Review for NeurIPS paper: Instance-wise Feature Grouping

Additional Feedback: A few other minor comments: Other methods to compare? For gene expression experiments, I've found k-means clustering using R 2 on columns to be a surprisingly good baseline for global feature clustering (and it allows for getting groups that are anti-correlated). I've also seen methods for finding groups of variables with high multivariate mutual information / total correlation / redundancy. Those ideas could be interesting for comparison or for improving the representation redundancy part to allow for groups that are not always positively correlated. Attention-based learning methods are natural comparisons for things like Figure 1.