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Bio
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 25 篇Author StatisticsCo-AuthorSimilar Experts
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Björn Lütjens, Noelle Selin,Andre Souza, Gosha Geogdzhayev,Dava Newman, Paolo Giani,Claudia Tebaldi,Duncan Watson-Parris,Raffaele Ferrari
crossref(2024)
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)
crossref(2023)
arXiv (Cornell University) (2023)
AAAI Conference on Artificial Intelligenceno. 11 (2022): 12119-12125
crossref(2022)
Salva Rühling Cachay, Emma Erickson,Arthur Fender C. Bucker,Ernest Pokropek,Willa Potosnak, Suyash Bire,Salomey Osei,Björn Lütjens
ArXiv (2021)
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