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  • Presentation | SH43C: Advances in Understanding the Innermost Heliosphere IV Poster
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  • SH43C-2604: A Machine Learning Approach to Surveying Solar Energetic Particle Time Profiles in Parker Solar Probe EPI-Hi HET Data
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  • Board 2604‚ Hall EFG (Poster Hall)
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Author(s):
Allan Labrador, California Institute of Technology (First Author, Presenting Author)
Ashish Mahabal, California Institute of Technology
Eric Christian, NASA GSFC
Christina Cohen, Caltech
Richard Leske, Caltech
David McComas, Princeton University
J. Grant Mitchell, NASA Goddard Space Flight Center
Gabriel Muro, Caltech
Sungmin Pak, University of Nevada, Las Vegas
Jamie Rankin, Princeton University
Nathan Schwadron, University of New Hampshire
Mark Wiedenbeck, Jet Propulsion Laboratory, California Institute of Technology
Zigong Xu, California Institute of Technology


We apply machine learning techniques to surveying SEP event decay phases in Parker Solar Probe EPI-Hi data. These techniques were previously developed and applied to ACE/SIS and STEREO/LET data.



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