2 papers
stat.ML2026
On the Computational Efficiency of Bayesian Additive Regression Trees: An Asymptotic Analysis
Yan Shuo Tan, Omer Ronen, Theo Saarinen +1
Bayesian Additive Regression Trees (BART) is a popular Bayesian non-parametric regression model that is commonly used in causal inference and beyond. Its strong predictive performa…
stat.ME2025
Integrating Random Forests and Generalized Linear Models for Improved Accuracy and Interpretability
Abhineet Agarwal, Ana M. Kenney, Yan Shuo Tan +2
Random forests (RFs) are among the most popular supervised learning algorithms due to their nonlinear flexibility and ease-of-use. However, as black box models, they can only be in…