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cs.LG2024★ 2 cited
When Heterophily Meets Heterogeneity: Challenges and a New Large-Scale Graph Benchmark
Junhong Lin, Xiaojie Guo, Shuaicheng Zhang +2
Graph mining has become crucial in fields such as social science, finance, and cybersecurity. Many large-scale real-world networks exhibit both heterogeneity, where multiple node a…
stat.ML2024★ 1 cited
PAC-Bayesian Adversarially Robust Generalization Bounds for Graph Neural Network
Tan Sun, Junhong Lin
Graph neural networks (GNNs) have gained popularity for various graph-related tasks. However, similar to deep neural networks, GNNs are also vulnerable to adversarial attacks. Empi…