Review for NeurIPS paper: On the equivalence of molecular graph convolution and molecular wave function with poor basis set

The paper compares different deep learning approaches to modeling the quantum mechanic properties of molecules, and presents a model that incorporates multiple ideas from physics. Some reviewers appreciated multiple aspects of the paper, including: - A novel approach, offering an interesting contrast to GCN approaches - Compelling numerical results in comparison to a standard GCN approach (even if this not extrapolation, it still shows the benefit of the proposed approach over GCNs). The proposed approach does not even use spherical harmonics in the LCAO representation. The fact that this "still works well" is bothering as it necessarily leads to a bad approximation of the molecular orbitals, to a point where the added benefit of chemically informed modeling might be almost gone. Overall, the impression is positive and our recommendation is to accept the paper.