Claudia Plant

AGNN: Alternating Graph-Regularized Neural Networks to Alleviate Over-Smoothing

2023 · arXiv (Cornell University)

Graph Convolutional Network (GCN) with the powerful capacity to explore graph-structural data has gained noticeable success in recent years. Nonetheless, most of the existing GCN-based models suffer from the notorious over-smoothing issue, owing to which …

ADEdgeDrop: Adversarial Edge Dropping for Robust Graph Neural Networks

2024 · arXiv (Cornell University)

Although Graph Neural Networks (GNNs) have exhibited the powerful ability to gather graph-structured information from neighborhood nodes via various message-passing mechanisms, the performance of GNNs is limited by poor generalization and fragile robustness caused by …