Sub-seasonal to seasonal forecasts through self-supervised learning (Proposals Track)

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Sub-seasonal to seasonal forecasts through self-supervised learning (Proposals Track)

Author: Thuemmel, Jannik; Strnad, Felix; Schlör, Jakob; Butz, Martin V.; Goswami, Bedartha
Tübinger Autor(en):
Thümmel, Jannik
Schlör, Jakob
Butz, Martin V.
Goswami, Bedartha
Published in: ICLR 2023 Workshop on Tackling Climate Change with Machine Learning (2023), Bd.
Verlagsangabe: Climate Change AI
Language: English
Full text: https://www.climatechange.ai/papers/iclr2023/37
DDC Classifikation: 004 - Data processing and computer science
Dokumentart: Article
ConferenceObject
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