anishazaveri / austen_plotsLinks
Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".
☆26Updated 4 years ago
Alternatives and similar repositories for austen_plots
Users that are interested in austen_plots are comparing it to the libraries listed below
Sorting:
- Non-parametrics for Causal Inference☆50Updated 3 years ago
- ☆95Updated last year
- Design of Simulations using WGAN☆55Updated 3 years ago
- Code to run submissions for the Atlantic Causal Inference Competition☆43Updated last year
- Bayesian Causal Forests☆50Updated last year
- Code to reproduce the numerical experiments in the paper Domain adaptation under structural causal models by Yuansi Chen and Peter Bühlma…☆18Updated 4 years ago
- Short tutorials on the use of machine learning methods for causal inference☆49Updated 3 years ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆83Updated 11 months ago
- Policy learning via doubly robust empirical welfare maximization over trees☆86Updated 4 months ago
- ☆24Updated 4 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆83Updated 4 years ago
- Data for and description of the ACIC 2023 data competition☆32Updated 2 years ago
- Quasi-Oracle Estimation of Heterogeneous Treatment Effects☆119Updated 4 years ago
- Course materials for Advanced Topics in Statistical Learning, Spring 2023☆49Updated 4 months ago
- Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds☆11Updated 6 years ago
- Repository for Introduction to Bayesian Estimation of Causal Effects☆68Updated 5 years ago
- Tools for causal discovery in R☆20Updated 9 months ago
- Python package to compute conditional and non-conditional causal effects.☆36Updated 3 years ago
- This is a read-only mirror of the CRAN R package repository. pcalg — Methods for Graphical Models and Causal Inference. Homepage: https…☆35Updated last year
- Implementation of "Dynamic Causal Effects Evaluation in A/B Testing with a Reinforcement Learning Framework" (JASA 2023)☆32Updated 2 years ago
- Tools for conformal inference in regression☆251Updated last year
- R and python implementations of Accelerated Bayesian Causal Forest.☆25Updated last year
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆62Updated 4 months ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆160Updated 4 years ago
- Code for the paper "Joint Causal Inference from Multiple Contexts" (JMLR 2020)☆16Updated 5 years ago
- An optimization-based algorithm to accurately estimate the causal effects and robustly predict under distribution shifts. It leverages th…☆14Updated last year
- A unified interface for the estimation of causal networks☆22Updated 5 years ago
- ☆44Updated 4 years ago
- An Interface to Specify Causal Graphs and Compute Balke Bounds☆22Updated 9 months ago
- Conditional calibration of conformal p-values for outlier detection.☆37Updated 3 years ago