Adarsh Subbaswamy

According to our database, Adarsh Subbaswamy authored at least 19 papers between 2013 and 2024.

Collaborative distances:

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

2024

Scorecards for Synthetic Medical Data Evaluation and Reporting.

Ghada Zamzmi, Adarsh Subbaswamy, Elena Sizikova, Ed Margerrison, Jana G. Delfino, Aldo Badano

CoRR, 2024

A hierarchical decomposition for explaining ML performance discrepancies.

Jean Feng, Harvineet Singh, Fan Xia, Adarsh Subbaswamy, Alexej Gossmann

CoRR, 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

Proceedings of the Causal Learning and Reasoning, 2024

2023

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

2022

A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models.

H. Echo Wang, Matthew Landers, Roy Adams, Adarsh Subbaswamy, Hadi Kharrazi, Darrell J. Gaskin, Suchi Saria

J. Am. Medical Informatics Assoc., 2022

Machine Learning for Health symposium 2022 - Extended Abstract track.

Antonio Parziale, Monica Agrawal, Shalmali Joshi, Irene Y. Chen, Shengpu Tang, Luis Oala, Adarsh Subbaswamy

CoRR, 2022

Machine Learning for Health (ML4H) 2022.

Antonio Parziale, Monica Agrawal, Shengpu Tang, Kristen Severson, Luis Oala, Adarsh Subbaswamy, Sayantan Kumar, Elora D. M. Schörverth, Stefan Hegselmann, Helen Zhou, Ghada Zamzmi, Purity Mugambi, Elena Sizikova, Girmaw Abebe Tadesse, Yuyin Zhou, Taylor W. Killian, Haoran Zhang, Fahad Kamran, Andrea Hobby, Mars Huang, Ahmed M. Alaa, Harvineet Singh, Irene Y. Chen, Shalmali Joshi

Proceedings of the Machine Learning for Health, 2022

2021

Evaluating Model Robustness and Stability to Dataset Shift.

Adarsh Subbaswamy, Roy Adams, Suchi Saria

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Evaluating Model Robustness to Dataset Shift.

Adarsh Subbaswamy, Roy Adams, Suchi Saria

CoRR, 2020

I-SPEC: An End-to-End Framework for Learning Transportable, Shift-Stable Models.

Adarsh Subbaswamy, Suchi Saria

CoRR, 2020

2019

The Hierarchy of Stable Distributions and Operators to Trade Off Stability and Performance.

Adarsh Subbaswamy, Bryant Chen, Suchi Saria

CoRR, 2019

Tutorial: Safe and Reliable Machine Learning.

Suchi Saria, Adarsh Subbaswamy

CoRR, 2019

Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport.

Adarsh Subbaswamy, Peter Schulam, Suchi Saria

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Learning Predictive Models That Transport.

Adarsh Subbaswamy, Peter Schulam, Suchi Saria

CoRR, 2018

Counterfactual Normalization: Proactively Addressing Dataset Shift and Improving Reliability Using Causal Mechanisms.

Adarsh Subbaswamy, Suchi Saria

CoRR, 2018

Counterfactual Normalization: Proactively Addressing Dataset Shift Using Causal Mechanisms.

Adarsh Subbaswamy, Suchi Saria

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

2017

Treatment-Response Models for Counterfactual Reasoning with Continuous-time, Continuous-valued Interventions.

Hossein Soleimani, Adarsh Subbaswamy, Suchi Saria

CoRR, 2017

Learning Treatment-Response Models from Multivariate Longitudinal Data.

Hossein Soleimani, Adarsh Subbaswamy, Suchi Saria

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

2013

Non-Intrusive Occupancy Monitoring using Smart Meters.

Dong Chen, Sean Kenneth Barker, Adarsh Subbaswamy, David E. Irwin, Prashant J. Shenoy

Proceedings of the BuildSys 2013, 2013