LAPACK development repository

Face Recognition using method of Eigenfaces

A collection of matrix-free iterative eigensolvers

V library to develop Artificial Intelligence and High-Performance Scientific Computations

Explore linear algebraic concepts 📊 from eigen vectors to vector decomposition 💡 in this GitHub repository! Dive into coding solutions 🖥️ for a range of problems and enhance your understanding of fundamental concepts in linear algebra. 🚀

Rust Scientific Libary. ODE and DAE (Runge-Kutta) solvers. Special functions (Bessel, Elliptic, Beta, Gamma, Erf). Linear algebra. Sparse solvers (MUMPS, UMFPACK). Probability distributions. Tensor calculus.

Code to the paper: A First Approach to Quantum Logical Shape Classification Framework

Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations.

Why should you care about Eigenvectors? A study on the efficacy of using eigenfaces in image classification.

The Arnoldi Method with Krylov-Schur restart, natively in Julia.

Modularized Fortran LAPACK implementation

PCA in c

complexarith is an attempt to model the complex field arithmetic in Java to be used in mathematical developments.

The Hari-Zimmermann complex generalized hyperbolic SVD and EVD.

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

Hamming Network implementation using PCA implementation from scratch

helmholtz-x

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.

Julia package for Schur decomposition of matrices with generic element types