Balancing Confounder Distributions with Forest Energy Balancing

Estimates average treatment effects using kernel energy balancing with random forest similarity kernels. A multivariate random forest jointly models covariates, outcome, and treatment to build a similarity kernel between observations. This kernel is then used for energy balancing to create weights that control for confounding. The method is described in De and Huling (2025) .