Supervised community detection with line graph neural networks

A Bayesian model+algorithm for community detection in bipartite networks

Community Detection in Graphs (master's degree short project)

Bayesian network models for inferring core-periphery structure

Pruning tool to identify small subsets of network partitions that are significant from the perspective of stochastic block model inference. This method works for single-layer and multi-layer networks, as well as for restricting focus to a fixed number of communities when desired.

Software that simulates voting processes and compares electoral systems. A network of voters is generated by the Stochastic Block Model or a distance-based model. Opinion dynamics are run on the network with options for zealots and media bias. Different electoral systems are supported with high flexibility to accommodate real-world systems.”

[NeurIPS 2023] Official implementation of "A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks"

Neural Network based Stochastic Blockmodel using Variational Inference

Relational Data Learning

Variational Inference for Random Graph Models

Mixed Membership Stochastic Block Models

Hedonic Game Theory for Community Detection