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junpenglao/[WIP] Bayesian GMM.ipynb

Last active October 18, 2019 11:11
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Documents/Github/Human_Learning/Miscellaneous/[WIP] Bayesian GMM.ipynb
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junpenglao commented Apr 27, 2017 •
edited

Currently, this is not working too well yet. To improve from here, it might be necessary to follow Kamary, Lee & Robert (2017), or the more classical Expectation Propagation. It doesn't hurt also to revisited the relevant chapters in Christopher Bishop's Pattern Recognition and Machine Learning.
Better sampling/fitting could be archived by utilising the composing inferences in PyMC3 or Edward (by implementing the special models as described in the papers mentioned above).

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junpenglao commented Mar 31, 2018 •
edited

It should now works a bit more naturally after pymc-devs/pymc#2904 - there is no need to write down the custom logp any more.

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