kochbj / Deep-Learning-for-Causal-InferenceLinks
Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2 and Pytorch.
☆328Updated 7 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
Sorting:
- Must-read papers and resources related to causal inference and machine (deep) learning☆718Updated 2 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆140Updated 11 months ago
- A curated list of awesome work on causal inference, particularly in machine learning.☆105Updated 4 years ago
- A data index for learning causality.☆467Updated last year
- ☆268Updated 3 years ago
- EconML/CausalML KDD 2021 Tutorial☆161Updated last year
- Resources related to causality☆265Updated last year
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆156Updated 3 years ago
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆88Updated 2 years ago
- A (concise) curated list of awesome Causal Inference resources.☆236Updated 2 years ago
- DoubleML - Double Machine Learning in Python☆594Updated last week
- The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML☆762Updated 10 months ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆75Updated 4 years ago
- ☆185Updated 2 years ago
- Counterfactual Regression☆307Updated 2 years ago
- Makes algorithms/code in Tetrad available in Python via JPype☆78Updated last month
- Notebooks for Applied Causal Inference Powered by ML and AI☆118Updated 2 months ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆83Updated 7 years ago
- Code accompanying the paper "Empirical analysis of model selection for heterogeneous causal effect estimation"☆13Updated 4 months ago
- Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018☆61Updated 5 years ago
- A collection of visual guides to help applied scientists learn causal inference.☆268Updated 2 years ago
- Non-parametrics for Causal Inference☆47Updated 3 years ago
- Example causal datasets with consistent formatting and ground truth☆83Updated last month
- Code for "Learning End-to-End Patient Representations through Self-Supervised Covariate Balancing for Causal Treatment Effect Estimation"☆25Updated 2 years ago
- Short tutorials on the use of machine learning methods for causal inference☆49Updated 2 years ago
- Implements the Causal Forest algorithm formulated in Athey and Wager (2018).☆70Updated 4 years ago
- DAGs with NO TEARS: Continuous Optimization for Structure Learning☆628Updated last year
- ☆78Updated 4 years ago
- ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.☆128Updated 2 years ago
- python implementation of Peng Ding's "First Course in Causal Inference"☆164Updated 11 months ago