schur-decomposition

C++ Matrix -- High performance and accurate (e.g. edge cases) matrix math library with expression template arithmetic operators

Julia package for Schur decomposition of matrices with generic element types

Differentiable matrix factorizations using ImplicitDifferentiation.jl.

A Task-based Library for Solving Dense Nonsymmetric Eigenvalue Problems

Fast computation of some matrices useful in statistics

Implementation and numerical verification of fundamental Linear Algebra concepts including eigenvalues, SVD, matrix rank, fundamental subspaces, matrix polynomials, diagonalizability, Householder transformations, and Schur decomposition using Python.

Matrix Computations

Computational Linear Algebra course covering topics like iterative methods, matrix decompositions, and applications. It includes theoretical concepts, practical exercises, and code. Advanced methods like QR factorization, spectral theorem, and iterative solvers for linear systems.

Some notes on linear algebra and numerical linear algebra

This is the final course project for linear algebra course, spring of 2022.

A representation-theoretic trajectory diagnostic for quantum neural networks. The symmetry-organised complexity index measures how a QNN distributes expressive capacity across the multiplicity structure of a target symmetry, rather than how much of Hilbert space it visits.