kochbj / Deep-Learning-for-Causal-Inference
Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2 and Pytorch.
☆314Updated 5 months ago
Alternatives and similar repositories for Deep-Learning-for-Causal-Inference:
Users that are interested in Deep-Learning-for-Causal-Inference are comparing it to the libraries listed below
- Must-read papers and resources related to causal inference and machine (deep) learning☆698Updated 2 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆136Updated 9 months ago
- ☆263Updated 2 years ago
- A data index for learning causality.☆462Updated last year
- A curated list of awesome work on causal inference, particularly in machine learning.☆100Updated 3 years ago
- EconML/CausalML KDD 2021 Tutorial☆161Updated last year
- Resources related to causality☆261Updated last year
- Counterfactual Regression☆304Updated 2 years ago
- DoubleML - Double Machine Learning in Python☆563Updated last week
- The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML☆754Updated 7 months ago
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆87Updated 2 years ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆156Updated 3 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆82Updated 6 years ago
- Makes algorithms/code in Tetrad available in Python via JPype☆72Updated this week
- Causal discovery algorithms and tools for implementing new ones☆215Updated 2 months ago
- Lecture notes for the Causality in Machine Learning course☆14Updated 5 years ago
- A (concise) curated list of awesome Causal Inference resources.☆229Updated 2 years ago
- A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python☆62Updated last year
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆72Updated 3 years ago
- Short tutorials on the use of machine learning methods for causal inference☆49Updated 2 years ago
- Example causal datasets with consistent formatting and ground truth☆80Updated last year
- Code accompanying the paper "Empirical analysis of model selection for heterogeneous causal effect estimation"☆12Updated last month
- Notebooks for Applied Causal Inference Powered by ML and AI☆109Updated this week
- Python package for causal discovery based on LiNGAM.☆406Updated 2 weeks ago
- A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…☆114Updated last year
- Code for "Learning End-to-End Patient Representations through Self-Supervised Covariate Balancing for Causal Treatment Effect Estimation"☆22Updated last year
- A Python package for modular causal inference analysis and model evaluations☆761Updated this week
- A collection of visual guides to help applied scientists learn causal inference.☆263Updated 2 years ago
- ☆182Updated 2 years ago
- 4th Year project aiming to implement PC, FCI and RFCI algorithms in python☆14Updated 5 years ago