When Missingness Follows the Graph: Beyond Feature Propagation for Missing Features

Enrico Chialà, Francesco Ferrini, Antonio Longa +4

Graph Neural Networks (GNNs) commonly assume that node features are fully observed, despite missing features being pervasive in real-world applications. By leveraging the dependenc…