sgao-academics/causalscale

Scalable open-source software to run, develop, and benchmark causal discovery algorithms

Causal Discovery in Python. Learning causality from data.

Python package for causal discovery based on LiNGAM.

Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

Repository for the Tetrad Project, www.phil.cmu.edu/tetrad.

A Python library that helps data scientists to infer causation rather than observing correlation.

Python Toolkit for Causal and Probabilistic Reasoning