Trending repositories for topic causal-inference
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 Discovery in Python. It also includes (conditional) independence tests and score functions.
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.
A curated list of causal inference libraries, resources, and applications.
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 framework to infer causality on a pair of time series of real numbers based on Variable-lag Granger causality and transfer entropy.
🛠 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】
Algorithms for detecting associations, dynamical influences and causal inference from data.
Causal inference, graphical models and structure learning in Julia
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 library that helps data scientists to infer causation rather than observing correlation.
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.
An index of algorithms for learning causality with data
A framework to infer causality on a pair of time series of real numbers based on Variable-lag Granger causality and transfer entropy.
🛠 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】
Algorithms for detecting associations, dynamical influences and causal inference from 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.
Causal inference, graphical models and structure learning in Julia
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
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
Next generation of automated data exploratory analysis and visualization platform.
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...
A Python library that helps data scientists to infer causation rather than observing correlation.
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.
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.
An index of algorithms for learning causality with data
Next generation of automated data exploratory analysis and visualization platform.
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 curated list of causal inference libraries, resources, and applications.
A Python library that helps data scientists to infer causation rather than observing correlation.
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, graphical models and structure learning in Julia
A Python package for modular causal inference analysis and model evaluations
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
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 framework to infer causality on a pair of time series of real numbers based on Variable-lag Granger causality and transfer entropy.
A framework to infer causality on a pair of time series of real numbers based on Variable-lag Granger causality and transfer entropy.
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.
🛠 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】
Python implementation of Richard McElreath's Statistical Rethinking 2023 lecture series on causal inference & Bayesian estimation.
Causal inference, graphical models and structure learning in Julia
Algorithms for detecting associations, dynamical influences and causal inference from data.
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
Tutorial in Python targeted at Epidemiologists. Will discuss the basics of analysis in Python 3
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 curated list of causal inference libraries, resources, and applications.
A Python package for modular causal inference analysis and model evaluations
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.
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
An index of algorithms for learning causality with data
A Python library that helps data scientists to infer causation rather than observing correlation.
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 ...
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.
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.
A Python package for causal inference in quasi-experimental settings
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
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.
Fast and customizable framework for automatic and quick Causal Inference in Python
A Python library that helps data scientists to infer causation rather than observing correlation.
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 modular causal inference analysis and model evaluations
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 Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
Fast and customizable framework for automatic and quick Causal Inference in Python
Python implementation of Richard McElreath's Statistical Rethinking 2023 lecture series on causal inference & Bayesian estimation.
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 Python package for causal inference in quasi-experimental settings
A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more
Active Bayesian Causal Inference (Neurips'22)
A curated list of causal inference libraries, resources, and applications.
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...
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
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】
Algorithms for detecting associations, dynamical influences and causal inference from data.
A framework to infer causality on a pair of time series of real numbers based on Variable-lag Granger causality and transfer entropy.
Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events
python implementation of Peng Ding's "First Course in Causal Inference"
Python implementation of Richard McElreath's Statistical Rethinking 2023 lecture series on causal inference & Bayesian estimation.
Fast and customizable framework for automatic and quick Causal Inference in Python
A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more
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...
Next generation of automated data exploratory analysis and visualization platform.
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 ...
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 curated list of causal inference libraries, resources, and applications.
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.
A Python package for causal inference in quasi-experimental settings
An index of algorithms for learning causality with data
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
A Python library that helps data scientists to infer causation rather than observing correlation.
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
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 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.
Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
Must-read papers and resources related to causal inference and machine (deep) learning
:exclamation: uplift modeling in scikit-learn style in python :snake:
A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more
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...
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 Crash Course for Scientists - contains slides and Jupyter notebooks
Active Bayesian Causal Inference (Neurips'22)
[ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization
A list of Graph Causal Learning materials.
A spatiotemporal causal convolutional network for predicting PM2.5 concentrations.
🛠 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】
A Python package for causal inference in quasi-experimental settings
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
The repository contains lists of papers on causality and how relevant techniques are being used to further enhance deep learning era computer vision solutions.
Tutorial for a target trial emulation with a time-varying exposure, time-dependent confounding, time-to-event outcome, and Sequentially Doubly Robust estimation (Hoffman et al. 2022).
[KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua.