2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2023
HeteroNet: Heterophily-aware Representation Learning on Heterogenerous Graphs
Jintang Li, Zheng Wei, Jiawang Dan +9
Real-world graphs are typically complex, exhibiting heterogeneity in the global structure, as well as strong heterophily within local neighborhoods. While a growing body of literat…
cs.LG2023★ 1 cited
GRANDE: a neural model over directed multigraphs with application to anti-money laundering
Ruofan Wu, Boqun Ma, Hong Jin +3
The application of graph representation learning techniques to the area of financial risk management (FRM) has attracted significant attention recently. However, directly modeling…
cs.LG2023★ 2 cited
SplitGNN: Splitting GNN for Node Classification with Heterogeneous Attention
Xiaolong Xu, Lingjuan Lyu, Yihong Dong +3
With the frequent happening of privacy leakage and the enactment of privacy laws across different countries, data owners are reluctant to directly share their raw data and labels w…