An index of algorithms for learning causality with data

Eliot: the logging system that tells you *why* it happened

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

YLearn, a pun of "learn why", is a python package for causal inference

Python package for causal discovery based on LiNGAM.

A resource list for causality in statistics, data science and physics

A Python package for causal inference using Synthetic Controls

Hyper-geometric computational causality library for Rust

💊 Comparing causality methods in a fair and just way.

Python package for Granger causality test with nonlinear forecasting methods.

Causing: CAUsal INterpretation using Graphs

가짜연구소 <인과추론과 실무> 프로젝트

A project for exploring differentially active signaling paths related to proteomics datasets

Tigramite is a time series analysis python module for linear and information-theoretic causal inference. Version 3.0 described in http://arxiv.org/abs/1702.07007 is available at https://github.com/jakobrunge/tigramite!

Causal Relation Extraction and Identification using Conditional Random Fields

金融文本中的原因事件

Mendelian Randomization with Biomarker Associations for Causality with Outcomes

Causal Inference Using Quasi-Experimental Methods

Identifying reasons for human actions in lifestyle vlogs.

Source code for the paper "Causal Modeling of Twitter Activity during COVID-19". Computation, 2020.