4 citations · 6 across the 7 of their papers we have counts for
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cs.LG2022★ 4 cited
T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation
Cuiying Huo, Di Jin, Yawen Li +3
Graph Neural Networks (GNNs) have been a prevailing technique for tackling various analysis tasks on graph data. A key premise for the remarkable performance of GNNs relies on comp…
cs.LG2022★ 1 cited
Distributed Graph Neural Network Training: A Survey
Yingxia Shao, Hongzheng Li, Xizhi Gu +6
Graph neural networks (GNNs) are a type of deep learning models that are trained on graphs and have been successfully applied in various domains. Despite the effectiveness of GNNs,…