2a084e55c87b1ebcdaad1f62fdbbac8e-AuthorFeedback.pdf

We thank the reviewer for these references, they are very relevant6 and will be added to the manuscript. Rev #1 also suggests to add experiments in order to compare UMNNs with7 thismethod. Instead,weargue18 that other neural architectures for density estimation do so in a way that "leads to a cap on the expressiveness" of19 thetransformations inthenon-asymptotic case(finitenumber ofneurons). Then, this pass must be evaluated backward again in order to38 obtainthelog-likelihood derivative. BothNAFandB-NAFprovideamethod tomakethiscomputation numerically39 stable, however both fail at not increasing the size of the computation graph of the log-likelihood derivative, hence40 leadingtoamemoryoverhead.