Could anyone point me in the direction of resources to learn more about probabilistic programming?
(e.g.: text books, practical applications, introductory articles)
(e.g.: text books, practical applications, introductory articles)
The Design and Implementation of Probabilistic Programming Languages (https://dippl.org) by Noah D. Goodman https://cocolab.stanford.edu/ndg.html
Stanford CS 228: Probabilistic Graphical Models https://cs228.stanford.edu and book by Daphne Koller http://openclassroom.stanford.edu/MainFolder/CoursePage.php?...
ProbTorch: Library for deep generative models that extends PyTorch https://github.com/probtorch/probtorch
Anglican: Probabilistic programming language integrated with Clojure and ClojureScript https://probprog.github.io/anglican/index.html
Discussion: https://news.ycombinator.com/item?id=18585465
Ranked programming is like probabilistic programming but you don't use probabilities. Instead, you state how your program normally behaves and how it may exceptionally behave. Conceptually it's very similar to probabilistic programming, but the underlying uncertainty formalism is replaced with ranking theory.
You can find an implementation of this idea (based on Scheme/Racket) here:
https://github.com/tjitze/ranked-programming
For more detailed information check the paper linked to on that page.
- Probabilistic Models of Cognition https://probmods.org/ by Noah D. Goodman, Joshua B. Tenenbaum & contributors
- An Introduction to Probabilistic Programming https://arxiv.org/abs/1809.10756 By Jan-Willem van de Meent, Brooks Paige, Hongseok Yang, Frank Wood