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Causal Machine Learning Python Packages

Python packages with the GitHub topic causal-machine-learning. Sorted by relevance, with stars and monthly downloads.
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.

170K 8K 1K
MasemeneMatlakanaBenny
mini-causal

A Python package for measuring the impact of features

4K 0 0
SUwonglab
causalegm

CausalEGM: an encoding generative modeling approach to dimension reduction and covariate adjustment in causal inference with observational studies

1K 74 11
athammad
onlinecml

Online Causal Machine Learning in Python — one observation at a time

1K 2 0
JianqiaoMao
causalbootstrapping

CausalBootstrapping is an easy-access implementation and extention of causal bootstrapping (CB) technique for causal analysis. With certain input of observational data, causal graph and variable distributions, CB resamples the data by adjusting the variable distributions which follow intended causal effects.

662 2 0
ShaokunAn
sccausalvi

Perturbational analysis by causality-aware generative model for single-cell RNA-sequencing data

560 23 3
JianqiaoMao
mechanism-learn

Mechanism-learn is a simple method to deconfound observational data such that any appropriate machine learning model is forced to learn predictive relationships between effects and their causes, despite the potential presence of multiple unknown and unmeasured confounding. The library is compatible with most existing ML deployments.

394 3 1
DSsoli
scmopy

scmopy: Distribution-Agnostic Structural Causal Models Optimization in Python

356 0 0
rivkalipko
synthnn

A Python package implementing the synthetic nearest neighbors estimator for panel data causal inference.

237 0 1
adrianjav
causalflows

Causal Normalizing flows in PyTorch

142 31 1
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