Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most difficult tasks in numerical ...

Computing the inverse of a matrix is one of the most important operations in machine learning. If some matrix A has shape n-by-n, then its inverse matrix Ai is n-by-n and the matrix product of Ai * A ...

Drazin inverses and their modern generalisations constitute a pivotal area of operator theory within Banach algebras. These inverse concepts extend the classic notion of the matrix inverse to settings ...

This article proposes a method for computing the Moore–Penrose inverse of a complex matrix using polynomials in matrices. Such a method is valid for all matrices and does not involve spectral ...

We generalize a result stating that a nonnegative finite square matrix has a nonnegative inverse if and only if it is the product of a permutation matrix by a diagonal matrix. We consider ...

NumPy includes some tools for working with linear algebra in the numpy.linalg module. However, unless you really don’t want to add SciPy as a dependency to your project, it’s typically better to use ...

Circulant matrices are a special class of structured matrices that underpin a diverse range of applications in mathematics and engineering. Characterised by the property that each row is a cyclic ...