Centrality-Aware Fairness-Inducing In-Processing for Unsupervised Graph Representation Learning

Centrality-aware fairness-inducing framework (CAFIN) that leverages the structural information of graphs to tune the representations generated by existing unsupervised graph learning frameworks, reducing performance disparity across nodes.