This repository aggregates deep learning methods for graph clustering, which aims to partition nodes in graph structures into meaningful groups. It covers graph neural networks, graph convolutional networks, self-supervised learning approaches, and related techniques. The collection includes published papers, accompanying code implementations, and datasets used for benchmarking clustering performance on graph data.