vdorie/bartCause

Causal Inference in Python

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.

A Python package for causal inference in quasi-experimental settings

Extended two-way fixed effects

CausalPFN: Amortized Causal Effect Estimation via In-Context Learning

Augmented Synthetic Control Method

R package mediation

Structural causal models with Bayesian estimation and interventional simulation via a concise DSL.