Reviews: Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers

Overall, I believe the paper makes a meaningful empirical contribution to scalable training methods of robust classifiers. By finding adversarial examples for smoothed classifiers and modifying the training procedure, the authors significantly improve the accuracy of smoothed classifiers. Smoothed classifiers are of interest since they are scalable and come with a certificate of robustness. The paper is clearly written. However, the contribution seems incremental.