mlsanityData to 14 Oct 2026

Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations

arXiv 2006.12224 ↗First posted 22 Jun 2020astro-ph.SR astro-ph.IM cs.LGcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Jun 2020.

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Citing papers per year: 2025: 1; 2026: 1.

2 papers.