Certifying Robustness of Graph Convolutional Networks for Node Perturbation with Polyhedra Abstract Interpretation

Boqi Chen, Kristóf Marussy, Oszkár Semeráth +2

Graph convolutional neural networks (GCNs) are powerful tools for learning graph-based knowledge representations from training data. However, they are vulnerable to small perturbat…