Publikationen von Markus Reichstein

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)

Reichstein, M.: How can artificial intelligence enhance our understanding of the earth system? (2020)

Paulus, S.; El-Madany, T. S.; Wutzler, T.; Carrara, A.; Moreno, G. M.; Reichstein, M.; Orth, R.; Hertel, M.; López-Jimenez, R.; Migliavacca, M.: High-resolution large weighing lysimeter measurements with meteorological and soil-hydrological variables from a Mediterranean Savanna. (2022)

Han, B.; Zhang, S.; Shi, X.; Reichstein, M.: Bridging remote sensors with multisensor geospatial foundation models. (2024)

Reichstein, M.; Benson, V.; Camps-Valls, G.; Boran, H.; Fearnley, C.; Kornhuber, K.; Rahaman, N.; Schöllkopf, B.; Tárraga, J. M.; Vinuesa, R. et al.; Blunk, J.; Dall, K.; Denzler, J.; Frank, D.; Martini, G.; Nganga, N.; Robinson, D. M.: Early warning of complex climate risk with integrated artificial intelligence. (2024)

Liu, G.; Migliavacca, M.; Reimers, C.; Kraft, B.; Reichstein, M.; Richardson, A.; Wingate, L.; Delpierre, N.; Yang, H.; Winkler, A.: DeepPhenoMem V1.0: Deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology. (2024)

Cohrs, K.-H.; Varando, G.; Camps-Valls, G.; Carvalhais, N.; Reichstein, M.: Double machine learning for causal hybrid modeling - applications in the earth sciences. (2024)

Nelson, J. A.; Walther, S.; Gans, F.; Kraft, B.; Weber, U.; Novick, K.; Buchmann, N.; Migliavacca, M.; Wohlfahrt, G.; Šigut, L. et al.; Ibrom, A.; Papale, D.; Göckede, M.; Duveiller, G.; Knohl, A.; Hörtnagl, L.; Scott, R. L.; Zhang, W.; Hamdi, Z. M.; Reichstein, M.; Aranda-Barranco, S.; Ardö, J.; de Beeck, M. O.; Billdesbach, D.; Bowling, D.; Bracho, R.; Brümmer, C.; Camps-Valls, G.; Chen, S.; Cleverly, J. R.; Desai, A.; Dong, G.; El-Madany, T. S.; Euskirchen, E. S.; Feigenwinter, I.; Galvagno, M.; Gerosa, G.; Gielen, B.; Goded, I.; Goslee, S.; Gough, C. M.; Heinesch, B.; Ichii, K.; Jackowicz-Korczynski, M. A.; Klosterhalfen, A.; Knox, S.; Kobayashi, H.; Kohonen, K.-M.; Korkiakoski, M.; Mammarella, I.; Mana, G.; Marzuoli, R.; Matamala, R.; Metzger, S.; Montagnani, L.; Nicolini, G.; O'Halloran, T.; Ourcival, J.-M.; Peichl, M.; Pendall, E.; Reverter, B. R.; Roland, M.; Sabbatini, S.; Sachs, T.; Schmidt, M.; Schwalm, C. R.; Shekhar, A.; Silberstein, R.; Silveira, M. L.; Spano, D.; Tagesson, T.; Tramontana, G.; Trotta, C.; Turco, F.; Vesala, T.; Vincke, C.; Vitale, D.; Vivoni, E. R.; Wang, Y.; Woodgate, W.; Yepez, E. A.; Zhang, J.; Zona, D.; Jung, M.: X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X. (2024)

Poehls, J.; Silva, L. A.; Koirala, S.; Carvalhais, N.; Reichstein, M.: Downscaling soil moisture to sub-km resolutions with simple machine learning ensembles. (2024)

Zhan, C.; Orth, R.; Yang, H.; Reichstein, M.; Zaehle, S.; De Kauwe, M. G.; Rammig, A.; Winkler, A.: Estimating the CO₂ fertilization effect on extratropical forest productivity from Flux-tower observations. (2023)