Abstract: Real-world networks have properties such as complex interactions and large-scale structures, which pose significant computational challenges when analyzing their structural and dynamical ...

Abstract: Heterogeneous Graph Neural Networks (HGNNs) are powerful tools for deep learning on heterogeneous graphs. Typical HGNNs require repetitive message passing during training, limiting ...