HMMs in PyTorch

This repo contains code for Hidden Markov Models (HMMs) in PyTorch, including the forward algorithm, the Viterbi algorithm, and sampling. Training is implemented by backpropagating the negative log-likelihood from the forward algorithm, instead of using the EM algorithm.

You can read a notebook which covers the theory of HMMs and implements the model in PyTorch piece-by-piece here.