Review for NeurIPS paper: Certified Monotonic Neural Networks

Weaknesses: I'd probably be OK with the paper being published as is, but I feel strongly that the authors should clarify one key part of their algorithm. I would be happy to increase my rating if they could make this clarification. The objective function presented in eq. As the authors themselves say, if R(f) equals 0 in the true, exact, analytic sense of the expectation w.r.t the uniform distribution over X, then the network is indeed monotonic (aside from pathological measure-0 scenarios which we will leave aside). But if it is indeed truly monotonic, then you would not need to verify it with the MILP solver.