Jixi Liu

FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization

Despite the remarkable success of graph neural networks (GNNs) in modeling graph-structured data, like other machine learning models, GNNs are also susceptible to making biased predictions based on sensitive attributes, such as race and gender. For fairness consideration, recent state-of-the-art (SO…