2 papers
cs.LG2026
AbstainGNN: Teaching Graph Neural Networks to Abstain for Graph Classification
Xixun Lin, Zhiheng Zhou, Zhengyin Zhang +9
Graph classification is a core task in graph data mining with widespread real-world applications. Recent advances in graph neural networks (GNNs) have led to substantial performanc…
cs.LG2024
FlexiDrop: Theoretical Insights and Practical Advances in Random Dropout Method on GNNs
Zhiheng Zhou, Sihao Liu, Weichen Zhao
Graph Neural Networks (GNNs) are powerful tools for handling graph-type data. Recently, GNNs have been widely applied in various domains, but they also face some issues, such as ov…