mlsanityData to 14 Oct 2026

Heliophysics Discovery Tools for the 21st Century: Data Science and Machine Learning Structures and Recommendations for 2020-2050

arXiv 2212.13325 ↗First posted 26 Dec 2022astro-ph.IM astro-ph.SR cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

Three main points: 1. Data Science (DS) will be increasingly important to heliophysics; 2. Methods of heliophysics science discovery will continually evolve, requiring the use of learning technologies [e.g., machine learning (ML)] that are applied rigorously and that are capable of supporting discovery; and 3. To grow with the pace of data, technology, and workforce changes, heliophysics requires a new approach to the representation of knowledge.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 2 references that are in the map. First posted on arXiv 26 Dec 2022.

Builds on

1 of 2 references.

References · 1

  1. 2016Theory-guided Data Science: A New Paradigm for Scientific Discovery from Datacited by 171

Built on by

Not cited yet.