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

Despite its success in the image domain, adversarial training did not (yet) stand out as an effective defense for Graph Neural Networks (GNNs) against graph structure perturbations. In the pursuit of fixing adversarial training (1) we show and overcome fundamental theoretical as well as practical li...

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Hauptverfasser:	Gosch, Lukas, Geisler, Simon, Sturm, Daniel, Charpentier, Bertrand, Zügner, Daniel, Günnemann, Stephan
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning
Online-Zugang:	Volltext bestellen
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