Reviews: Composing graphical models with neural networks for structured representations and fast inference

Combining PGMs and deep learning/neural networks is a very active and promising area of research. This is an interesting paper, with it's main contribution to the existing literature being that it presents a model that can account for discrete latent variables. This new capability suggests that it could be used in a variety of interesting applications, including the type of behavior representation modeling shown in one of the experiments. Overall, the organization of the paper is excellent, and the writing is clear. The technical part is however quite dense.