Propensity Patchwork Kriging for Scalable Inference on Heterogeneous Treatment Effects
用于异质性处理效应可扩展推断的倾向得分拼接克里金
Gaussian process-based models are attractive for estimating heterogeneous treatment effects (HTE), but their computational cost limits scalability in causal inference settings. In this work, we address this challenge by extending Patchwork Kriging into the causal inference framework. Our proposed method partitions the data according to the estimated propensity score and applies Patchwork Kriging to enforce continuity of HTE estimates across adjacent regions. By imposing…