Trending repositories for topic causal-inference
An index of algorithms for learning causality with data
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
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 ...
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
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 goal...
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
Next generation of automated data exploratory analysis and visualization platform.
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
An index of algorithms for learning causality with data
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
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 ...
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 goal...
Next generation of automated data exploratory analysis and visualization platform.
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
An index of algorithms for learning causality with data
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 ...
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
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 goal...
Next generation of automated data exploratory analysis and visualization platform.
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
A curated list of causal inference libraries, resources, and applications.
A Python library that helps data scientists to infer causation rather than observing correlation.
:exclamation: uplift modeling in scikit-learn style in python :snake:
A (concise) curated list of awesome Causal Inference resources.
A Python package for causal inference in quasi-experimental settings
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
[ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization
[ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
Fast and customizable framework for automatic and quick Causal Inference in Python
A (concise) curated list of awesome Causal Inference resources.
An index of algorithms for learning causality with data
A curated list of causal inference libraries, resources, and applications.
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
:exclamation: uplift modeling in scikit-learn style in python :snake:
Open-source Python library for statistical analysis of randomised control trials (A/B tests)
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
Causal Inference for The Brave and True 책의 한국어 번역 자료입니다.
:arrow_lower_left: :arrow_lower_right: An R package for working with causal directed acyclic graphs (DAGs)
A Python package for causal inference in quasi-experimental settings
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
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 goal...
A Python library that helps data scientists to infer causation rather than observing correlation.
An index of algorithms for learning causality with data
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
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 ...
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 goal...
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
Next generation of automated data exploratory analysis and visualization platform.
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
A Python package for causal inference in quasi-experimental settings
A curated list of causal inference libraries, resources, and applications.
Causal Inference for the Brave and True的中文翻译版。全部代码基于Python，适用于计量经济学、量化社会学、策略评估等领域。英文版原作者：Matheus Facure
Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
A Python library that helps data scientists to infer causation rather than observing correlation.
A Python package for modular causal inference analysis and model evaluations
:exclamation: uplift modeling in scikit-learn style in python :snake:
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
Notebooks for Applied Causal Inference Powered by ML and AI
CausalMatch is a Bytedance research project aimed at integrating cutting-edge machine learning and econometrics methods to bring about automation in decision-making process.
A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more
An index of algorithms for learning causality with data
Python implementation of Richard McElreath's Statistical Rethinking 2023 lecture series on causal inference & Bayesian estimation.
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
🛠 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】
Causal Inference Crash Course for Scientists - contains slides and Jupyter notebooks
The repository contains lists of papers on causality and how relevant techniques are being used to further enhance deep learning era computer vision solutions.
CausalMatch is a Bytedance research project aimed at integrating cutting-edge machine learning and econometrics methods to bring about automation in decision-making process.
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 ...
Next generation of automated data exploratory analysis and visualization platform.
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
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 goal...
A curated list of causal inference libraries, resources, and applications.
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
An index of algorithms for learning causality with data
Causal Inference for the Brave and True的中文翻译版。全部代码基于Python，适用于计量经济学、量化社会学、策略评估等领域。英文版原作者：Matheus Facure
A Python package for causal inference in quasi-experimental settings
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
A Python library that helps data scientists to infer causation rather than observing correlation.
Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
Must-read papers and resources related to causal inference and machine (deep) learning
Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
A Python package for modular causal inference analysis and model evaluations
Notebooks for Applied Causal Inference Powered by ML and AI
Fast and customizable framework for automatic and quick Causal Inference in Python
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 pac...
A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more
Python implementation of Richard McElreath's Statistical Rethinking 2023 lecture series on causal inference & Bayesian estimation.
python implementation of Peng Ding's "First Course in Causal Inference"
Active Bayesian Causal Inference (Neurips'22)
A curated list of causal inference libraries, resources, and applications.
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
A spatiotemporal causal convolutional network for predicting PM2.5 concentrations.
Causal Inference for the Brave and True的中文翻译版。全部代码基于Python，适用于计量经济学、量化社会学、策略评估等领域。英文版原作者：Matheus Facure
🛠 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】
