15 citations · 23 across the 5 of their papers we have counts for
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cs.LG2023★ 4 cited
Graph-based Knowledge Distillation: A survey and experimental evaluation
Jing Liu, Tongya Zheng, Guanzheng Zhang +1
Graph, such as citation networks, social networks, and transportation networks, are prevalent in the real world. Graph Neural Networks (GNNs) have gained widespread attention for t…
cs.LG2022
HIRE: Distilling High-order Relational Knowledge From Heterogeneous Graph Neural Networks
Jing Liu, Tongya Zheng, Qinfen Hao
Researchers have recently proposed plenty of heterogeneous graph neural networks (HGNNs) due to the ubiquity of heterogeneous graphs in both academic and industrial areas. Instead…
cs.LG2021★ 15 cited
Residual Network and Embedding Usage: New Tricks of Node Classification with Graph Convolutional Networks
Huixuan Chi, Yuying Wang, Qinfen Hao +1
Graph Convolutional Networks (GCNs) and subsequent variants have been proposed to solve tasks on graphs, especially node classification tasks. In the literature, however, most tric…