Graph Encoder Ensemble for Simultaneous Vertex Embedding and Community Detection

• URL: http://arxiv.org/abs/2301.11290v3
• Date: Sun, 21 Jul 2024 17:26:26 GMT
• Title: Graph Encoder Ensemble for Simultaneous Vertex Embedding and Community Detection
• Authors: Cencheng Shen, Youngser Park, Carey E. Priebe,
• Abstract summary: We introduce a novel and computationally efficient method for 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.
• Score: 16.743897700396218
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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