TianyiPeng / causaltensor
A python package for causal inference in panels
☆12Updated 2 weeks ago
Alternatives and similar repositories for causaltensor:
Users that are interested in causaltensor are comparing it to the libraries listed below
- ☆22Updated 3 years ago
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆26Updated 3 years ago
- Bayesian Causal Forests☆43Updated 10 months ago
- Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr☆51Updated 4 months ago
- ☆93Updated last year
- Data for and description of the ACIC 2023 data competition☆32Updated last year
- Repository for Introduction to Bayesian Estimation of Causal Effects☆59Updated 4 years ago
- A package for conformal prediction with conditional guarantees.☆52Updated last month
- Tools for causal discovery in R☆19Updated 3 weeks ago
- Conditional calibration of conformal p-values for outlier detection.☆34Updated 2 years ago
- Repository for the ISU Causal Inference Working Group☆12Updated 11 months ago
- difference-in-differences in Python☆100Updated last year
- Design of Simulations using WGAN☆49Updated 2 years ago
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆56Updated 10 months ago
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆44Updated last year
- The pygformula implements the parametric g-formula in Python. The parametric g-formula (Robins, 1986) uses longitudinal data with time-va…☆25Updated 2 weeks ago
- Replication files for Chernozhukov, Newey, Quintas-Martínez and Syrgkanis (2021) "RieszNet and ForestRiesz: Automatic Debiased Machine Le…☆14Updated 2 years ago
- R and python implementations of Accelerated Bayesian Causal Forest.☆25Updated 9 months ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆81Updated 3 months ago
- Policy learning via doubly robust empirical welfare maximization over trees☆78Updated 9 months ago
- Paper Repository☆11Updated 2 years ago
- Notebooks for Applied Causal Inference Powered by ML and AI☆110Updated 2 weeks ago
- ☆18Updated last year
- ☆8Updated 3 years ago
- Course material for the PhD course in Advanced Bayesian Learning☆59Updated last month
- Python package for (conditional) independence testing and statistical functions related to causality.☆28Updated 3 months ago
- Causal Inference in Python☆41Updated 2 months ago
- This tutorial will introduce key concepts in machine learning-based causal inference. This tutorial is used by professor Susan Athey in t…☆12Updated last year
- Simulations for predictive model selection in causal inference☆13Updated 2 months ago
- 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 last year