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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 ...
Created
2018-05-31
1,012 commits to main branch, last one 2 days ago
A resource list for causality in statistics, data science and physics
causal
physics
causality
causation
statistics
data-science
causal-impact
causal-models
meta-learning
causal-networks
causal-discovery
causal-inference
machine-learning
bayesian-inference
causality-analysis
statistical-physics
causality-algorithms
statistical-inference
statistical-mechanics
causal-machine-learning
Created
2018-01-04
235 commits to master branch, last one 2 months ago
🛠 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】
Created
2022-11-11
27 commits to master branch, last one about a year ago
Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.
Created
2019-12-06
14 commits to master branch, last one 2 years ago
🎯 :closed_book: Targeted Learning in R: A Causal Data Science Handbook
Created
2019-03-23
494 commits to master branch, last one 11 months ago
A General Causal Inference Framework by Encoding Generative Modeling
Created
2022-06-07
237 commits to main branch, last one 16 days ago