Nonparametric variable importance using an augmented neural network with multi-task learning. - Jean Feng; Brian D. Williamson; Marco Carone; Noah Simon (ICML, 2018)

An analysis of the cost of hyper-parameter selection via split-sample validation, with applications to penalized regression. - Jean Feng; Noah Simon (CoRR, 2019)

Selective prediction-set models with coverage guarantees. - Jean Feng; Arjun Sondhi; Jessica Perry; Noah Simon (CoRR, 2019)

Approval policies for modifications to Machine Learning-Based Software as a Medical Device: A study of bio-creep. - Jean Feng; Scott Emerson; Noah Simon (CoRR, 2019)

Efficient nonparametric statistical inference on population feature importance using Shapley values. - Brian D. Williamson; Jean Feng (ICML, 2020)

Learning how to approve updates to machine learning algorithms in non-stationary settings. - Jean Feng (CoRR, 2020)

Learning to safely approve updates to machine learning algorithms. - Jean Feng (CHIL, 2021)

Sequential algorithmic modification with test data reuse. - Jean Feng; Gene Pennello; Nicholas Petrick; Berkman Sahiner; Romain Pirracchio; Alexej Gossmann (UAI, 2022)

Monitoring machine learning (ML)-based risk prediction algorithms in the presence of confounding medical interventions. - Jean Feng; Alexej Gossmann; Gene Pennello; Nicholas Petrick; Berkman Sahiner; Romain Pirracchio (CoRR, 2022)

Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees. - Jean Feng; Alexej Gossmann; Berkman Sahiner; Romain Pirracchio (J. Am. Medical Informatics Assoc., 2022)

Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials. - Andre Esteva; Jean Feng; Douwe van der Wal; Shih-Cheng Huang; Jeffry P. Simko; Sandy Devries; Emmalyn Chen; Edward M. Schaeffer; Todd M. Morgan; Yilun Sun; Amirata Ghorbani; Nikhil Naik 002; et al. (npj Digit. Medicine, 2022)

Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare. - Jean Feng; Rachael V. Phillips; Ivana Malenica; Andrew Bishara; Alan E. Hubbard; Leo A. Celi; Romain Pirracchio (npj Digit. Medicine, 2022)

Ensembled sparse-input hierarchical networks for high-dimensional datasets. - Jean Feng; Noah Simon (Stat. Anal. Data Min., 2022)

Towards a Post-Market Monitoring Framework for Machine Learning-based Medical Devices: A case study. - Jean Feng; Adarsh Subbaswamy; Alexej Gossmann; Harvineet Singh; Berkman Sahiner; Mi-Ok Kim; Gene Pennello; Nicholas Petrick; Romain Pirracchio; Fan Xia (CoRR, 2023)

A Brief Tutorial on Sample Size Calculations for Fairness Audits. - Harvineet Singh; Fan Xia; Mi-Ok Kim; Romain Pirracchio; Rumi Chunara; Jean Feng (CoRR, 2023)

Author Correction: Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials. - Andre Esteva; Jean Feng; Douwe van der Wal; Shih-Cheng Huang; Jeffry P. Simko; Sandy Devries; Emmalyn Chen; Edward M. Schaeffer; Todd M. Morgan; Yilun Sun; Amirata Ghorbani; Nikhil Naik 002; et al. (npj Digit. Medicine, 2023)

Is this model reliable for everyone? Testing for strong calibration. - Jean Feng; Alexej Gossmann; Romain Pirracchio; Nicholas Petrick; Gene Pennello; Berkman Sahiner (AISTATS, 2024)

Monitoring machine learning-based risk prediction algorithms in the presence of performativity. - Jean Feng; Alexej Gossmann; Gene Pennello; Nicholas Petrick; Berkman Sahiner; Romain Pirracchio (AISTATS, 2024)

Designing monitoring strategies for deployed machine learning algorithms: navigating performativity through a causal lens. - Jean Feng; Adarsh Subbaswamy; Alexej Gossmann; Harvineet Singh; Berkman Sahiner; Mi-Ok Kim; Gene Anthony Pennello; Nicholas Petrick; Romain Pirracchio; Fan Xia (CLeaR, 2024)

A hierarchical decomposition for explaining ML performance discrepancies. - Harvineet Singh; Fan Xia; Adarsh Subbaswamy; Alexej Gossmann; Jean Feng (NeurIPS, 2024)

Bayesian Concept Bottleneck Models with LLM Priors. - Jean Feng; Avni Kothari; Luke Zier; Chandan Singh; Yan Shuo Tan (CoRR, 2024)

Judging LLMs on a Simplex. - Patrick Vossler; Fan Xia; Yifan Mai 001; Jean Feng (CoRR, 2025)

"Who experiences large model decay and why?" A Hierarchical Framework for Diagnosing Heterogeneous Performance Drift. - Harvineet Singh; Fan Xia; Alexej Gossmann; Andrew Chuang; Julian C. Hong; Jean Feng (CoRR, 2025)

When the Domain Expert Has No Time and the LLM Developer Has No Clinical Expertise: Real-World Lessons from LLM Co-Design in a Safety-Net Hospital. - Avni Kothari; Patrick Vossler; Jean Digitale; Mohammad Forouzannia; Elise Rosenberg; Michele Lee; Jennee Bryant; Melanie Molina; James Marks; Lucas Zier; Jean Feng (CoRR, 2025)