Kronberg, Elena A. https://orcid.org/0000-0001-7741-682X
Gastaldello, Fabio https://orcid.org/0000-0002-9112-0184
Haaland, Stein https://orcid.org/0000-0002-1241-7570
Smirnov, Artem https://orcid.org/0000-0003-3689-4336
Berrendorf, Max https://orcid.org/0000-0001-9724-4009
Ghizzardi, Simona https://orcid.org/0000-0003-0879-7328
Kuntz, K. D. https://orcid.org/0000-0001-6654-5378
Sivadas, Nithin https://orcid.org/0000-0003-4278-0482
Allen, Robert C. https://orcid.org/0000-0003-2079-5683
Tiengo, Andrea https://orcid.org/0000-0002-6038-1090
Ilie, Raluca https://orcid.org/0000-0002-7305-2579
Huang, Yu https://orcid.org/0000-0001-5023-0427
Kistler, Lynn https://orcid.org/0000-0002-8240-5559
Funding for this research was provided by:
German Research Foundation (KR 4375/2-1)
NASA Earth and Space Science Grant (80NSSC17K0433)
Article Title: Prediction and Understanding of Soft-proton Contamination in XMM-Newton: A Machine Learning Approach
Journal Title: The Astrophysical Journal
Article Type: paper
Copyright Information: © 2020. The American Astronomical Society. All rights reserved.
Publication dates
Date Received: 2020-05-28
Date Accepted: 2020-09-23
Online publication date: 2020-11-06