Publikationen von M. Reichstein

Subke, J.-A.; Heinemeyer, A.; Reichstein, M.: Experimental design: scaling up in time and space, and its statistical considerations. In: Soil Carbon Dynamics - an Integrated Methodology, S. 34 - 48 (Hg. Kutsch, W.; Bahn, M.; Heinemeyer, A.). Cambridge Univ. Press, Cambridge (2009)

Reichstein, M.: Impact of climate change on forest soil carbon - Principles, Factors, Models, Uncertainties. In: Forestry and climate change, S. 127 - 135 (Hg. Freer-Smith, P. H.; Broadmeadow, M. S. J.; Lynch, J. M.). CABI Publ., Wallingford (2007)

Reichstein, M.; Tenhunen, J.; Berbigier, P.; Magliulo, E.; Miglietta, F.; Ourcival, J.-M.; Pecchiari, M.; Peressotti, A.; Rambal, S.; Valentini, R. et al.; Vitullo, M.: Mediterranean ecosystem carbon and water exchange in response to drought: monospecific evergreen forest versus multi-species macchia. In: Funktionelle Bedeutung von Biodiversität, S. 154 - 154. Parey, Berlin (2001)

Benson, V.; Robin, C.; Requena Mesa, C.; Alonso, L.; Carvalhais, N.; Cortés, J.; Gao, Z.; Linscheid, N.; Weynants, M.; Reichstein, M.: Multi-modal learning for geospatial vegetation forecasting. In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle , 17. Juni 2024 - 21. Juni 2024. (2024)

Voigt, H.; Carvalhais, N.; Meuschke, M.; Reichstein, M.; Zarrie, S.; Lawonn, K.: VIST5: An adaptive, retrieval-augmented language model for visualization-oriented dialog. In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, S. 70 - 81. The 2023 Conference on Empirical Methods in Natural Language Processing, Singapure, 06. Dezember 2023 - 10. Dezember 2023. Association for Computational Linguistics, Singapur (2023)

Sillmann, J.; Christensen, I.; Hochrainer-Stigler, S.; Huang-Lachmann, J.-T.; Juhola, S.; Kornhuber, K.; Mahecha, M. D.; Mechler, R.; Reichstein, M.; Ruane, A. C. et al.; Schweizer, P.-J.; Williams, S.: Briefing note on systemic risk. International Science Council, S. 1 - 35 (2022)

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)

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 , 19. Juni 2021 - 25. Juni 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, S. 3999 - 4002. IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, 26. September 2020 - 02. Oktober 2020. IEEE (2021)

Camps-Valls, G.; Reichstein, M.; Zhu, X.; Tuia, D.: Advancing deep learning for earth sciences: From hybrid modeling to interpretability. In: IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, S. 3979 - 3982. IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, ELECTR NETWORK, 26. September 2020 - 02. Oktober 2020. (2020)

Le Toan, T.; Chave, J.; Dall, J.; Papathanassiou, K.; Paillou, P.; Reichstein, M.; Quegan, S.; Saatchi, S.; Scipal, K.; Shugart, H. et al.; Tebaldini, S.; Ulander, L.; Williams, M.: The biomass mission: Objectives and requirements. In: IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, S. 8563 - 8566. (2018)

García, Y. G.; Shadaydeh, M.; Mahecha, M. D.; Reichstein, M.; Denzler, J.: BACI: Towards a biosphere atmosphere change index - Detection of extreme events in the biosphere. In: BigSkyEarth conference: AstroGeoInformatics, S. 1 - 6. BigSkyEarth conference: AstroGeoInformatics, Tenerife, Spain, 17. Dezember 2018 - 19. Dezember 2018. (2018)

Martini, D.; Pacheco-Labrador, J.; Perez‑Priego, O.; van der Tol, C.; El-Madany, T. S.; Julitta, T.; Rossini, M.; Gitelson, A.; Reichstein, M.; Migliavacca, M.: Photosynthesis-sun induced fluorescence relationship in a mediterranean grassland. In: IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Bd. 4, S. 5979 - 5982. International Geoscience and Remote Sensing Symposium (IGARSS) , Valencia, Spain, 11. Juli 2018 - 27. Juli 2018. Institute of Electrical and Electronics Engineers Inc. (2018)

Pacheco-Labrador, J.; Carvalhais, N.; Perez-Priego, O.; El-Madany, T. S.; Rossini, M.; Julitta, T.; Moreno, G.; González-Cascón, R.; Martín, M. P.; Reichstein, M. et al.; Carrara, A.; Guanter, L.; Migliavacca, M.: Assessing the use of multiple constraints and ancillary data to support scope model inversion in a experimental grassland. In: IEEE International Geoscience and Remote Sensing Symposium, IGARSS, S. 5975 - 5978. International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, 22. Juli 2018 - 27. Juli 2018. Institute of Electrical and Electronics Engineers Inc. (2018)

Reichstein, M.; Besnard, S.; Carvalhais, N.; Gans, F.; Jung, M.; Kraft, B.; Mahecha, M. D.: Modelling landsurface time-series with recurrent neural nets. In: 2018 IEEE International geoscience and remote sensing symposium (IGARSS), S. 7640 - 7643. Valencia, 2018 (2018)

Requena-Mesa, C.; Reichstein, M.; Mahecha, M. D.; Kraft, B.; Denzler, J.: Predicting landscapes as seen from space from environmental conditions. In: 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), S. 1768 - 1771. (2018)

Shadaydeh, M.; Garcia, Y. G.; Mahecha, M. D.; Reichstein, M.; Denzler, J.: Causality analysis of ecological time series: a time-frequency approach. In: 8th International Workshop on Climate Informatics: CI 2018, S. 111 - 114 (Hg. Chen, C.; Cooley, D.; Runge, J.; Szekely, E.). 8th International Workshop on Climate Informatics: CI 2018, Boulder, Colorado, 19. September 2018 - 21. September 2019. (2018)

Rodner, E.; Barz, B.; Guanche, Y.; Flach, M.; Mahecha, M. D.; Bodesheim, P.; Reichstein, M.; Denzler, J.: Maximally divergent intervals for anomaly detection. In: ICML 2016 Anomaly Detection Workshop. ICML 2016 Anomaly Detection Workshop, New York (USA), 19. Juni 2016 - 24. Juni 2016. (2016)

Camps-Valls, G.; Jung, M.; Ichii, K.; Papale, D.; Tramontana, G.; Bodesheim, P.; Schwalm, C.; Zscheischler, J.; Mahecha, M. D.; Reichstein, M.: Ranking drivers of global carbon and energy fluxes over land. In: IEEE International Symposium on Geoscience and Remote Sensing IGARSS, S. 4416 - 4419. (2015)

Shan, H.; Kattge, J.; Reich, P.; Banerjee, A.; Schrodt, F.; Reichstein, M.: Gap filling in the plant kingdom - Trait prediction using hierarchical probabilistic matrix factorization. In: Proceedings of the International Conference for Machine Learning (ICML), Bd. 2, S. 1303 - 1310 (Hg. Langford, J.). International Conference on Machine Learning, Edinburgh (2012)