Reviews: Non-Adversarial Mapping with VAEs

The manuscript considers the problem of unsupervised mapping across domains by use of variational auto-encoders (VAE) instead of the current adversarial training (GAN) approach. The approach extends a recently proposed non-adversarial mapping (NAM) framework extracting a mapping from a pretrained generative model to a target domain with the present addition of a probabilistic encoder which maps the target image y to the latent domain z_y, i.e. based on the optimization given in equation 2 of the manuscript. Quality: The issue of mapping between domains is interesting and the framework presented seems new and useful. It however also appears to be a straightforward extension to NAM but providing computational merits and improved performance in terms of the quality of mapping which could warrant publication. The experimentation is somewhat limited and the presentation of the paper could be improved by proofreading the manuscript.