Machine Learning for Clouds and Climate (Invited Chapter for the AGU Geophysical Monograph Series "Clouds and Climate")-Reference-Cited by-同舟云学术

Machine Learning for Clouds and Climate (Invited Chapter for the AGU Geophysical Monograph Series "Clouds and Climate")

Published:2021-05-03 Issue: Volume: Page:
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Author:

Beucler Tom¹²^ORCID,Ebert-Uphoff Imme³⁴,Rasp Stephan⁵⁶,Pritchard Michael⁷,Gentine Pierre⁸

Affiliation:

1. University of Lausanne

2. University of California, Irvine

3. Cooperative Institute for Research in the Atmosphere

4. Colorado State University

5. ClimateAi

6. Inc

7. University of California

8. Columbia University

Funder

National Science Foundation

U.S. Department of Energy

European Research Council

Publisher

Wiley

Reference197 articles.

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3. Bansal N. Agarwal C. & Nguyen A. (2020). Sam: The sensitivity of attribution methods to hyperparameters. In Proceedings of the ieee/cvf conference on computer vision and pattern recognition (pp. 8673-8683).

4. Viewing forced climate patterns through an ai lens;Barnes E. A.;Geophysical Research Letters,2019

5. August). Tropospheric and stratospheric causal pathways between the MJO and NAO;Barnes E. A.;J. Geophys. Res. D: Atmos.,2019

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