spectralGraphTopology provides estimators to learn k-component, bipartite, and k-component bipartite graphs from data by imposing spectral constraints on the eigenvalues and eigenvectors of the Laplacian and adjacency matrices. Those estimators leverages spectral properties of the graphical models as a prior information, which turn out to play key roles in unsupervised machine learning tasks such as community detection.

spectralGraphTopology is developed on GitHub: https://github.com/dppalomar/spectralGraphTopology

For documentation, installation instructions, and examples of usage, check out https://mirca.github.io/spectralGraphTopology