León, E https://orcid.org/0000-0002-0073-5512
Li, A https://orcid.org/0000-0002-4844-9339
Bahena Schott, M A https://orcid.org/0000-0001-7892-8691
Bos, B https://orcid.org/0009-0008-5828-1745
Busch, M https://orcid.org/0009-0002-9336-3937
Chapman, J R https://orcid.org/0009-0004-9815-2981
Duran, G L https://orcid.org/0009-0001-3047-478X
Gruszko, J https://orcid.org/0000-0002-3777-2237
Henning, R https://orcid.org/0000-0001-8651-2960
Martin, E L https://orcid.org/0000-0002-5008-1596
Wilkerson, J F https://orcid.org/0000-0002-0342-0217
Funding for this research was provided by:
Nuclear Physics Program of the National Science Foundation (PHY- 1812374)
Department of Energy, Office of Science, Office of Nuclear Physics (DE-FG02- 97ER41041)
Article Title: Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines
Journal Title: Machine Learning: Science and Technology
Article Type: paper
Copyright Information: © 2025 The Author(s). Published by IOP Publishing Ltd
Publication dates
Date Received: 2024-11-15
Date Accepted: 2025-02-27
Online publication date: 2025-03-17