Review for NeurIPS paper: GradAug: A New Regularization Method for Deep Neural Networks

Summary and Contributions: After rebuttal and discussion with other reviewers I have updated my score. However, I do point out several concerns of mine which the authors could consider further validation for: It's good that the authors performed the time/memory comparison in the rebuttal as that was a significant concern of mine. My concerns mostly revolve around what other techniques should we compare this against? Given that this algorithm takes 3-4x the time with comparison to the baseline, I could for example: 1: Train a much larger network and then use compression techniques to slim it to the same size. Mixup which is still 70% faster.