Learning · Computer Science 2024-05-27 Yuanhang Yang , Shiyi Qi , Wenchao Gu , Chaozheng Wang , Cuiyun Gao , Zenglin Xu

Package-X, a Mathematica package for the analytic computation of one-loop integrals dimensionally regulated near 4 spacetime dimensions is described. Package-X computes arbitrarily high rank tensor integrals with up to three propagators,…

High Energy Physics - Phenomenology · Physics 2015-12-01 Hiren H. Patel

This paper presents Sparse Partitioning, a Bayesian method for identifying predictors that either individually or in combination with others affect a response variable. The method is designed for regression problems involving binary or…

Quantitative Methods · Quantitative Biology 2011-08-31 Doug Speed , Simon Tavaré

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

Conjugate gradient is an efficient algorithm for solving large sparse linear systems. It has been utilized to accelerate the computation in Bayesian analysis for many large-scale problems. This article discusses the applications of…

Methodology · Statistics 2023-08-30 Lu Zhang

Resultants are important special functions used in description of non-linear phenomena. Resultant $R_{r_1, ..., r_n}$ defines a condition of solvability for a system of $n$ homogeneous polynomials of degrees $r_1, ..., r_n$ in $n$…

Algebraic Geometry · Mathematics 2008-07-30 A. Morozov , Sh. Shakirov

This article presents a new method to compute matrices from numerical simulations based on the ideas of sparse sampling and compressed sensing. The method is useful for problems where the determination of the entries of a matrix constitutes…

Chemical Physics · Physics 2014-10-21 Jacob N. Sanders , Xavier Andrade , Alán Aspuru-Guzik

In this article we show how to compute a matrix representation and the implicit equation by means of the method developed in [Botbol: arXiv:1007.3437], using the computer algebra system Macaulay2 \cite{M2}. As it is probably the most…

Algebraic Geometry · Mathematics 2010-07-22 Nicolas Botbol

We give an overview of a Macaulay2 package for computing with the multigraded BGG correspondence. This software builds on the package BGG due to Abo-Decker-Eisenbud-Schreyer-Smith-Stillman, which concerns the standard graded BGG…

Commutative Algebra · Mathematics 2025-11-26 Maya Banks , Michael K. Brown , Tara Gomes , Prashanth Sridhar , Eduardo Torres Davila , Sasha Zotine

We introduce SP$\mathbb{Q}$R, a new Mathematica package for the division and elimination of variables from polynomial systems. SP$\mathbb{Q}$R works by sampling and reconstructing results over finite fields, in an analogous manner to many…

High Energy Physics - Theory · Physics 2025-11-20 Vsevolod Chestnov , Giulio Crisanti

In a previous paper it was shown that a machine learning regression problem can be solved within the framework of random function theory, with the optimal kernel analytically derived from symmetry and indifference principles and coinciding…

Machine Learning · Computer Science 2025-12-19 Yuriy N. Bakhvalov

We present formulas for the homogenous multivariate resultant as a quotient of two determinants. They extend classical Macaulay formulas, and involve matrices of considerably smaller size, whose non zero entries include coefficients of the…

Algebraic Geometry · Mathematics 2007-05-23 Carlos D'Andrea , Alicia Dickenstein

One of the biggest open problems in computational algebra is the design of efficient algorithms for Gr{\"o}bner basis computations that take into account the sparsity of the input polynomials. We can perform such computations in the case of…

Symbolic Computation · Computer Science 2018-06-22 Matías Bender , Jean-Charles Faugère , Elias Tsigaridas

We introduce the Macaulay2 package HomologicalShiftIdeals. It allows to compute the homological shift ideals of a monomial ideal, and to check the homological shift properties, including having linear resolution, having linear quotients, or…

Commutative Algebra · Mathematics 2023-09-19 Antonino Ficarra

Efficient solutions of large-scale, ill-conditioned and indefinite algebraic equations are ubiquitously needed in numerous computational fields, including multiphysics simulations, machine learning, and data science. Because of their…

Mathematical Software · Computer Science 2026-05-25 Xiaoye Sherry Li , Yang Liu
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