u/jaredtobinin r/haskell • Recommends
On “Smart classification using Bayesian monads in Haskell”
Check out Ścibior et al from ICFP 2015. The associated talk is also available here.
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#probabilisticprogramming#monads#bayesianinference
2 05 Practical Probabilistic Programming with Monads
ICFP Video
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- Recommended by 2 people: 2 in engineering communities.
Advanced. Deep dive for people who know the field.
1.1K views11 years ago2 recommendations
Programming languagesComputer scienceHaskellFunctional programming
This ICFP 2015 talk presents a monadic approach to practical probabilistic programming in Haskell.
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2 people recommend thisWhat people say. Recommended as the accompanying talk to the paper on Bayesian monads in Haskell.
u/edwardkmettin r/haskell • Recommends
On “Monadic/Applicative representation of continuous probability distributions?”
It is a good paper.
link to this video is the talk that went it.
The requirement that all Conditionals wind up on the left of a monadic bind rather than the right is somewhat galling though. (section 4, paragraph 2)
I'd rather have a separate type for specifying conditionals, because that fails the "is it a monad?" test.
Also, extending this monad with an explicit constructor for handling `(<*>)` is quite important in practice for sampling from it, if you use MCMC-based techniques, because you can always do Gibbs sampling style moves for each side of the `(<*>)` independently. This makes a _massive_ difference in the performance of large models, as for independent draws we can Gibbs sample without…