4 citations · 14 across the 10 of their papers we have counts for
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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…