thank you for the great examples on how to perform inference in a hidden markov model with pyro (in pyro/examples/hmm.py)
I wonder what the best practice is to perform the following task:
Run the HMM on some input data for t steps.
- Infer the probabilities for the hidden states and observations for t+1
- Infer the probabilities for some of the observations conditioned on a given subset of observations.
Thank you and kind regards,