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.
@article{arxiv.2301.11290,
title = {Graph Encoder Ensemble for Simultaneous Vertex Embedding and Community Detection},
author = {Cencheng Shen and Youngser Park and Carey E. Priebe},
journal= {arXiv preprint arXiv:2301.11290},
year = {2024}
}