Ćiprijanović, A https://orcid.org/0000-0003-1281-7192
Lewis, A https://orcid.org/0000-0003-3734-335X
Pedro, K https://orcid.org/0000-0003-2260-9151
Madireddy, S https://orcid.org/0000-0002-0437-8655
Nord, B https://orcid.org/0000-0001-6706-8972
Perdue, G N https://orcid.org/0000-0001-6785-8720
Wild, S M https://orcid.org/0000-0002-6099-2772
Funding for this research was provided by:
U.S. Department of Energy (DE-AC02-06CH11357)
Article Title: DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection
Journal Title: Machine Learning: Science and Technology
Article Type: paper
Copyright Information: © 2023 The Author(s). Published by IOP Publishing Ltd
Publication dates
Date Received: 2023-02-03
Date Accepted: 2023-04-04
Online publication date: 2023-04-25