Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations
Abstract
The authors of this white paper met on 16-17 January 2020 at the New Jersey Institute of Technology, Newark, NJ, for a 2-day workshop that brought together a group of heliophysicists, data providers, expert modelers, and computer/data scientists. Their objective was to discuss critical developments and prospects of the application of machine and/or deep learning techniques for data analysis, modeling and forecasting in Heliophysics, and to shape a strategy for further developments in the field. The workshop combined a set of plenary sessions featuring invited introductory talks interleaved with a set of open discussion sessions. The outcome of the discussion is encapsulated in this white paper that also features a top-level list of recommendations agreed by participants.
- Publication:
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arXiv e-prints
- Pub Date:
- June 2020
- DOI:
- arXiv:
- arXiv:2006.12224
- Bibcode:
- 2020arXiv200612224N
- Keywords:
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- Astrophysics - Solar and Stellar Astrophysics;
- Astrophysics - Instrumentation and Methods for Astrophysics;
- Computer Science - Machine Learning
- E-Print:
- Workshop Report