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