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Title:

ResoNet: Robust and Explainable ENSO Forecasts with Hybrid Convolution and Transformer Networks

Document type:
Zeitschriftenaufsatz
Author(s):
Lyu, Pumeng; Tang, Tao; Ling, Fenghua; Luo, Jing-Jia; Boers, Niklas; Ouyang, Wanli; Bai, Lei
Journal title:
Advances in Atmospheric Sciences
Year:
2024
Journal volume:
41
Journal issue:
7
Pages contribution:
1289-1298
Fulltext / DOI:
doi:10.1007/s00376-024-3316-6
Publisher:
Springer Science and Business Media LLC
E-ISSN:
0256-15301861-9533
Date of publication:
22.06.2024
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