Center-For-Complex-Systems-Science/causationentropy

Causal Discovery for Time Series

Fast causal discovery library

Python package for causal discovery based on LiNGAM.

Causal Discovery in Python. Learning causality from data.

Synergistic-Unique-Redundant Decomposition of causality from time series (Nature Communications, 2024)

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

Reconstructing shared causal drivers from noisy time series

Unified causal discovery engine

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