In this paper, we propose an algorithm for estimating the parameters of a time-homogeneous hidden Markov model (HMM) from aggregate observations. This problem arises when only population level counts number individuals at each time step are available, and one seeks to learn individual HMM these Our is built upon classical expectation–maximization recently proposed inference (Sinkhorn belief pro...