GP-BART: a novel Bayesian additive regression trees approach using Gaussian processes. (arXiv:2204.02112v1 [stat.ME])

The Bayesian additive regression trees (BART) model is an ensemble method
extensively and successfully used in regression tasks due to its consistently
strong predictive performance and its ability to quantify uncertainty. BART
combines "weak" tree models through a set of shrinkage priors, whereby each
tree explains a small portion of the variability in the data. However, the lack
of smoothness and the absence of a covariance structure over the observations
in standard BART can yield poor performance in cases where …

arxiv bart bayesian processes regression trees