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I am concerned that running a high-resolution (1km) climate model can take multiple weeks on the world's largest supercomputers; consuming the same electricity a coal power plant would generate in one hour. To overcome the computational complexity, we are reshaping machine learning models into fast copies, or 'surrogates', of climate models. The core difficulty is to ensure physical-consistency in the surrogates, such that policy- or decision-makers can trust the machine learning surrogates.
Research Interests
Papers共 28 篇Author StatisticsCo-AuthorSimilar Experts
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arxiv(2024)
Cited0Views0Bibtex
0
0
Björn Lütjens, Noelle Selin,Andre Souza, Gosha Geogdzhayev,Dava Newman, Paolo Giani,Claudia Tebaldi,Duncan Watson-Parris,Raffaele Ferrari
crossref(2024)
Sungduk Yu, Zeyuan Hu,Akshay Subramaniam,Walter Hannah,Liran Peng,Jerry Lin,Mohamed Aziz Bhouri,Ritwik Gupta,Björn Lütjens, Justus C. Will,Gunnar Behrens,Julius J. M. Busecke,
arxiv(2023)
Cited10Views0Bibtex
10
0
Björn Lütjens,Brandon Leshchinskiy,Christian Requena-Mesa,Farrukh Chishtie,Natalia Díaz-Rodríguez,Océane Boulais,Aruna Sankaranarayanan, Margaux Masson-Forsythe, Aaron Piña,Yarin Gal,Chedy Raïssi,Alexander Lavin,
CoRR (2023)
Björn Lütjens,Patrick Alexander,Raf Antwerpen, Guido Cervone, Matthew Kearney, Bingkun Luo,Dava Newman,Marco Tedesco
crossref(2023)
arXiv (Cornell University) (2023)
crossref(2023)
CoRR (2023)
Cited0Views0EIBibtex
0
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AAAI Conference on Artificial Intelligenceno. 11 (2022): 12119-12125
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Author Statistics
#Papers: 28
#Citation: 260
H-Index: 6
G-Index: 16
Sociability: 5
Diversity: 0
Activity: 1
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