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Graph Encoder Ensemble for Simultaneous Vertex Embedding and Community Detection

Cencheng Shen
Youngser Park
Carey E. Priebe
Abstract

In this paper, we introduce a novel and computationally efficient method for vertex embedding, community detection, and community size determination. Our approach leverages a normalized one-hot graph encoder and a rank-based cluster size measure. Through extensive simulations, we demonstrate the excellent numerical performance of our proposed graph encoder ensemble algorithm.

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