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。该方法采用归一化独热图编码器与基于排序的聚类规模度量。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。