Opportunities & Challenges of AI/ML: Trends from the Space Weather Perspective
presentation
posted on 2021-02-19, 18:12 authored by Ryan McGranaghanRyan McGranaghan, Barbara Thompson, Matthew Argall, Hazel Bain, Jacob Bortnik, Viacheslav SadykovA look at the trends and opportunities for artificial intelligence and machine learning in the space and Earth sciences. This was presented at the 2021 Earth Science Information Partners (ESIP) Winter Meeting held virtually in January 2021.
Funding
NSF Award Number: 1937152
NSF Award Number: 1940208
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- Mesospheric, thermospheric, ionospheric and magnetospheric physics
- Solar system planetary science (excl. planetary geology)
- Space sciences not elsewhere classified
- Solar physics
- Geophysics not elsewhere classified
- Artificial intelligence not elsewhere classified
- Information modelling, management and ontologies
- Information systems not elsewhere classified
- Organisation of information and knowledge resources
- Pattern recognition
- Data mining and knowledge discovery
- Applied computing not elsewhere classified
Keywords
space weatherHeliophysicsmachine learningartificial intelligenceknowledge graphsrepresentation theoryEarth Science Informatics PartnersMesospheric, Ionospheric and Magnetospheric PhysicsSolar System, Solar Physics, Planets and ExoplanetsSpace ScienceSpace and Solar PhysicsGeophysicsArtificial Intelligence and Image ProcessingConceptual ModellingInformation SystemsOrganisation of Information and Knowledge ResourcesPattern Recognition and Data MiningApplied Computer Science
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