EddieYang211 / ebal-pyLinks
Python implementation of Entropy Balancing for binary and continuous treatment
☆20Updated 3 years ago
Alternatives and similar repositories for ebal-py
Users that are interested in ebal-py are comparing it to the libraries listed below
Sorting:
- Causality with machine learning, topic including causal represenation learning, causal reinforcement learning☆11Updated 4 years ago
- Code for Colangelo and Lee (2025)☆15Updated 8 months ago
- ☆44Updated 4 years ago
- Code to run submissions for the Atlantic Causal Inference Competition☆42Updated last year
- Implements the Causal Forest algorithm formulated in Athey and Wager (2018).☆69Updated 5 years ago
- Repository for the ISU Causal Inference Working Group☆12Updated last year
- Non-parametrics for Causal Inference☆49Updated 3 years ago
- Distributional Random Forests (Cevid et al., 2020)☆45Updated 2 years ago
- Replication files for Chernozhukov, Newey, Quintas-Martínez and Syrgkanis (2021) "RieszNet and ForestRiesz: Automatic Debiased Machine Le…☆14Updated 3 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆147Updated last year
- ☆95Updated last year
- The pygformula implements the parametric g-formula in Python. The parametric g-formula (Robins, 1986) uses longitudinal data with time-va…☆30Updated 2 weeks ago
- A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python☆67Updated last year
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆91Updated 2 years ago
- Synthetic difference in differences for Python☆84Updated last year
- Bayesian Causal Forests☆48Updated last year
- [ICLR 2021] Code for: Varying Coefficient Neural Network with Functional Targeted Regularization for Estimating Continuous Treatment Effe…☆88Updated 3 years ago
- Data for and description of the ACIC 2023 data competition☆32Updated 2 years ago
- Quasi-Oracle Estimation of Heterogeneous Treatment Effects☆116Updated 4 years ago
- This tutorial will introduce key concepts in machine learning-based causal inference. This tutorial is used by professor Susan Athey in t…☆13Updated 2 years ago
- Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr☆52Updated 4 months ago
- Policy learning via doubly robust empirical welfare maximization over trees☆84Updated 2 months ago
- Materials Collection for Causal Inference☆47Updated 2 years ago
- ☆17Updated 5 months ago
- R and python implementations of Accelerated Bayesian Causal Forest.☆25Updated last year
- This material has been created based on the tutorials of the course 14.388 Inference on Causal and Structural Parameters Using ML and AI …☆16Updated 2 years ago
- scikit-learn compatible Python bindings for grf (generalized random forests) C++ random forest library☆34Updated 3 years ago
- R package cfcausal☆33Updated 2 years ago
- difference-in-differences in Python☆105Updated last year
- Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and mu…☆70Updated 5 months ago