Comments (5)
murphyk
commented on June 19, 2024
Set optimizer=None in https://github.com/probml/ssm-jax/blob/main/ssm_jax/hmm/models/bernoulli_hmm.py#L68
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murphyk
commented on June 19, 2024
Here are the details from my book 1. Note that the add one smoothng prior corresponds to Beta(2,2) which is much stronger than your current Beta(1.1, 1.1). This might explain your numerical problems.
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slinderman
commented on June 19, 2024
Replace beta.mode in https://github.com/probml/ssm-jax/blob/main/ssm_jax/hmm/models/bernoulli_hmm.py#L99 with pseudo counts
I actually like the Beta(count1, count0).mode() formulation! I think it shows off the general form of the M-steps.
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karalleyna
commented on June 19, 2024
I think we've all settled on using the Beta(count1, count0).mode(). Could I close this issue?
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slinderman
commented on June 19, 2024
Yup!
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