Fei Zhu

Towards robust Graph Neural Networks: A comprehensive strategy against graph and label noise

The increasing use of graph data in emerging domains has highlighted the importance of Graph Neural Networks (GNNs). However, traditional GNNs are highly susceptible to both graph and label noise, leading to degraded and unstable performance under noisy conditions. To address this challenge, we propose a R obust S truc...