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Observation impact explanation in atmospheric state estimation using hierarchical message-passing graph neural networksThis paper is significantly revised from an earlier version [] presented at the Explainable Machine Learning for Sciences Workshop (XAI4Sci) in conjunction with the 38th AAAI Conference on Artificial Intelligence (AAAI 2024) held in Vancouver, Canada, in February 2024

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Bibliographic Details
Published in:	Machine learning: science and technology 2024-11, Vol.5 (4)
Main Authors:	Jeon, Hyeon-Ju, Kang, Jeon-ho, Kwon, In-Hyuk, Lee, O-Joun
Format:	Article
Language:	English
Subjects:	explainable weather forecasting forecast sensitivity to observation hierarchical message-passing graph neural networks numerical weather prediction observation impact explanation
Online Access:	Get full text
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