KColangelo / Double-ML-Continuous-TreatmentLinks
Code for Colangelo and Lee (2025)
☆13Updated 4 months ago
Alternatives and similar repositories for Double-ML-Continuous-Treatment
Users that are interested in Double-ML-Continuous-Treatment are comparing it to the libraries listed below
Sorting:
- Replication files for Chernozhukov, Newey, Quintas-Martínez and Syrgkanis (2021) "RieszNet and ForestRiesz: Automatic Debiased Machine Le…☆14Updated 2 years ago
- ☆42Updated 4 years ago
- Code to run submissions for the Atlantic Causal Inference Competition☆42Updated 9 months ago
- Documentation and User Guide for DoubleML - Double Machine Learning in Python & R☆21Updated last week
- Causality with machine learning, topic including causal represenation learning, causal reinforcement learning☆11Updated 4 years ago
- Non-parametrics for Causal Inference☆47Updated 3 years ago
- ☆95Updated last year
- Policy learning via doubly robust empirical welfare maximization over trees☆81Updated 11 months ago
- Python implementation of Entropy Balancing for binary and continuous treatment☆19Updated 3 years ago
- Implementation of "Dynamic Causal Effects Evaluation in A/B Testing with a Reinforcement Learning Framework" (JASA 2023)☆30Updated last year
- Repository for the ISU Causal Inference Working Group☆12Updated last year
- ☆13Updated last year
- Code associated with paper: Orthogonal Machine Learning for Demand Estimation: High-Dimensional Causal Inference in Dynamic Panels, Seme…☆25Updated 2 years ago
- A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python☆63Updated last year
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆140Updated 11 months ago
- Quasi-Oracle Estimation of Heterogeneous Treatment Effects☆111Updated 4 years ago
- Approximately balanced estimation of average treatment effects in high dimensions.☆34Updated 3 years ago
- Implementation of Double Machine Learning☆35Updated last month
- The pygformula implements the parametric g-formula in Python. The parametric g-formula (Robins, 1986) uses longitudinal data with time-va…☆29Updated 2 months ago
- Implements the Causal Forest algorithm formulated in Athey and Wager (2018).☆70Updated 4 years ago
- Official repository for the mcf package.☆18Updated 2 months ago
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆26Updated 3 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆83Updated 7 years ago
- Repository for Introduction to Bayesian Estimation of Causal Effects☆62Updated 4 years ago
- Paper Repository☆11Updated 2 years ago
- Bayesian Causal Forests☆45Updated last year
- Materials Collection for Causal Inference☆46Updated 2 years ago
- ☆10Updated 3 years ago
- Sensitivity analysis tools for causal ML☆17Updated 2 weeks ago
- ☆24Updated 3 years ago