Abstract: Graph contrastive learning (GCL) is emerging as a pivotal technique in graph representation learning. However, recent research indicates that GCL is vulnerable to adversarial attacks, while ...

Abstract: Graph neural networks (GNNs) are effective models for analyzing graph-structured data, but encounter challenges when training on large distributed graphs. Existing GNN training frameworks ...

This is read by an automated voice. Please report any issues or inconsistencies here. Not every exercise deserves a spot in your workout. Some lifts add more risk than reward, while others are so ...