64 citations · 95 across the 3 of their papers we have counts for
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cs.SI2022★ 28 cited
DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection
Xuanwen Huang, Yang Yang, Yang Wang +5
Graph Anomaly Detection (GAD) has recently become a hot research spot due to its practicability and theoretical value. Since GAD emphasizes the application and the rarity of anomal…
cs.LG2022★ 64 cited
DropMessage: Unifying Random Dropping for Graph Neural Networks
Taoran Fang, Zhiqing Xiao, Chunping Wang +3
Graph Neural Networks (GNNs) are powerful tools for graph representation learning. Despite their rapid development, GNNs also face some challenges, such as over-fitting, over-smoot…