Review for NeurIPS paper: Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems

Summary and Contributions: Summary of contributions i) They set out to deploy probabilistic methods to determine the probability of dangerous events and determine the safety of a given, where dangerous events are simulated in a custom-built simulator, that combines exploration, exploitation, and optimization techniques to find failure modes and estimate the rate of occurrence. Summary They combine an adapted version of HMC, that they call warped HMC which, through sequential updates, utilizes normalizing flows and bridge sampling to extract samples corresponding to rare-events in a variety of different scenarios, generated via stochastic simulation. This paper shares some similar themes with NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport, but they also combine a series of other techniques. I had read this two-weeks ago and contributed to the discussions, so I apologise for the delay in the update. Just a few points and I believe the AC/ other reviewers have provided you with more feedback.