Causal AI (Causal discovery and inference) open-source library

Open-source 로 수행가능한 Causal discovery 와 inference library 들을 아래 정리 하였다. 

 

 

Package	Made by	Language			Site	Description	Area
		Python	R	MATLAB			Causal discovery	CAusal inference
cdml-neurips2020	CausaLens	O			https://github.com/causalens/cdml-neurips2020	A library for generating synthetic data to evaluate causal discovery techniques	O
Awesome-Causality-Algorithms	every				https://github.com/rguo12/awesome-causality-algorithms	A compilation of causal discovery & inference tools, packages, and other resources	O	O
gCastle	Huawei	O			https://github.com/huawei-noah/trustworthyAI/tree/master/gcastle	A causal structure learning toolchain	O
Tetrad, Causal-learn	CMU	O			https://sites.google.com/view/tetradcausal/home?authuser=0 https://causal-learn.readthedocs.io/en/latest/index.html	causal-learn is a Python translation and extension of the Tetrad java code. It offers the implementations of up-to-date causal discovery methods as well as simple and intuitive APIs.	O
Tigramite		O			https://jakobrunge.github.io/tigramite/	Tigramite is a causal time series analysis python package., e.g., PCMCI	O
Causal discovery toolbox	Personal researcher	O	O		https://fentechsolutions.github.io/CausalDiscoveryToolbox/html/index.html	A repository of causal discovery algorithms	O
Causalimpact	Google		O		https://google.github.io/CausalImpact/CausalImpact.html	An R package for causal inference using Bayesian sturctural time-series models		O
Causalib	IBM	O			https://causallib.readthedocs.io/en/latest/	A Python package for inferring causal effects from observational data.		O
EconML	Microsoft	O			https://github.com/microsoft/EconML	A python package for estimating heterogeneous treatment effects from observational data		O
DoWhy	Microsoft	O			https://github.com/py-why/dowhy	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.		O
CausalML	Uber	O			https://github.com/uber/causalml	Uplift modeling and causal inference with machine learning algorithms		O
CausalNex	QuantumBlack	O			https://github.com/quantumblacklabs/causalnex	A Python library that helps data scientists to infer causation rather than observing correlation. A toolkit for causal reasoning with Bayesian networks	O	O