excellent paper. continues a curious discourse on unintuitive results in high d generative modeling tracing back to gutmann/hyvarinen (nce [1]), theis/van den oord ("bad samples w good likelihoods" [2]) and later nalisnick ("ood" data w higher likelihoods under model than train data [3])
add a skeleton here at some point
10 months ago