Review for NeurIPS paper: Network Diffusions via Neural Mean-Field Dynamics

Weaknesses: i) Many design choices appear rather arbitrary in section 3.2, e.g. Since \epsilon is a black box, can we not get rid of the linear part from the beginning? Such an optimal control connection can be done for any parameter inference problem. From my understanding, the parameters are trained by minimizing loss function 18a with gradient descent. However if PMP is used, the solution quality heavily depends on the chosen solver method to the PMP problem, e.g. A discussion about such is missing.