Review for NeurIPS paper: An implicit function learning approach for parametric modal regression

Thank you for your submission to NeurIPS. This was a borderline paper, with three of the reviewers being position (including one that went from negative to positive after the discussion period), and one remaining quite unconvinced about the paper. Having read through the paper myself, I agree with the overall assessment that there are both some strong and weak aspects to the paper. On the positive side, I found the proposed modeling approach here genuinely interesting. The idea of parameterizing a kind of energy function (I know the authors don't use this notion, but I do feel it is warranted ... this refers to the loss function that is ultimately minimized to find the modes) as the combination of the squared value of a the function f plus the penalty of the function derivative away from zero, this was rather interesting, and I believe likely to have applications well beyond just modal regression.