Abstract
This Master's research proposal focuses on pioneering the use of Bayesian Neural Networks (BNNs) for Conditional Average Treatment Effect (CATE) estimation and on improving the use of the Bayesian Additive Regression Tree (BART) model for CATE estimation, leveraging the framework proposed by Hahn et al. (2020). It addresses the notable gap in literature concerning BNN applications in CATE…