syrgkanislab / orthogonal_regularized_estimationLinks
Code associated with paper: Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models, Chernozhukov, Nekipelov, Semenova, Syrgkanis, 2018
☆16Updated 4 years ago
Alternatives and similar repositories for orthogonal_regularized_estimation
Users that are interested in orthogonal_regularized_estimation are comparing it to the libraries listed below
Sorting:
- (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’☆31Updated 2 years ago
- Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…☆25Updated 3 years ago
- ☆11Updated 7 years ago
- 💊 Comparing causality methods in a fair and just way.☆139Updated 5 years ago
- Non-parametrics for Causal Inference☆49Updated 3 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆84Updated 7 years ago
- 🪜 Bayesian Hierarchical Models at Scale☆51Updated 3 years ago
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆61Updated last week
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆26Updated 3 years ago
- Machine learning based causal inference/uplift in Python☆61Updated last year
- ☆24Updated 3 years ago
- Design of Simulations using WGAN☆52Updated 2 years ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆156Updated 4 years ago
- Code associated with paper: Orthogonal Machine Learning for Demand Estimation: High-Dimensional Causal Inference in Dynamic Panels, Seme…☆25Updated 2 years ago
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆60Updated 3 months ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆83Updated 7 months ago
- An R package to estimate the effect of interventions on univariate time series using ARIMA models☆23Updated last year
- EconML/CausalML KDD 2021 Tutorial☆161Updated last year
- Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and mu…☆69Updated 3 months ago
- R code for ''Bayesian method for causal inference in spatially-correlated multivariate time series''☆46Updated 4 years ago
- difference-in-differences in Python☆103Updated last year
- Some notes on Causal Inference, with examples in python☆153Updated 5 years ago
- A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and …☆63Updated 3 years ago
- ☆79Updated 4 years ago
- Fit Sparse Synthetic Control Models in Python☆83Updated last year
- Comparing different performance estimation methods for time series forecasting tasks☆37Updated 3 months ago
- An extension of CatBoost to probabilistic modelling☆145Updated last year
- Flowchart to help choose which causal inference book to read. See https://bradyneal.github.io/which-causal-inference-book for more info s…☆59Updated 5 years ago
- Machine Learning models using a Bayesian approach and often PyMC3☆25Updated 4 years ago
- Implements the Causal Forest algorithm formulated in Athey and Wager (2018).☆70Updated 5 years ago