CSGNN: Conquering Noisy Node labels via Dynamic Class-wise Selection

Yifan Li, Zhen Tan, Kai Shu +3

Graph Neural Networks (GNNs) have emerged as a powerful tool for representation learning on graphs, but they often suffer from overfitting and label noise issues, especially when t…