Uncertainty quantification with approximate variational learning for wearable photoplethysmography prediction tasks

Bench C., Desai V., Moulaeifard M., Strodthoff N., Aston P., Thompson A.
Keywords:

Monte Carlo dropout, uncertainty quantification, photoplethysmography, PPG, deep learning, Improved Variational Online Newton

Document type Article
Journal title / Source Machine Learning: Health
Volume 1
Issue 1
Page numbers / Article number 015013
Publisher's name IOP Publishing
Publisher's address (city only) Bristol, United Kingdom
Publication date 2025-1-1
ISSN 3049-477X
DOI 10.1088/3049-477X/ae0b74

Back to the list view

Information

Name of Call / Funding Programme
Metrology Partnership 2022: Health