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cs.LG2025
FairGSE: Fairness-Aware Graph Neural Network without High False Positive Rates
Zhenqiang Ye, Jinjie Lu, Tianlong Gu +2
Graph neural networks (GNNs) have emerged as the mainstream paradigm for graph representation learning due to their effective message aggregation. However, this advantage also ampl…
cs.LG2024
Towards Fair Graph Neural Networks via Graph Counterfactual without Sensitive Attributes
Xuemin Wang, Tianlong Gu, Xuguang Bao +1
Graph-structured data is ubiquitous in today's connected world, driving extensive research in graph analysis. Graph Neural Networks (GNNs) have shown great success in this field, l…