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Found 4 papers, 0 papers with code
Unsupervised Optimisation of GNNs for Node Clustering
Although modularity is a graph partitioning quality metric, we show that this can be used to optimise GNNs that also encode features without a drop in performance.
A Framework for Exploring Federated Community Detection
Federated Learning is machine learning in the context of a network of clients whilst maintaining data residency and/or privacy constraints.
Uncertainty in GNN Learning Evaluations: A Comparison Between Measures for Quantifying Randomness in GNN Community Detection
(1) The enhanced capability of Graph Neural Networks (GNNs) in unsupervised community detection of clustered nodes is attributed to their capacity to encode both the connectivity and feature information spaces of graphs.
Uncertainty in GNN Learning Evaluations: The Importance of a Consistent Benchmark for Community Detection
We find that by ensuring the same evaluation criteria is followed, there may be significant differences from the reported performance of methods at this task, but a more complete evaluation and comparison of methods is possible.
