I'm quite new to LW, and find myself wondering whether Hidden Markov models (HMM) are underappreciated as a formal reasoning tool in the rationalist community, especially compared to Bayesian networks?

Perhaps it's because HMM seem to be more difficult to grasp?

Or it's because formally HMM are just a special case of Bayesian networks (i.e. dynamic Bayes nets)? Still, HMM are widely used in science on their own.

For comparison, Google search "bayes OR bayesian network OR net" site:lesswrong.com gives 1,090 results.

Google search hidden markov model site:lesswrong.com gives 91 results.

Out of curiosity, did you happen to read Kurzweil's recent book on HHMMs?

I think the safest answer is that a HMM is just a specific way of mathematically writing down an updating Bayesian network.

1ChristianKl6yHidden Markov models are a reasoning model to solve a specific problem. If you don't face that specific problem they are no use. Most of the problems we discuss aren't modeled well with HMMs.
0Qiaochu_Yuan6yThere's a proliferation of terminology in this area; I think a lot of these are in some sense equivalent and/or special cases of each other. I guess "Bayesian network" is more consistent with the other Bayes-based vocabulary around here.

Open thread, January 25- February 1

by NancyLebovitz 1 min read25th Jan 2014318 comments

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