A complete list of all publications from the Department of Biogeochemical Integration

Book Chapter (6)

81.
Book Chapter
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)
82.
Book Chapter
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)
83.
Book Chapter
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)
84.
Book Chapter
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)
85.
Book Chapter
Reimers, C.; Bodesheim, P.; Runge, J.; Denzler, J.: Conditional adversarial debiasing: Towards learning unbiased classifiers from biased data. In: Pattern Recognition. DAGM GCPR 2021. Lecture Notes in Computer Science, Vol. 13024, pp. 48 - 62. Springer International Publishing, Cham (2021)

Conference Paper (4)

86.
Conference Paper
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)
87.
Conference Paper
Körschens, M.; Bodesheim, P.; Römermann, C.; Bucher, S. F.; Migliavacca, M.; Ulrich, J.; Denzler, J.: Automatic plant cover estimation with convolutional neural networks. In: GI-Edition: lecture notes in informatics. Proceedings. Informatik 2021 : computer science & sustainability, Berlin / Gesellschaft für Informatik e.V. (GI) (Hrsg.) , September 27, 2021 - October 01, 2021. Ges. für Informatik, Bonn (2021)
88.
Conference Paper
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)
89.
Conference Paper
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)
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