Divya Shanmugam
Divya Shanmugam
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Citata da
Citata da
Better aggregation in test-time augmentation
D Shanmugam, D Blalock, G Balakrishnan, J Guttag
Proceedings of the IEEE/CVF international conference on computer visioná…, 2021
When and why test-time augmentation works
D Shanmugam, D Blalock, G Balakrishnan, J Guttag
arXiv preprint arXiv:2011.11156 1 (3), 4, 2020
Unsupervised domain adaptation in the absence of source data
R Sahoo, D Shanmugam, J Guttag
arXiv preprint arXiv:2007.10233, 2020
Learning to limit data collection via scaling laws: A computational interpretation for the legal principle of data minimization
D Shanmugam, F Diaz, S Shabanian, M Finck, A Biega
Proceedings of the 2022 ACM Conference on Fairness, Accountability, andá…, 2022
Data augmentation for electrocardiograms
A Raghu, D Shanmugam, E Pomerantsev, J Guttag, CM Stultz
Conference on Health, Inference, and Learning, 282-310, 2022
Multiple instance learning for ECG risk stratification
D Shanmugam, D Blalock, J Guttag
Machine Learning for Healthcare Conference, 124-139, 2019
Coarse race data conceals disparities in clinical risk score model performance
R Movva, D Shanmugam, K Hou, P Pathak, J Guttag, N Garg, E Pierson
Improved text classification via test-time augmentation
H Lu, D Shanmugam, H Suresh, J Guttag
arXiv preprint arXiv:2206.13607, 2022
Quantifying disparities in intimate partner violence: a machine learning method to correct for underreporting
D Shanmugam, K Hou, E Pierson
npj Women's Health 2 (1), 15, 2024
Kaleidoscope: Semantically-grounded, context-specific ML model evaluation
H Suresh, D Shanmugam, T Chen, AG Bryan, A D'Amour, J Guttag, ...
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systemsá…, 2023
Image segmentation of liver stage malaria infection with spatial uncertainty sampling
AP Soleimany, H Suresh, JJG Ortiz, D Shanmugam, N Gural, J Guttag, ...
arXiv preprint arXiv:1912.00262, 2019
Jiffy: A convolutional approach to learning time series similarity
D Shanmugam, D Blalock, J Guttag
A tale of two time series methods: representation learning for improved distance and risk metrics
D Shanmugam
Massachusetts Institute of Technology, 2018
Use large language models to promote equity
E Pierson, D Shanmugam, R Movva, J Kleinberg, M Agrawal, M Dredze, ...
arXiv preprint arXiv:2312.14804, 2023
An Energy-Based Framework for Arbitrary Label Noise Correction
J Sahota, D Shanmugam, J Ramanan, S Eghbali, M Brubaker
At the Intersection of Conceptual Art and Deep Learning: The End of Signature
KM Lewis, DM Shanmugam, JJG Ortiz, A Kurant, J Guttag
Workshop on Broadening Research Collaborations 2022, 0
Longitudinal changes in sexual desire and attraction among women who started using the Natural Cycles app
J Gassen, S Mengelkoch, D Shanmugam, JT Pearson, ...
Hormones and Behavior 162, 105546, 2024
Machine Learning for Health (ML4H) 2023
S Hegselmann, A Parziale, D Shanmugam, S Tang, K Severson, ...
Machine Learning for Health (ML4H), 1-12, 2023
Machine Learning for Health symposium 2023--Findings track
S Hegselmann, A Parziale, D Shanmugam, S Tang, MN Asiedu, S Chang, ...
arXiv preprint arXiv:2312.00655, 2023
A multi-site study of the relationship between photoperiod and ovulation rate using Natural Cycles data
D Shanmugam, M Espinosa, J Gassen, A van Lamsweerde, JT Pearson, ...
Scientific Reports 13 (1), 8379, 2023
Il sistema al momento non pu˛ eseguire l'operazione. Riprova pi¨ tardi.
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