Divya Shanmugam

According to our database, Divya Shanmugam authored at least 20 papers between 2014 and 2024.

Collaborative distances:

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

2024

Learning Disease Progression Models That Capture Health Disparities.

Erica Chiang, Divya Shanmugam, Ashley N. Beecy, Gabriel Sayer, Nir Uriel, Deborah Estrin, Nikhil Garg, Emma Pierson

CoRR, 2024

Generative AI in Medicine.

Divya Shanmugam, Monica Agrawal, Rajiv Movva, Irene Y. Chen, Marzyeh Ghassemi, Maia Jacobs, Emma Pierson

CoRR, 2024

2023

Use large language models to promote equity.

Emma Pierson, Divya Shanmugam, Rajiv Movva, Jon M. Kleinberg, Monica Agrawal, Mark Dredze, Kadija Ferryman, Judy Wawira Gichoya, Dan Jurafsky, Pang Wei Koh, Karen Levy, Sendhil Mullainathan, Ziad Obermeyer, Harini Suresh, Keyon Vafa

CoRR, 2023

Machine Learning for Health symposium 2023 - Findings track.

Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Mercy Nyamewaa Asiedu, Serina Chang, Thomas Hartvigsen, Harvineet Singh

CoRR, 2023

Coarse race data conceals disparities in clinical risk score performance.

Rajiv Movva, Divya Shanmugam, Kaihua Hou, Priya Pathak, John V. Guttag, Nikhil Garg, Emma Pierson

Proceedings of the Machine Learning for Healthcare Conference, 2023

Machine Learning for Health (ML4H) 2023.

Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Kristen Severson, Mercy Nyamewaa Asiedu, Serina Chang, Bonaventure F. P. Dossou, Qian Huang, Fahad Kamran, Haoran Zhang, Sujay Nagaraj, Luis Oala, Shan Xu, Chinasa T. Okolo, Helen Zhou, Jessica Dafflon, Caleb Ellington, Sarah Jabbour, Hyewon Jeong, Harry Reyes Nieva, Yuzhe Yang, Ghada Zamzmi, Vishwali Mhasawade, Van Truong, Payal Chandak, Matthew Lee, Peniel Argaw, Kyle Heuton, Harvineet Singh, Thomas Hartvigsen

Proceedings of the Machine Learning for Health, 2023

Kaleidoscope: Semantically-grounded, context-specific ML model evaluation.

Harini Suresh, Divya Shanmugam, Tiffany Chen, Annie G. Bryan, Alexander D'Amour, John V. Guttag, Arvind Satyanarayan

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

2022

At the Intersection of Deep Learning and Conceptual Art: The End of Signature.

Divya Shanmugam, Katie Lewis, Jose Javier Gonzalez Ortiz, Agnieszka Kurant, John V. Guttag

CoRR, 2022

Improved Text Classification via Test-Time Augmentation.

Helen Lu, Divya Shanmugam, Harini Suresh, John V. Guttag

CoRR, 2022

Learning to Limit Data Collection via Scaling Laws: A Computational Interpretation for the Legal Principle of Data Minimization.

Divya Shanmugam, Fernando Diaz, Samira Shabanian, Michèle Finck, Asia Biega

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Data Augmentation for Electrocardiograms.

Aniruddh Raghu, Divya Shanmugam, Eugene Pomerantsev, John V. Guttag, Collin M. Stultz

Proceedings of the Conference on Health, Inference, and Learning, 2022

2021

Quantifying Inequality in Underreported Medical Conditions.

Divya Shanmugam, Emma Pierson

CoRR, 2021

Learning to Limit Data Collection via Scaling Laws: Data Minimization Compliance in Practice.

Divya Shanmugam, Samira Shabanian, Fernando Diaz, Michèle Finck, Asia Biega

CoRR, 2021

Better Aggregation in Test-Time Augmentation.

Divya Shanmugam, Davis W. Blalock, Guha Balakrishnan, John V. Guttag

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

When and Why Test-Time Augmentation Works.

Divya Shanmugam, Davis W. Blalock, Guha Balakrishnan, John V. Guttag

CoRR, 2020

Unsupervised Domain Adaptation in the Absence of Source Data.

Roshni Sahoo, Divya Shanmugam, John V. Guttag

CoRR, 2020

2019

Image segmentation of liver stage malaria infection with spatial uncertainty sampling.

Ava P. Soleimany, Harini Suresh, Jose Javier Gonzalez Ortiz, Divya Shanmugam, Nil Gural, John V. Guttag, Sangeeta N. Bhatia

CoRR, 2019

Multiple Instance Learning for ECG Risk Stratification.

Divya Shanmugam, Davis W. Blalock, John V. Guttag

Proceedings of the Machine Learning for Healthcare Conference, 2019

2018

Multiple Instance Learning for ECG Risk Stratification.

Divya Shanmugam, Davis W. Blalock, Jen J. Gong, John V. Guttag

CoRR, 2018

2014

Controllability of nonlinear implicit fractional integrodifferential systems.

Krishnan Balachandran, Divya Shanmugam

Int. J. Appl. Math. Comput. Sci., 2014