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.
A Python library that helps data scientists to infer causation rather than observing correlation.
Next generation of automated data exploratory analysis and visualization platform.
Fast and customizable framework for automatic and quick Causal Inference in Python
python implementation of Peng Ding's "First Course in Causal Inference"
A curated list of causal inference libraries, resources, and applications.
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.
Fast and customizable framework for automatic and quick Causal Inference in Python
python implementation of Peng Ding's "First Course in 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.
A curated list of causal inference libraries, resources, and applications.
A Python library that helps data scientists to infer causation rather than observing correlation.
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
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.
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.
Next generation of automated data exploratory analysis and visualization platform.
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 Inference for The Brave and True 책의 한국어 번역 자료입니다.
A Python library that helps data scientists to infer causation rather than observing correlation.
A Python package for causal inference in quasi-experimental settings
Notebooks for Applied Causal Inference Powered by ML and AI
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
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.
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
Fast and customizable framework for automatic and quick Causal Inference in Python
python implementation of Peng Ding's "First Course in Causal Inference"
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
Notebooks for Applied Causal Inference Powered by ML and AI
A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more
Fast and customizable framework for automatic and quick Causal Inference in Python
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 책의 한국어 번역 자료입니다.
python implementation of Peng Ding's "First Course in Causal Inference"
A curated list of causal inference libraries, resources, and applications.
A Python package for causal inference in quasi-experimental settings
Must-read papers and resources related to causal inference and machine (deep) learning
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
:exclamation: uplift modeling in scikit-learn style in python :snake:
Next generation of automated data exploratory analysis and visualization platform.
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...
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
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.
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 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.
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
An index of algorithms for learning causality with data
A Python library that helps data scientists to infer causation rather than observing correlation.
Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
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 책의 한국어 번역 자료입니다.
Fast and customizable framework for automatic and quick Causal Inference in Python
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
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
Official PyTorch Implementation for "Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian Detection" in CVPR 2024
Julia code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
A curated list of causal inference libraries, resources, and applications.
Python implementation of Richard McElreath's Statistical Rethinking 2023 lecture series on causal inference & Bayesian estimation.
CausalMatch is a Bytedance research project aimed at integrating cutting-edge machine learning and econometrics methods to bring about automation in decision-making process.
Notebooks for Applied Causal Inference Powered by ML and AI
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
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.
python implementation of Peng Ding's "First Course in Causal Inference"
Causal Inference for The Brave and True 책의 한국어 번역 자료입니다.
A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more
A framework to infer causality on a pair of time series of real numbers based on Variable-lag Granger causality and transfer entropy.
🎯 :closed_book: Targeted Learning in R: A Causal Data Science Handbook
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
CausalMatch is a Bytedance research project aimed at integrating cutting-edge machine learning and econometrics methods to bring about automation in decision-making process.
Official PyTorch Implementation for "Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian Detection" in CVPR 2024
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.
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.
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...
An index of algorithms for learning causality with data
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
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
A Python package for causal inference in quasi-experimental settings
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.
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.
Must-read papers and resources related to causal inference and machine (deep) learning
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
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"
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 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】
A spatiotemporal causal convolutional network for predicting PM2.5 concentrations.
A curated list of causal inference libraries, resources, and applications.
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).