3 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
Self-supervision meets kernel graph neural models: From architecture to augmentations
Jiawang Dan, Ruofan Wu, Yunpeng Liu +8
Graph representation learning has now become the de facto standard when handling graph-structured data, with the framework of message-passing graph neural networks (MPNN) being the…
cs.LG2023★ 3 cited
DEDGAT: Dual Embedding of Directed Graph Attention Networks for Detecting Financial Risk
Jiafu Wu, Mufeng Yao, Dong Wu +6
Graph representation plays an important role in the field of financial risk control, where the relationship among users can be constructed in a graph manner. In practical scenarios…