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Found 2 papers, 2 papers with code
Causal Inference with the Instrumental Variable Approach and Bayesian Nonparametric Machine Learning
We provide a new flexible framework for inference with the instrumental variable model.
BART: Bayesian additive regression trees
We develop a Bayesian "sum-of-trees" model where each tree is constrained by a regularization prior to be a weak learner, and fitting and inference are accomplished via an iterative Bayesian backfitting MCMC algorithm that generates samples from a posterior.
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Causal Inference
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