Reviews: Deep Poisson gamma dynamical systems

This paper presents Deep Poisson-Gamma Dynamical System (DPGDS) for modeling temporal multivariate count data. It is based on previously developed Gamma-Belief networks, extended to the dynamical scenarios by adding transitions of latent units in consecutive times. The paper is well written, and connections to previous papers are explained clearly. While the temporal structure is based on transition of latent units in a Markov manner, the authors' claim about better capturing long-range temporal changes should be justified more clearly. In line 30, "separated" should be replaced by "separately".