Reviews: An Architecture for Deep, Hierarchical Generative Models

This is an interesting and fairly well executed paper. The main contribution of the paper is a hierarchical VAE architecture with deterministic connections in the inference and generative models, implementing incremental generation of observations. A similar approach has been pioneered by DRAW, but in DRAW-like models the layers of latent variables don't form a hierarchy (and are all at essentially the same level). Prob Ladder Nets have all the proposed features except for the deterministic connections in the generative model. Thus the main novel contribution here is the introduction of deterministic connections in a generative hierarchical model.