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DIGRAC: Digraph Clustering Based on Flow Imbalance. (arXiv:2106.05194v6 [stat.ML] UPDATED)
May 25, 2022, 1:11 a.m. | Yixuan He, Gesine Reinert, Mihai Cucuringu
stat.ML updates on arXiv.org arxiv.org
Node clustering is a powerful tool in the analysis of networks. We introduce
a graph neural network framework to obtain node embeddings for directed
networks in a self-supervised manner, including a novel probabilistic imbalance
loss, which can be used for network clustering. Here, we propose directed flow
imbalance measures, which are tightly related to directionality, to reveal
clusters in the network even when there is no density difference between
clusters. In contrast to standard approaches in the literature, in this …
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