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Projects in Awesome Lists tagged with causality

A curated list of projects in awesome lists tagged with causality .

https://github.com/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.

bayesian-networks causal-inference causal-machine-learning causal-models causality data-science do-calculus graphical-models machine-learning python3 treatment-effects

Last synced: 01 Oct 2024

https://github.com/microsoft/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.

bayesian-networks causal-inference causal-machine-learning causal-models causality data-science do-calculus graphical-models machine-learning python3 treatment-effects

Last synced: 28 Aug 2024

https://github.com/py-why/EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

causal-inference causality econometrics economics machine-learning treatment-effects

Last synced: 31 Jul 2024

https://github.com/microsoft/EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

causal-inference causality econometrics economics machine-learning treatment-effects

Last synced: 31 Jul 2024

https://github.com/py-why/econml

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

causal-inference causality econometrics economics machine-learning treatment-effects

Last synced: 30 Sep 2024

https://matheusfacure.github.io/python-causality-handbook/

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

causal-inference causality data-science econometrics harmless-econometrics impact-estimation python

Last synced: 01 Aug 2024

https://github.com/matheusfacure/python-causality-handbook

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

causal-inference causality data-science econometrics harmless-econometrics impact-estimation python

Last synced: 30 Sep 2024

https://github.com/jrfiedler/causal_inference_python_code

Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins

causal-inference causality data-science python

Last synced: 30 Sep 2024

https://github.com/yfzhang114/generalization-causality

关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记

adaptation causality deep-learning generative-model machine-learning optimization robustness

Last synced: 30 Sep 2024

https://github.com/py-why/causal-learn

Causal Discovery in Python. It also includes (conditional) independence tests and score functions.

causal causal-discovery causal-inference causal-representation-learning causality confounder graph hidden-causal independence-tests python statistics structure tetrad time-series

Last synced: 01 Oct 2024

https://github.com/fentechsolutions/causaldiscoverytoolbox

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

algorithm causal-discovery causal-inference causal-models causality graph graph-structure-recovery inference machine-learning python toolbox

Last synced: 30 Sep 2024

https://github.com/yfzhang114/Generalization-Causality

关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记

adaptation causality deep-learning generative-model machine-learning optimization robustness

Last synced: 03 Aug 2024

https://github.com/FenTechSolutions/CausalDiscoveryToolbox

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

algorithm causal-discovery causal-inference causal-models causality graph graph-structure-recovery inference machine-learning python toolbox

Last synced: 31 Jul 2024

https://github.com/causaltext/causal-text-papers

Curated research at the intersection of causal inference and natural language processing.

causality natural-language-processing

Last synced: 31 Jul 2024

https://github.com/altdeep/causalML

The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML

causality machine-learning

Last synced: 02 Aug 2024

https://github.com/BiomedSciAI/causallib

A Python package for modular causal inference analysis and model evaluations

causal causal-inference causal-models causality data-science machine-learning ml

Last synced: 31 Jul 2024

https://github.com/fulifeng/Causal_Reading_Group

We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.

causal-inference causality deep-learning machine-learning recommender-system

Last synced: 31 Jul 2024

https://github.com/M-Nauta/TCDF

Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series

causality cnn forecasting machine-learning neural-networks prediction python pytorch timeseries

Last synced: 03 Aug 2024

https://github.com/wmayner/pyphi

A toolbox for integrated information theory.

causality causation information integrated-information modeling neuroscience

Last synced: 02 Aug 2024

https://github.com/Minyus/causallift

CausalLift: Python package for causality-based Uplift Modeling in real-world business

causal-impact causal-inference causality counterfactual econometrics propensity-score propensity-scores uplift uplift-modeling

Last synced: 31 Jul 2024

https://github.com/salesforce/causalai

Salesforce CausalAI Library: A Fast and Scalable framework for Causal Analysis of Time Series and Tabular Data

causality

Last synced: 02 Aug 2024

https://github.com/microsoft/robustdg

Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.

artificial-intelligence causality domain-generalization machine-learning privacy-preserving-machine-learning

Last synced: 02 Aug 2024

https://github.com/uhlerlab/causaldag

Python package for the creation, manipulation, and learning of Causal DAGs

causal-dags causal-inference causal-models causality inference

Last synced: 31 Jul 2024

https://github.com/maxwshen/iap-cidl

Causal Inference & Deep Learning, MIT IAP 2018

causal-models causality inference notes

Last synced: 05 Aug 2024

https://github.com/jrfiedler/causal_inference_julia_code

Julia code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins

causal-inference causality data-science julia julialang

Last synced: 29 Sep 2024

https://gitlab.com/agrumery/aGrUM

aGrUM is a C++ library designed for easily building applications using graphical models such as Bayesian networks, influence diagrams, decision trees, GAI networks or Markov decision processes.

artificial-intelligence bayesian-network causal-inference causal-models causality cpp20 credal-network explainable-ai influence-diagram machine-learning-algorithms markov-network parallel-algorithm probabilistic-classifiers probabilistic-graphical-models probabilistic-models python python3 statistical-learning structural-learning

Last synced: 30 Sep 2024

https://github.com/kuffmode/msa

Hopefully, a compact and general-purpose Python package for Multiperturbation Shapley value Analysis (MSA).

artificial-neural-networks brainmapping causality gametheory python shapley-value

Last synced: 02 Aug 2024

https://github.com/IyarLin/simMixedDAG

The simMixedDAG package enables simulation of "real life" datasets from DAGs

causal-inference causality dag r r-package simulation

Last synced: 30 Jul 2024