DowhyDoWhy 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.
CIKM18-LCVACode for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.
personalizedMethods for subgroup identification / personalized medicine / individualized treatment rules
causal-mlMust-read papers and resources related to causal inference and machine (deep) learning
causeinferMachine learning based causal inference/uplift in Python
CATENetsSklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
cfml toolsMy collection of causal inference algorithms built on top of accessible, simple, out-of-the-box ML methods, aimed at being explainable and useful in the business context