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.

Next generation of automated data exploratory analysis and visualization platform.

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal …

An index of algorithms for learning causality with data

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins

关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记

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

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

Causal Discovery in Python. It also includes (conditional) independence tests and score functions.

Curated research at the intersection of causal inference and natural language processing.

The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML

❗ uplift modeling in scikit-learn style in python 🐍

A Python package for modular causal inference analysis and model evaluations

We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.

Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series

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

Causal Inference for The Brave and True 책의 한국어 번역 자료입니다.

A toolbox for integrated information theory.