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W Robert Long
@WRobertLong
@r_mohan_twitter take a look at the monad-bayes library
r_mohan
@r_mohan_twitter
Yves Parès
@YPares
@r_mohan_twitter Yep that's the one
MMesch
@MMesch

@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

r_mohan
@r_mohan_twitter
Thanks. Specialized gitter channels are better than general google search :-)
MMesch
@MMesch
:+1: don't hesitate to ask questions about it
Austin Huang
@austinvhuang

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)

Marco Zocca
@ocramz
@austinvhuang I actually read it some days ago. I very much agree with treating quantities as terms of some abstract syntax rather than constants. This is similar to how "push arrays" are implemented, and in fact deferring computation as long as possible to perfom symbolic simplifications is a very good idea
btw are tou going to PROBPROG in April?
*you
Austin Huang
@austinvhuang
@ocramz I’m not sure yet, wasn’t planning too though. we should definitely meet up if you attend!
Doug Burke
@DougBurke
I'm not yet sure if I'll go to PROBPROG, but as I live just down the road I may be interested in a meetup outside the conference.
Samuel Schlesinger
@SamuelSchlesinger
Hey all, its been years since I've been in here. Anyone want a hand with anything?
Tony Day
@tonyday567
hey sam, check out numhask-array for where I got to with higher kinded numbers.
feedback would be nice
Guillaume Desforges
@GuillaumeDesforges

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:

  • who maintains it ?
  • is it still updated ?

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

Marco Zocca
@ocramz
@GuillaumeDesforges I maintained the homepage and the docs for almost three years
as for the roadmap .. everyone has different ideas on how that should look like.
Samuel Schlesinger
@SamuelSchlesinger
looking now @tonyday567
Gregory Nwosu
@gregnwosu
I think I've just found my spiritual home
Marco Zocca
@ocramz
hi @gregnwosu !
Gregory Nwosu
@gregnwosu
:wave:
what advantages does monad-bayes have over more traditional probablistic programming library such as say pymc3
MMesch
@MMesch
I am just an occasional user but I find Monad Bayes quite comfortable to use. Here are three things that come to my mind at the moment, compared to pymc3:
  • it integrates with standard Haskell syntax, you can sample from standard datatypes, functions and use do notation to combine those operations. With pymc3 you have to deal with theano tensors etc ...
  • Haskell syntax make the code really concise. It really looks almost like what you would write with standard math notation in an article.
  • Monad Bayes provides an abstraction on top of different inference representations and you can build new ones out of these basic building blocks. For example, mcmc requires a different representation of a prob distribution (in terms of accumulated log likelihood of the samples) than sequential monte carlo, or inverse sampling (cumulative distribution function) or a particle filter. Checkout table 1 in https://pdfs.semanticscholar.org/76ad/0090bf4a076391fe2cc6d6029f79ebc66308.pdf . AFAIK in pymc3 you basically chose a configurable out-of-the box sampler and than run it.
MMesch
@MMesch
you can sample from standard datatypes, functions
Gregory Nwosu
@gregnwosu
oh cool, so in theory you can make any program probablistic?
MMesch
@MMesch
this might read misleading - it is actually quite easy to sample from whatever custom datatype with itas well. It thus integrates quite naturally with other libraries.
@gregnwosu yes exactly - afterwards you might have to adapt your sampler a bit. E.g. with hamilton monte carlo, you cannot easily sample from discrete distributions (atm).
Alexey Kuleshevich
@lehins
This seems like a crowd that could potentially benefit from information in this blog post: https://www.reddit.com/r/haskell/comments/edr9n4/random_benchmarks/
MMesch
@MMesch
nice, thanks for writing this!
Alexey Kuleshevich
@lehins
:+1:
Gregory Nwosu
@gregnwosu_gitlab
happy new year all!
is anyone else experiencing long compilation times with Frames?
Tim Pierson
@o1lo01ol1o
@gregnwosu_gitlab Yes, some of the higher-kinded generics can get quite long depending on what you're trying to do.
Marco Zocca
@ocramz
happy new year! :tada:
Aleksey Khudyakov
@Shimuuar

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.

Marco Zocca
@ocramz
@Shimuuar I like it a lot; by coincidence I'm also tinkering quite a bit with lenses in the past few days, in particular the microlens set of libraries
Aleksey Khudyakov
@Shimuuar
I suspect that here lens will be necessary to be useful. But I didn't check
Tim Pierson
@o1lo01ol1o
have you considered optics?
Aleksey Khudyakov
@Shimuuar
Not really. lens is sort of standard now so I just went with it.
Tim Pierson
@o1lo01ol1o
The errors and documentation on optics are quite good, though. I think you sacrifice some cases of compositionally, but, in terms of people new to lens on a project that uses it (those poor, dreaded newbs), it presents a strong case
Marco Zocca
@ocramz
yeah the thing is that lens and friends are perfectly integrated with base concepts : (.), traverse, etc. My personal journey with this stuff has been extremely slow and gradual; I only found a need for it while refactoring my vega bindings, which have very nested datatypes
Marco Zocca
@ocramz
(I'm saying this because others might be in a similar position: not needing a full-blown optics library but just some convenience functionality)
Aleksey Khudyakov
@Shimuuar
Yes error messages are better. But libraires are more likely to provide van-Laarhoven's lens and newbies will have to learn lens anyway. There's no escape from it
Tim Pierson
@o1lo01ol1o

libraires are more likely to provide van-Laarhoven's lens and newbies will have to learn lens anyway. There's no escape from it

be the change u want to see in 2020. :sunglasses:

Marco Zocca
@ocramz
@Shimuuar do you plan to introduce Prism and Iso in statistics as well?
Aleksey Khudyakov
@Shimuuar
I don't know yet. Currently type signatures looks like: meanOf :: Getting (Endo (Endo MeanKBN)) s Double -> s -> Double and yes one could plug prisms there
Aleksey Khudyakov
@Shimuuar
@o1lo01ol1o Having to wrangle both libraries seems much more likely outcome
Marco Zocca
@ocramz
@Shimuuar please also consider the downstream cost of having to compile lens and/or optics while building criterion etc.