Efficient and Scalable Granular-ball Graph Coarsening Method for Large-scale Graph Node Classification

ArXi:2603.29148v1 Announce Type: cross Graph Convolutional Network (GCN) is a model that can effectively handle graph data tasks and has been successfully applied. However, for large-scale graph datasets, GCN still faces the challenge of high computational overhead, especially when the number of convolutional layers in the graph is large. Currently, there are many advanced methods that use various sampling techniques or graph coarsening techniques to alleviate the inconvenience caused during