Penrose meets Pearl, (c) 2021
Our honour to be mentioned by Judea Pearl on twitter.
Aspiration to learn everything from data alone has
kept the ML community away from science.
Judea Pearl
A resource list, code snippets or small scale software solutions for causal analysis in different areas. The name is inspired from the movie looper, which has a premise of time-like loops, probably the most complex causal subject from physics point of view.
The main entry is a markdown file as follows, any looper specific internal examples are lined there too :
- A resource list for causality in statistics, data science and physics Other fields of course such as econometrics, epidemiology and many more.
Looper Nuggets mimick a glossary of terms and concepts in causal inference, though they are entry to understanding concepts in pedagogical manner. See the list of them here.
This repository and all contributions are licensed under
Please attribute this work as follows
@misc{suezen2018a,
author = {Mehmet S{\"u}zen et. al.},
title = {A resource list for causality in statistics, data science and physics},
year = {2018},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/msuzen/looper}},
}
If you are embedding specific release, use the version link, for example for https://github.com/msuzen/looper/tree/v0.1.2
in howpublished tag.
Please send a pull request or create an issue for suggestions or codes. See Basic how to contribute guide