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I think PyMC is a much more mature solution. Also while PyMC is much more focused on sampling, Hakaru is more focused on Bayesian inference and trying to repres
by cf 10y ago
I think PyMC is a much more mature solution. Also while PyMC is much more focused on sampling, Hakaru is more focused on Bayesian inference and trying to represent stochastic models in a way such that any inference algorithm could be applied to it.
- eli_gottlieb 10y agoWhy does it look like Python all of a sudden? What happened to embedding probabilistic programming in Haskell?
- cf 10y agoThat's the concrete syntax for the language. It was chosen to be make the language more familiar to people who do machine learning in Python. The embedded design we had made it very challenging to develop new inference algorithms and to combine them. You can still find that version of hakaru at https://github.com/zaxtax/hakaru-old https://github.com/zaxtax/hakaru-old
- eli_gottlieb 10y agoAnd here I actually used the old Hakaru. What would be the problems in porting it to more recent Base libraries and GHC versions?
- cf 10y agoI expect no significant challenges in porting to more recent version of GHC. Some version bounds will need to be loosened and an Applicative instance added for the Measure monads. Also if you have any feature requests for that version I'd be curious what they were.