Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering

1 code implementation • 19 Jul 2021 • Nairouz Mrabah, Mohamed Bouguessa, Mohamed Fawzi Touati, Riadh Ksantini

We study these issues from two aspects: (1) there is a trade-off between Feature Randomness and Feature Drift when clustering and reconstruction are performed at the same level, and (2) the problem of Feature Drift is more pronounced for GAE models, compared with vanilla auto-encoder models, due to the graph convolutional operation and the graph decoding design.

Clustering Graph Clustering +1