20 citations · 21 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
CPDG: A Contrastive Pre-Training Method for Dynamic Graph Neural Networks
Yuanchen Bei, Hao Xu, Sheng Zhou +5
Dynamic graph data mining has gained popularity in recent years due to the rich information contained in dynamic graphs and their widespread use in the real world. Despite the adva…
cs.LG2021★ 20 cited
GraphPAS: Parallel Architecture Search for Graph Neural Networks
Jiamin Chen, Jianliang Gao, Yibo Chen +3
Graph neural architecture search has received a lot of attention as Graph Neural Networks (GNNs) has been successfully applied on the non-Euclidean data recently. However, explorin…