Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions

no code implementations • NeurIPS 2023 • Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann

Including these contributions, we demonstrate that adversarial training is a state-of-the-art defense against adversarial structure perturbations.

Graph Learning

Revisiting Robustness in Graph Machine Learning

no code implementations • 1 May 2023 • Lukas Gosch, Daniel Sturm, Simon Geisler, Stephan Günnemann

Many works show that node-level predictions of Graph Neural Networks (GNNs) are unrobust to small, often termed adversarial, changes to the graph structure.

Adversarial Robustness