📚 Publications

Publications listed in reverse chronological order.


2024


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    Some models are useful, but for how long?: A decision theoretic approach to choosing when to refit large-scale prediction models
    Kentaro Hoffman , Stephen Salerno, Jeff Leek, Tyler McCormick
    Under Review, 2024
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    IPD: An R Package for Conducting Inference on Predicted Data
    Stephen Salerno, Jiacheng Miao, Awan Afiaz, Kentaro Hoffman, Anna Neufeld, Qiongshi Lu, Tyler H. McCormick, Jeffrey T. Leek
    Under Review, 2024
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    Using Rashomon Sets for Robust Active Learning
    Simon Dovan Nguyen,Kentaro Hoffman, Tyler McCormick
    NeurIPS Workshop on Bayesian Decision Making and Uncertainty, 2024
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    Bayesian Optimal Experimental Design of Streaming Data Incorporating Machine Learning-Generated Synthetic Data
    Kentaro Hoffman and Tyler H. McCormick
    NeurIPS Workshop on Bayesian Decision Making and Uncertainty, 2024
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    From Narratives to Numbers: Valid Inference Using Language Model Predictions from Verbal Autopsy Narratives
    Shuxian Fan, Adam Visokay, Kentaro Hoffman, Stephen Salerno, Li Liu, Jeffrey T. Leek, and Tyler H. McCormick
    Conference on Language Models (COLM), 2024
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2023

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    Effects of epileptiform activity on discharge outcome in critically ill patients in the USA: a retrospective cross-sectional study
    Harsh Parikh, Kentaro Hoffman, Haoqi Sun, Sahar F Zafar, Wendong Ge, Jin Jing, Lin Liu, Jimeng Sun, Aaron Struck, Alexander Volfovsky, Cynthia Rudin, M Brandon Westover
    The Lancet Digital Health, 2023
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