787 citations · 1.2k across the 7 of their papers we have counts for
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cs.LG2020★ 787 cited
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training
Jiezhong Qiu, Qibin Chen, Yuxiao Dong +5
Graph representation learning has emerged as a powerful technique for addressing real-world problems. Various downstream graph learning tasks have benefited from its recent develop…
cs.LG2020★ 71 cited
GPT-GNN: Generative Pre-Training of Graph Neural Networks
Ziniu Hu, Yuxiao Dong, Kuansan Wang +2
Graph neural networks (GNNs) have been demonstrated to be powerful in modeling graph-structured data. However, training GNNs usually requires abundant task-specific labeled data, w…
cs.LG2020★ 30 cited
Heterogeneous Graph Transformer
Ziniu Hu, Yuxiao Dong, Kuansan Wang +1
Recent years have witnessed the emerging success of graph neural networks (GNNs) for modeling structured data. However, most GNNs are designed for homogeneous graphs, in which all…