79 citations · 119 across the 6 of their papers we have counts for
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cs.LG2023★ 38 cited
Graph Contrastive Learning with Generative Adversarial Network
Cheng Wu, Chaokun Wang, Jingcao Xu +5
Graph Neural Networks (GNNs) have demonstrated promising results on exploiting node representations for many downstream tasks through supervised end-to-end training. To deal with t…
cs.LG2022
HybridGNN: Learning Hybrid Representation in Multiplex Heterogeneous Networks
Tiankai Gu, Chaokun Wang, Cheng Wu +6
Recently, graph neural networks have shown the superiority of modeling the complex topological structures in heterogeneous network-based recommender systems. Due to the diverse int…