Michael S. Yao

According to our database, Michael S. Yao authored at least 9 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization.

Michael S. Yao, James C. Gee, Osbert Bastani

CoRR, January, 2025

2024

Evidence Is All You Need: Ordering Imaging Studies via Language Model Alignment with the ACR Appropriateness Criteria.

Michael S. Yao, Allison Chae, Charles E. Kahn Jr., Walter R. Witschey, James C. Gee, Hersh Sagreiya, Osbert Bastani

CoRR, 2024

A Concept-based Interpretable Model for the Diagnosis of Choroid Neoplasias using Multimodal Data.

Yifan Wu, Yang Liu, Yue Yang, Michael S. Yao, Wenli Yang, Xuehui Shi, Lihong Yang, Dongjun Li, Yueming Liu, James C. Gee, Xuan Yang, Wenbin Wei, Shi Gu

CoRR, 2024

Generative Adversarial Bayesian Optimization for Surrogate Objectives.

Michael S. Yao, Yimeng Zeng, Hamsa Bastani, Jacob R. Gardner, James C. Gee, Osbert Bastani

CoRR, 2024

Generative Adversarial Model-Based Optimization via Source Critic Regularization.

Michael S. Yao, Yimeng Zeng, Hamsa Bastani, Jacob R. Gardner, James C. Gee, Osbert Bastani

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis.

Yue Yang, Mona Gandhi, Yufei Wang, Yifan Wu, Michael S. Yao, Chris Callison-Burch, James C. Gee, Mark Yatskar

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

SynthA1c: Towards Clinically Interpretable Patient Representations for Diabetes Risk Stratification.

Michael S. Yao, Allison Chae, Matthew T. MacLean, Anurag Verma, Jeffrey T. Duda, James C. Gee, Drew A. Torigian, Daniel J. Rader, Charles E. Kahn, Walter R. Witschey, Hersh Sagreiya

Proceedings of the Predictive Intelligence in Medicine - 6th International Workshop, 2023

2022

Learning-Based Radiomic Prediction of Type 2 Diabetes Mellitus Using Image-Derived Phenotypes.

Michael S. Yao, Allison Chae, Matthew T. MacLean, Anurag Verma, Jeffrey T. Duda, James C. Gee, Drew A. Torigian, Daniel J. Rader, Charles E. Kahn, Walter R. Witschey, Hersh Sagreiya

CoRR, 2022

A Path Towards Clinical Adaptation of Accelerated MRI.

Michael S. Yao, Michael S. Hansen

Proceedings of the Machine Learning for Health, 2022