causal-machine-learning

There are 25 repositories under causal-machine-learning topic.

  • 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.

    Language:Python6.8k137449917

  • msuzen/looper

    A resource list for causality in statistics, data science and physics

    242123631

  • JackHCC/Awesome-Uplift-Model

    🛠 How to Apply Causal ML to Real Scene Modeling？How to learn Causal ML？【✔从Causal ML到实际场景的Uplift建模】

    Language:Jupyter Notebook872012

  • rguo12/network-deconfounder-wsdm20

    Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.

    Language:Python67308

  • tlverse/tlverse-handbook

    🎯 :closed_book: Targeted Learning in R: A Causal Data Science Handbook

    Language:TeX5552317

  • SUwonglab/CausalEGM

    A General Causal Inference Framework by Encoding Generative Modeling

    Language:Python52308

  • dscolby/CausalELM.jl

    Taking causal inference to the extreme!

    Language:Julia181430

  • Scriddie/Varsortability

    Implementations of var-sortability, sortnregress, and chain-orientation as presented in the article "Beware of the Simulated DAG": https://arxiv.org/abs/2102.13647.

    Language:Python14402

  • nhejazi/medoutcon

    :package: R/medoutcon: Efficient Causal Mediation Analysis with Natural and Interventional Direct/Indirect Effects

    Language:R138285

  • ssbin0914/Causal-Mode-Multiplexer

    Official PyTorch Implementation for "Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian Detection" in CVPR 2024

    Language:Python12

  • lmz123321/which_invariance

    Official implementation for ICML23 paper: Which Invariance Should We Transfer? A Causal Minimax Learning Approach

    Language:Jupyter Notebook11202

  • UzmaHasan/KCRL

    Causal Discovery with Prior Knowledge

    Language:Python10200

  • JanTeichertKluge/DMLSim

    This library provides packages on DoubleML / Causal Machine Learning and Neural Networks in Python for Simulation and Case Studies.

    Language:Python6200

  • clarenceluo78/deep-learning-lookup

    Collection and implementation of a variety of machine learning code examples (notebooks and Python scripts) and projects.

    Language:Jupyter Notebook41

  • quillan86/impactflow

    ImpactFlow is a Python Library for decision modeling based on causal decision models - in which levers and external factors of decisions feed into outcomes.

    Language:Python2100

  • umbertocollodel/Machine_Learning_in_Economics

    Treatment evaluation in presence of large number of covariates or treatment heterogeneity through Machine Learning methods

    Language:R2122

  • Scriddie/VarsortabilityExperimentSuite

    Basic experimental set-up for the comparison of causal structure learning algorithms as shown in "Beware of the Simulated DAG".

    Language:Python1101

  • tobiasuruali/Causal_MachineLearning

    Causal Machine Learning project analyzing and evaluating different Double ML models for estimating treatment effects in observational data.

    Language:HTML10

  • Tommylee1013/EconomicCycle

    2023학년도 2학기 경기변동론 프로젝트 페이지

    Language:Python10

  • KevinArthurTittel/CausalML

    Robust Smooth Heterogeneous Treatment Effect Estimation using Causal Machine Learning

    Language:R0100

  • noname31157/KCRL

    This is the public repository of the code implementation for KCRL.

    Language:Python0100

  • syedmfuad/causal_ml

    Comparing effectiveness of the most common causal machine learning methods across various treatment effect, model complexities, data dimensions and sample sizes.

    Language:R0100

  • tiger7789/Software_Promotion_Campaign_Causal_ML

    Explore the impact of discounts and tech support on revenue through Causal ML models. This repo provides an analysis notebook, data, and a guide on leveraging machine learning for strategic business decisions.

    Language:Jupyter Notebook00

  • mmuratardag/AC_NFsh_causal_segmentation

    Causal segmentation: estimating conditional average treatment effects for the heterogeneous groups in a sample

    Language:R

  • niklaslienau/ML-Methods-to-estimate-mutivalued-TE

    This repo contains all replication files for my M.Sc thesis on "Machine Learning Methods to estimate treatment effects with multivalued treatment".

    10