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treatment-effects x

22 search results found

Dowhy ⭐ 6,730

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.

Econml ⭐ 3,522

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

Causal Ml ⭐ 376

Must-read papers and resources related to causal inference and machine (deep) learning

Rdrobust ⭐ 60

Statistical inference and graphical procedures for RD designs using local polynomial and partitioning regression methods.

Causeinfer ⭐ 54

Machine learning based causal inference/uplift in Python

Causalegm ⭐ 35

A General Causal Inference Framework by Encoding Generative Modeling

Openasce ⭐ 35

OpenASCE (Open All-Scale Casual Engine) is a Python package for end-to-end large-scale causal learning. It provides causal discovery, causal effect estimation and attribution algorithms all in one package.

Network Deconfounder Wsdm20 ⭐ 35

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

Personalized ⭐ 24

Methods for subgroup identification / personalized medicine / individualized treatment rules

Causaltoolbox ⭐ 23

Cfml_tools ⭐ 12

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

Causalinference ⭐ 12

CRAN Task View: Causal Inference

Cikm18 Lcva ⭐ 12

Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.

📦 🎲 R/txshift: Efficient Estimation of the Causal Effects of Stochastic Interventions, with Corrections for Outcome-Dependent Sampling

Causalglm ⭐ 11

Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning

Tmle3shift ⭐ 11

🎯 🎲 Targeted Learning of the Causal Effects of Stochastic Interventions

Rdpackages.github.io ⭐ 10

Regression Discontinuity Design Software Packages

Medoutcon ⭐ 10

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

Causalhal ⭐ 9

Adaptive debiased machine learning of treatment effects with the highly adaptive lasso

Rddensity ⭐ 9

Manipulation testing using local polynomial density methods.

Rdlocrand ⭐ 6

Finite-sample inference for RD designs using local randomization and related methods.

📦 🎲 R/medshift: Causal Mediation Analysis for Stochastic Interventions

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Machine Learning Treatment Effects (17)

1-22 of 22 search results

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