Review for NeurIPS paper: Hierarchical nucleation in deep neural networks

Weaknesses: The primary weaknesses are 1) lack of novelty, 2) concern as to whether the analysis method is advantageous and appropriate for understanding representation learning in CNNs, and 3) lack of convincing evidence that the four stated hypotheses are valid. Moreover, as argued in A.4, the method is also closely-related to CKA [3]. Thus the novelty comes primarily from the specific hypotheses raised by the authors and the methods used to test them. Note that this is not a substantial weakness, in that if the findings were interesting and the evidence was persuasive then acceptance would be merited. The need to pick a certain number of discrete neighbors seems disadvantageous.