napsternxg / awesome-causality
Resources related to causality
☆260Updated 11 months ago
Alternatives and similar repositories for awesome-causality:
Users that are interested in awesome-causality are comparing it to the libraries listed below
- A data index for learning causality.☆450Updated last year
- A (concise) curated list of awesome Causal Inference resources.☆225Updated 2 years ago
- Repository with code and slides for a tutorial on causal inference.☆567Updated 5 years ago
- A curated list of awesome work on causal inference, particularly in machine learning.☆98Updated 3 years ago
- The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML☆743Updated 6 months ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆155Updated 3 years ago
- Must-read papers and resources related to causal inference and machine (deep) learning☆693Updated 2 years ago
- A every-so-often-updated collection of every causality + machine learning paper submitted to arXiv in the recent past.☆415Updated 4 years ago
- Causal Inference in Python☆555Updated 4 years ago
- Some notes on Causal Inference, with examples in python☆149Updated 4 years ago
- Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflo…☆309Updated 3 months ago
- Causal Graphical Models in Python☆241Updated last year
- ☆464Updated 7 months ago
- Quasi-Oracle Estimation of Heterogeneous Treatment Effects☆105Updated 3 years ago
- Non-parametrics for Causal Inference☆43Updated 2 years ago
- List of python packages for causal inference☆17Updated 3 years ago
- A Python package for modular causal inference analysis and model evaluations☆752Updated 5 months ago
- ☆253Updated 2 years ago
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆58Updated last year
- EconML/CausalML KDD 2021 Tutorial☆161Updated last year
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆133Updated 7 months ago
- 💊 Comparing causality methods in a fair and just way.☆138Updated 4 years ago
- Packages of Example Data for The Effect☆135Updated 2 months ago
- ☆181Updated last year
- AutoML for causal inference.☆213Updated last month
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆71Updated 3 years ago
- Counterfactual Regression☆298Updated 2 years ago
- A collection of visual guides to help applied scientists learn causal inference.☆251Updated 2 years ago
- Working repository for Causal Tree and extensions☆435Updated 4 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆81Updated 6 years ago