Sampling functions for the MuE/missing data discrete HMM.

[EWeinstein]

An implementation of sampling and estimation functions for the missing data discrete HMM, used in MuE models, including:

1. Smoothing latent state estimator.
2. Viterbi MAP estimator of latent states.
3. Sampling latent states conditional on observations (forward filtering backward sampling).
4. Sampling observations conditional on latent states.

This commit also includes updates to maintain compatibility with the latest torch version (in particular, the behavior of randperm changed), and updates to the MuE paper reference.

[fritzo]

Hi @EWeinstein you may need to make format now that we're using black. Let me know if you need anything. Happy to do a quick little 1.7.1 release after this merges if this is holding up anyone in your lab.

[fritzo]

Thanks for your patience @EWeinstein. This review involves some tricky code. Would you be up to walk me through some of the code over zoom, and generally catch up?

[fritzo]

Thanks for walking me through the code today!