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Book Chapter

Spatio-temporal Autoencoders in Weather and Climate Research

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Requena Mesa,  Christian
Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Prof. Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;
IMPRS International Max Planck Research School for Global Biogeochemical Cycles, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Tibau, X.-A., Reimers, C., Requena Mesa, C., & Runge, J. (2021). Spatio-temporal Autoencoders in Weather and Climate Research. In G. Camps-Valls, D. Tuia, X. X. Zhu, & M. Reichstein (Eds.), Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences (pp. 186-203). Hoboken, New Jersey: John Wiley & Sons Ltd.


Cite as: https://hdl.handle.net/21.11116/0000-0009-94CD-9
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