17 citations · 17 across the 2 of their papers we have counts for
2 papers
cs.LG2024
SlotGAT: Slot-based Message Passing for Heterogeneous Graph Neural Network
Ziang Zhou, Jieming Shi, Renchi Yang +2
Heterogeneous graphs are ubiquitous to model complex data. There are urgent needs on powerful heterogeneous graph neural networks to effectively support important applications. We…
cs.LG2019★ 17 cited
Effective Stabilized Self-Training on Few-Labeled Graph Data
Ziang Zhou, Jieming Shi, Shengzhong Zhang +2
Graph neural networks (GNNs) are designed for semi-supervised node classification on graphs where only a subset of nodes have class labels. However, under extreme cases when very f…