CausalDiscoveryToolbox

The Causal Discovery Toolbox is a package for causal inference in graphs and in the pairwise settings for Python>=3.5. Tools for graph structure recovery and dependencies are included. The package is based on Numpy, Scikit-learn, Pytorch and R. It implements lots of algorithms for graph structure recovery (including algorithms from the bnlearn, pcalg packages), mainly based out of observational data. Check out the documentation here Please cite us if you use our software A tutorial is available here Install it using pip: (See more details on installation below) Docker images Docker images are available, including all the dependencies, and enabled functionalities: Branch master dev :----------------: :--------------------------------------------------------------------------------------------------------------------------------------: :------------------------------------------------------------------------------------------------------------------------------------: Python 3.6 - CPU Python 3.6 - GPU Installation The packages requires a python version >=3.5, as well as some libraries listed in requirements file.