Machine learning methods based on spectral clustering.
- LAPACK — Linear Algebra PACKage is written in Fortran 90 and provides routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems.
- Lapack++ (Linear Algebra PACKage in C++) is a software library for numerical linear algebra that solves systems of linear equations and eigenvalue problems on high performance computer architectures.
- CLAPACK was built using a Fortran to C conversion utility called f2c.
- C wrapper for LAPACK.
- BLOPEX (Block Locally Optimal Preconditioned Eigenvalue Xolvers) is a package, written in C and MATLAB/OCTAVE, that includes an eigensolver implemented with the Locally Optimal Block Preconditioned Conjugate Gradient Method (LOBPCG).
- LOBPCG in SciPy.
- LOBPCG in Pytorch.
- ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems.
- RPACK-NG a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems.
- Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms.
- spectra is a header-only C++ library for large scale eigenvalue problems.
- HYPRE.
- SLEPc and PETSc.
Our work builds on and uses codes from:
- rsc
- fastsc
- Spectral Clustering in scikit-learn
- pygco
We'd like to thank the authors for making these libraries available.
Apache-2.0 License