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

arXiv: https://arxiv.org/abs/2006.12224 · HTML: https://mlsanity.com/paper/2006.12224/

## Key facts

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

## Built on by (most cited first, 2 of 2)

- [Surya: Foundation Model for Heliophysics](https://mlsanity.com/paper/2508.14112/) (2025)
- [Review of Machine Learning Models for Solar Energetic Particle Prediction](https://mlsanity.com/paper/2606.19539/) (2026)

## 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.