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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.

✭ 3,480

python machine-learning data-science graphical-models causality bayesian-networks causal-inference treatment-effects causal-models do-calculus causal-machine-learning

Causing

Causing: CAUsal INterpretation using Graphs

✭ 47

python Makefile graphs automatic-differentiation pytorch neural-networks graph-theory derivatives mediation-analysis dag causality-analysis latent-variables structural-equation-modeling structural-analysis effects-modeling causal-networks simultaneous-equation gnn do-calculus

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