1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Fairness-Aware Graph Representation Learning with Limited Demographic Information
Zichong Wang, Zhipeng Yin, Liping Yang +4
Ensuring fairness in Graph Neural Networks is fundamental to promoting trustworthy and socially responsible machine learning systems. In response, numerous fair graph learning meth…
cs.LG2024
RW-NSGCN: A Robust Approach to Structural Attacks via Negative Sampling
Shuqi He, Jun Zhuang, Ding Wang +1
Node classification using Graph Neural Networks (GNNs) has been widely applied in various practical scenarios, such as predicting user interests and detecting communities in social…
cs.LG2024★ 1 cited
Enhancing the Resilience of Graph Neural Networks to Topological Perturbations in Sparse Graphs
Shuqi He, Jun Zhuang, Ding Wang +2
Graph neural networks (GNNs) have been extensively employed in node classification. Nevertheless, recent studies indicate that GNNs are vulnerable to topological perturbations, suc…