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Bayesian nonparametric modeling for causal inference
Bayesian nonparametric modeling for causal inference. -
BD-HSIC dataset
The dataset used in this paper is a synthetic dataset for testing causal inference methods. -
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. -
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. -
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
