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stat.ME2025
Estimation and Inference for the Average Treatment Effect in a Score-Explained Heterogeneous Treatment Effect Model
Kevin Christian Wibisono, Debarghya Mukherjee, Moulinath Banerjee +1
In many practical situations, randomly assigning treatments to subjects is uncommon due to feasibility constraints. For example, economic aid programs and merit-based scholarships…
stat.ME2024
Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift
Jiawei Ge, Debarghya Mukherjee, Jianqing Fan
As machine learning models are increasingly deployed in dynamic environments, it becomes paramount to assess and quantify uncertainties associated with distribution shifts. A distr…
stat.ME2024
UTOPIA: Universally Trainable Optimal Prediction Intervals Aggregation
Jianqing Fan, Jiawei Ge, Debarghya Mukherjee
Uncertainty quantification in prediction presents a compelling challenge with vast applications across various domains, including biomedical science, economics, and weather forecas…