Extended Fiducial Inference for Individual Treatment Effects via Deep Neural Networks
通过深度神经网络开展个体治疗效应的扩展信赖推断
Individual treatment effect estimation has gained significant attention in recent data science literature. This work introduces the Double Neural Network (Double-NN) method to address this problem within the framework of extended fiducial inference (EFI). In the proposed method, deep neural networks are used to model the treatment and control effect functions, while an additional neural network is employed to estimate their parameters. The universal approximation capability…