hypergraphs

Language, Knowledge, Cognition

Cleora AI is a general-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data.

KaHyPar (Karlsruhe Hypergraph Partitioning) is a multilevel hypergraph partitioning framework providing direct k-way and recursive bisection based partitioning algorithms that compute solutions of very high quality.

Hypergraph is data structure library to create a directed hypergraph in which a hyperedge can join any number of vertices.

CompleX Group Interactions (XGI) provides an ecosystem for the analysis and representation of complex systems with group interactions.

hypergraph representation learning, graph neural network

Mt-KaHyPar (Multi-Threaded Karlsruhe Hypergraph Partitioner) is a shared-memory multilevel hypergraph partitioner equipped with parallel implementations of techniques employed in most sequential state-of-the-art hypergraph partitioners. Mt-KaHyPar can partition extremely large hypergraphs very fast and with high quality.

Chapel HyperGraph Library (CHGL) - HPC-class Hypergraphs in Chapel

New Algorithms for Learning on Hypergraphs

Data and source code for the paper "How choosing random-walk model and network representation matters for flow-based community detection in hypergraphs"

Python binding for reticula

Hypergraph Case-Based Reasoning

A simple python package for graph theory that supports multi-edges, hyper-edges, looped-edges and every other combination of these.

All the world's a (hyper)graph

Source code for VLDB 2020 paper "Hypergraph Motifs: Concepts, Algorithms, and Discoveries."

Source code for ICDM 2021 paper "THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact Counting."

Library for epidemics on hypergraphs

Source code for IJCAI 2022 paper "HashNWalk: Hash and Random Walk Based Anomaly Detection in Hyperedge Streams."

embeddings for hyperedges in a hypergraph

A package for the practical use of hypergraphs in R