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@r_mohan_twitter , we wrote a little intro about it here in case that you are interested:
https://www.tweag.io/posts/2019-09-20-monad-bayes-1.html
https://www.tweag.io/posts/2019-11-08-monad-bayes-2.html
otherwise these papers give a good overview of what it's doing:
https://dl.acm.org/citation.cfm?id=3236778
http://mlg.eng.cam.ac.uk/pub/pdf/SciGhaGor15.pdf
on probabilistic programming - i'm curious what people w/ more of a PL / FP background think of "Functional Tensors for Probabilistic Programming" https://arxiv.org/pdf/1910.10775.pdf
(wouldn't recommend this for day-to-day practical modeling yet, this is still pretty research-y for now)
Hi, it's been a while (studies and stuff). I'm still motivated tho! I am currently looking at http://www.datahaskell.org/, so I have a few questions:
And more general questions : is there a general roadmap, a "place" where people here would like to take Data Haskell to ?
Sorry if those topics have been discussed many times already, but I believe that as time goes by it can be clearer and change
Hi!
I'm proposing new lens-based API for statistics: bos/statistics#162 What to you think about it?
TL/DR example of use: meanOf (each . filtered (>0) . to log)
will compute mean of logarithm of every positive number.