Review for NeurIPS paper: Efficient Learning of Generative Models via Finite-Difference Score Matching

Additional Feedback: Concerning the title (and I know this is maybe pedantic), 'Efficient' is an entirely relative term, and means little in the absolute context of a paper title. An alternative title'Generative Modeling via Finite-Difference Score Matching' is both clearer and more concise. What does it mean to perform learning in a generative modeling'efficiently'? The proposed methods achieve efficiency with respect to the previous implementations of SSM and DSM, and are strictly in that sense efficient. Including'efficient' in the title only serves to obfuscate the actual contribution of the paper, which isn't about efficient learning of generative models compared to all other generative model learning approaches, but efficient score matching by finite difference methods specifically.