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.

uber / causalml

Uplift modeling and causal inference with machine learning algorithms

py-why / EconML

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 inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

matheusfacure / python-causality-handbook

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

pgmpy / pgmpy

Python Toolkit for Causal and Probabilistic Reasoning

rguo12 / awesome-causality-algorithms

An index of algorithms for learning causality with data

pedrohcgs / claude-code-my-workflow

A ready-to-fork Claude Code template for academics using LaTeX/Beamer + R. Multi-agent review, quality gates, adversarial QA, and replication protocols.

brycewang-stanford / Awesome-Journal-Skills

Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的 Claude Code/Codex 期刊技能包，从选题、识别策略到表格规范与审稿回复全流程，助你快速发论文。

pymc-labs / CausalPy

A Python package for causal inference in quasi-experimental settings

huawei-noah / trustworthyAI

Trustworthy AI related projects

carverauto / serviceradar

Open-Source Network Management, Monitoring, ITOM, and Security Analytics

DoubleML / doubleml-for-py

DoubleML - Double Machine Learning in Python

WillianFuks / tfcausalimpact

Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.

hanlulong / awesome-ai-for-economists

A curated list of AI tools, agent skills, libraries, and resources for economics research, teaching, and policy analysis. Maintained by the OpenEcon team.

JingxuanC / causal-memory

Causal memory layer for AI agents — MCP server that records decision→outcome relationships. Survives compaction.

sammargolis / DrugTargetWorld

DrugTargetWorld: a synthetic biobank for training and benchmarking AI scientists on end-to-end drug target discovery. Paper: arXiv:2610.09558