Reviews: Neural Relational Inference with Fast Modular Meta-learning

This paper is quite unbalanced in two ways. Firstly the balance of space devoted to discussing background vs contributions is skewed too heavily towards discussing prior work, with too little focus on explaining the contributions of this work. Secondly, the coverage of the literature is heavily focused on graph networks and meta learning, but neglects to cover prior work on (non-graph based) modular networks and on learned proposal distributions. Towards the first imbalance, the section on lines 201-235 is by far the most important content in the paper, but is positioned almost as an afterthought to the extensive exposition of Alet et al. (2018). The paper would be much stronger if other sections were shortened and the descriptions in this region were substantially expanded (eg.