Graph Neural Networks have fastly grown popularity in recent years due to their ability to learn non-pixel data representations. However, their robustness to noisy data or other kinds of perturbations is still not adequately explored. In this project, we will investigate various adversarial attacks and hopefully proposed methods to increase network robustness for their elimination.
Related work: https://arxiv.org/pdf/1805.07984.pdf,
https://arxiv.org/abs/1809.01093,
https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7974879