Open access
F1801Q161 – Causal Networks
Repository for code, notebooks and other material for the course F1801Q161 – Causal Networks. The course belongs to the Master’s Degree Course in Computer Science at the Department of Informatics, Systems and Communication (DISCo), University of Milano-Bicocca (Milan, Italy).
Causal-hub
A package for Causal Data Science, written in Rust.
PyCTBN
A Continuous Time Bayesian Networks (CTBN) library, written in Python.
Reserved
For access, please contact madlab@unimib.it.
Awesome MADLab
This list contains resources that could be useful for achieving the goal of your work, including but not limited to theoretical aspects, programming libraries and general guidelines. The main goal is to reduce the overhead of selecting what is really worth to take into consideration. The resources are licensed under GPLv3 and include: Causal Theory, Graph Theory, a Guide to LaTeX, a Guide To Markdown, a Guide To Repository, Probabilistic Graphical Models, Programming in Rust, Programming in C++, Time Series, and Reinforcement Learning.
CANET
“CAusal NETworks”. Instructions about internal Cloud Computing Services.
ZERG
“Zero-Effort Resource Governor”
Starter pack
A list of starter packs for beginners in causal discovery, causal inference, scientific programming and scientific writing.
Journal clubs
Recordings and slides of MADLab internal Journal Clubs.
Past presentations
Slides of MADLab past presentations.
Slides template
Shared Overleaf project. A common slide template to be used in presentations.