There are 24 repositories under causality topic.
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 Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
An index of algorithms for learning causality with data
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
关于domain generalization,domain adaptation,causality,robutness,prompt,optimization,generative model各式各样研究的阅读笔记
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
Causal Discovery in Python. Translation and extension of the Tetrad Java code.
Curated research at the intersection of causal inference and natural language processing.
:exclamation: uplift modeling in scikit-learn style in python :snake:
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.
YLearn, a pun of "learn why", is a python package for causal inference
Causal Inference for The Brave and True 책의 한국어 번역 자료입니다.
CausalLift: Python package for causality-based Uplift Modeling in real-world business
A curated list of trustworthy deep learning papers. Daily updating...
Code for the Recsys 2018 paper entitled Causal Embeddings for Recommandation.
Salesforce CausalAI Library: A Fast and Scalable framework for Causal Analysis of Time Series and Tabular Data
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning
A (concise) curated list of awesome Causal Inference resources.
This repository contains the dataset and the PyTorch implementations of the models from the paper Recognizing Emotion Cause in Conversations.
A Python package for causal inference using Synthetic Controls
The official implementation of "Disentangling User Interest and Conformity for Recommendation with Causal Embedding" (WWW '21)
Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test in Python
Awesome Neural Logic and Causality: MLN, NLRL, NLM, etc. 因果推断,神经逻辑,强人工智能逻辑推理前沿领域。
Hyper-geometric computational causality library for Rust