Review for NeurIPS paper: Unsupervised Data Augmentation for Consistency Training

Additional Feedback: The main comment I have regarding the paper is that the authors do not provide adequate justification as to why the advanced data augmentation work compared to the simple ones and when to apply them. This same intuition can be applied for other semi-supervised methods like nearest neighbor and label propagation. These methods will assign the same labels to unlabeled data examples within its component in a graph. This is intuitive but does not explain why the noise from the advanced data augmentation methods are better for semi-supervised learning or provide guarantees for when they work. I acknowledge that I read the rebuttal and thank the authors for providing explanations to the questions and concerns I had.