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Kraft, B.; Besnard, S.; Koirala, S.: Emulating ecological memory with recurrent neural networks. In: Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences, pp. 269 - 281 (Eds. Camps-Valls, G.; Tuia, D.; Zhu, X. X.; Reichstein, M.). John Wiley & Sons Ltd, Hoboken, New Jersey (2021)

Mateo-García, G.; Laparra, V.; Requena Mesa, C.; Gómez-Chova, L.: Generative adversarial networks in the Geosciences. In: Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences, pp. 24 - 36 (Eds. Camps-Valls, G.; Tuia, D.; Zhu, X. X.; Reichstein, M.). John Wiley & Sons Ltd, Hoboken, New Jersey (2021)

Reichstein, M.; Camps-Valls, G.; Tuia, D.; Zhu, X. X.: Outlook. In: Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences, pp. 328 - 330 (Eds. Camps-Valls, G.; Tuia, D.; Zhu, X. X.; Reichstein, M.). John Wiley & Sons Ltd, Hoboken, New Jersey (2021)

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

Kolle, O.; Kalthoff, N.; Kottmeier, C.; Munger, J. W.: Ground-based platforms. In: Handbook of Atmospheric Measurements, pp. 155 - 182 (Ed. Foken, T.). Springer, Cham (2021)

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Gottfriedsen, J.; Berrendorf, M.; Gentine, P.; Hassler, B.; Reichstein, M.; Weigel, K.; Eyring, V.: On the generalization of agricultural drought classification from climate data. In: NeurIPS 2021. Workshop - Tackling Climate Change with Machine Learning On the Generalization of ML-based Agricultural Drought Classification from Climate Date, 2021. (2021)

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Requena Mesa, C.; Benson, V.; Reichstein, M.; Runge, J.; Denzler, J.: EarthNet2021: A large-scale dataset and challenge for Earth surface forecasting as a guided video prediction task. In: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW, Nashville, TN, USA , June 19, 2021 - June 25, 2021. IEEE, Nashville, TN, USA (2021)

Adsuara, J. E.; Perez-Suay, A.; Moreno-Martınez, A.; Camps-Valls, G.; Kraemer, G.; Reichstein, M.; Mahecha, M. D.: Discovering differential equations from earth observation data. In: IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, pp. 3999 - 4002. IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, September 26, 2020 - October 02, 2020. IEEE (2021)

Trumbore, S. E.; Barros, A. P.; Becker, T. W.; Davidson, E. A.; Ehlmann, B. L.; Gruber, N.; Hofmann, E.; Hudson, M. K.; Illangasekare, T. H.; Kang, S. et al.; Malanotte-Rizzoli, P.; Montanari, A.; Nimmo, F.; Parsons, T.; Salters, V. J. M.; Schimel, D.; Stevens, B.; Wuebbles, D. J.; Zeitler, P.; Zhu, T.: Thank you to our 2020 peer reviewers, AGU Advances 2, (2021)

Ramirez, J. A.; Craven, D.; Posada, J. M.; Reu, B.; Sierra, C. A.; Hoch, G.; Handa, I. T.; Messier, C.: Non-structural carbohydrate concentrations in woody organs, but not leaves, of temperate and tropical tree angiosperms are independent of the ‘fast-slow’ plant economic spectrum. (2021)