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Top 7 treatment-effects open source projects

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.
CIKM18-LCVA
Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.
CATENets
Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
cfml tools
My 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
1-7 of 7 treatment-effects projects