Just in case people here are interested, here is a video of a seminar talk I was invited to give to the Psychology department at the University of Leicester, UK. I go through some examples using Julia and Turing. As well as a simple linear regression example, I give examples of two Bayesian cognitive models:
- Delay discounting in a decision making experiment
- A Bayesian optimal observer model of a visual attention experiment
Video: A beginners guide to Bayesian Cognitive Modelling - YouTube [45 mins]
GitHub repo: GitHub - drbenvincent/2021-Leicester-seminar: Code for a seminar talk at University of Leicester, UK
PS: If you like this kind of thing, then you can retweet this https://twitter.com/inferencelab/status/1364962838196977667?s=21
Hi @drbenvincent, very cool talk!
One question: what is
@.? I looked in turing and distributions for macros but didn’t see anything matching. Thanks!
Its a convenience macro that broadcasts every operation to its right, i.e.
@. a = b + c * d becomes
a .= b .+ c .* d.
@__dot__ which is searchable in the documentation.
The search for @. or “@.” was not helpful or productive.
@carstenbauer @devel-chm thanks both! I guessed it was related to the normal
. usage but it’s very handy to know for sure and also where to find it!
So, it seems like
__dot__ is handled as an exceptional case by the parser here and this is unique case (I cannot find any other dunders in there).