87 citations · 115 across the 6 of their papers we have counts for
Showing 2022Show all
2 papers · 1 filter
cs.LG2022★ 87 cited
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
Enyan Dai, Tianxiang Zhao, Huaisheng Zhu +5
Graph Neural Networks (GNNs) have made rapid developments in the recent years. Due to their great ability in modeling graph-structured data, GNNs are vastly used in various applica…
cs.LG2022★ 1 cited
Learning Fair Models without Sensitive Attributes: A Generative Approach
Huaisheng Zhu, Enyan Dai, Hui Liu +1
Most existing fair classifiers rely on sensitive attributes to achieve fairness. However, for many scenarios, we cannot obtain sensitive attributes due to privacy and legal issues.…