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.

翻译：本文提出了一种新颖且计算高效的方法，用于顶点嵌入、社区检测及社区规模确定。我们的方法利用了归一化的独热图编码器与基于排名的聚类规模度量。通过大量仿真实验，我们证明了所提出的图编码器集成算法具有优异的数值性能。