/HypergraphModularity

Code for generative hypergraph clustering via modularity-like objective functions.

Primary LanguageJupyter NotebookMIT LicenseMIT

Generative Hypergraph Clustering: From Blockmodels to Modularities

Phil Chodrow (UCLA), Nate Veldt (Cornell), and Austin Benson (Cornell)

This code is not the best one for users! To use this algorithm, use the Julia package hosted by Nate Veldt.

Code for our paper "Generative hypergraph clustering: from blockmodels to modularities," on hypergraph clustering via approximate maximum-likelihood inference in a degree-corrected hypergraph stochastic blockmodel. The code in this repository is sufficient to reproduce the main results and figures of the preprint. We intend to release soon a Julia package for hypergraph clustering via the presented methods.

You can also access the data sets used in this paper hosted on Austin Benson's website.