vveitch / causality-tutorialsLinks
Short tutorials on the use of machine learning methods for causal inference
☆48Updated 2 years ago
Alternatives and similar repositories for causality-tutorials
Users that are interested in causality-tutorials are comparing it to the libraries listed below
Sorting:
- ☆191Updated 2 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆80Updated 4 years ago
- Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflo…☆340Updated last year
- CSuite: A Suite of Benchmark Datasets for Causality☆78Updated 2 years ago
- Code for the paper "Local Causal Discovery for Estimating Causal Effects".☆11Updated last year
- Must-read papers and resources related to causal inference and machine (deep) learning☆741Updated 2 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆150Updated last year
- Example causal datasets with consistent formatting and ground truth☆96Updated 7 months ago
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆176Updated last year
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆26Updated 3 years ago
- A curated list of awesome work on causal inference, particularly in machine learning.☆109Updated 4 years ago
- Code for the paper "Joint Causal Inference from Multiple Contexts" (JMLR 2020)☆16Updated 5 years ago
- Scalable open-source software to run, develop, and benchmark causal discovery algorithms☆74Updated last week
- Notebooks for Applied Causal Inference Powered by ML and AI☆137Updated 7 months ago
- Resources related to causality☆266Updated last year
- ☆81Updated 5 years ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆159Updated 4 years ago
- ☆22Updated 2 years ago
- ☆22Updated 2 years ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆83Updated 10 months ago
- A data index for learning causality.☆480Updated 2 years ago
- Non-parametrics for Causal Inference☆50Updated 3 years ago
- Causal discovery algorithms and tools for implementing new ones☆237Updated 4 months ago
- Code for the paper "Causal Transformer for Estimating Counterfactual Outcomes"☆166Updated last year
- An optimization-based algorithm to accurately estimate the causal effects and robustly predict under distribution shifts. It leverages th…☆14Updated last year
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆84Updated 7 years ago
- Code for "Counterfactual Fairness" (NIPS2017)☆55Updated 7 years ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆68Updated 9 months ago
- A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…☆131Updated last year
- Data from the HeartSteps V1 study☆18Updated 2 years ago