-
Towards Robust Relational Causal Discovery
Relational causal discovery algorithm that effectively works with the available (nec-essarily imperfect) relational CI tests. -
Bayesian causal inference via probabilistic program synthesis
The dataset used in the paper is a set of probabilistic programs that generate, edit, and interpret the source code of causal models. -
Invariant Representation Learning for Treatment Effect Estimation
The dataset used in the paper is a collection of multiple datasets from different environments, each containing treatment, outcome, and covariate information. -
A large scale benchmark for uplift modeling
A large scale benchmark for uplift modeling. -
Monotone Function Estimation in the Presence of Extreme Data Coarsening
The dataset used in the paper for estimating the effect of maternal smoking on birth weight. -
Estimating Conditional Average Treatment Effects
The dataset used in the paper for estimating conditional average treatment effects. -
Latent Variable Confounding Simulation Dataset
The dataset used in the paper is a latent variable confounding simulation dataset. -
Total Random Simulation Dataset
The dataset used in the paper is a total random simulation dataset. -
Regression Discontinuity Design Dataset
The dataset used in the paper is a regression discontinuity design dataset. -
BlogCatalog
The BlogCatalog dataset is a blog directory that manages bloggers and their blogs. Each unit is a blogger and the features are bag-of-words representations of keywords in... -
IHDP dataset
IHDP dataset, a semi-synthetic dataset which consists of 747 patients with 25 covariates. The patient covariates come from a real randomized medical study from the 80s, however... -
Intact-VAE: Estimating Treatment Effects under Unobserved Confounding
Intact-VAE: Estimating Treatment Effects under Unobserved Confounding
