77 citations · 95 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 18 cited
CLEAR: Generative Counterfactual Explanations on Graphs
Jing Ma, Ruocheng Guo, Saumitra Mishra +2
Counterfactual explanations promote explainability in machine learning models by answering the question "how should an input instance be perturbed to obtain a desired predicted lab…
cs.LG2022★ 77 cited
Learning Fair Node Representations with Graph Counterfactual Fairness
Jing Ma, Ruocheng Guo, Mengting Wan +3
Fair machine learning aims to mitigate the biases of model predictions against certain subpopulations regarding sensitive attributes such as race and gender. Among the many existin…