cholesky

Backpropagate derivatives through the Cholesky decomposition

Sympiler is a Code Generator for Transforming Sparse Matrix Codes

Set up cholmod and scikit-sparse python package on Windows.

Sparse symmetric indefinite solver implemented with a runtime system

Fast routines for solving large systems of linear equations in R. Makes Eigen Cholesky-, LU-, QR-, and iterative (Conjugate Gradient, BiCGSTAB) solvers for both dense and sparse problems available.

Parallel approximate-Cholesky preconditioner and PCG solver for graph-Laplacian and SDDM linear systems (C++23, OpenMP/CUDA, Python bindings)

Autonomous Agent Cholesky Decomposition LL^T Solver for Symmetric Positive-Definite Covariance Matrices

Autonomous Agent Cholesky Decomposition LL^T Solver for Symmetric Positive-Definite Covariance Matrices

Fast selected inversion of sparse matrices

This package contains implementations of efficient representations and updating algorithms for Cholesky factorizations.

Numerical methods for engineers used for finding roots, solving matrix, finding functions from given values, performing integrals whose analytical solution is exhaustive, and solutions by approximation for differential equations.

Algoritmos de cálculo numérico usados para estudos e análise de complexidade

Rank-1 update and downdate of Cholesky factorization

JAMA : A Java Matrix Package. Fork of the original project.

Python and C# interoperability

Compute the `L * D * L^T` factorization of a real symmetric positive definite tridiagonal matrix `A`.

Small library for calculating the cholesky of a sparse matrix in parallel.

Repository for benchmarking linear solvers on GPU.

C# tool that computes Cholesky decomposition

C++26 powered GPU-accelerated scientific apps