Publikationen von Markus Reichstein

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)

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)

Lee, H. T.; Jung, M.; Carvalhais, N.; Reichstein, M.; Forkel, M.; Bloom, A. A.; Pacheco-Labrador, J.; Koirala, S.: Spatial attribution of temporal variability in global land-atmosphere CO₂ exchange using a model-data integration framework. ESS Open Archive (2025)

Zhao, W.; Winkler, A.; Reichstein, M.; Orth, R.; Gentine, P.: Learning evaporative fraction with memory. EGUsphere (2025)

Nadolski, L.; El-Madany, T. S.; Nelson, J. A.; Carrara, A.; Moreno, G.; Nair, R. K. F.; Luo, Y.; Hildebrandt, A.; Rolo, V.; Reichstein, M. et al.; Lee, S.-C.: Altered seasonal sensitivity of net ecosystem exchange to controls driven by nutrient balances in a semi-arid savanna. EGUsphere (2024)

Baghirov, Z.; Jung, M.; Reichstein, M.; Körner, M.; Kraft, B.: H2MV (v1.0): Global physically-constrained deep learning water cycle model with vegetation. EGUsphere (2024)

De, R.; Bao, S.; Koirala, S.; Brenning, A.; Reichstein, M.; Tagesson, T.; Liddell, M.; Ibrom, A.; Wolf, S.; Sigut, L. et al.; Hörtnagl, L.; Woodgate, W.; Korkiakoski, M.; Merbold, L.; Black, T. A.; Roland, M. E.; Klosterhalfen, A.; Blanken, P. D.; Knox, S.; Sabbatini, S.; Gielen, B.; Montagnani, L.; Fensholt, R.; Wohlfahrt, G.; Desai, A. R.; Paul-Limoges, E.; Galvagno, M.; Hammerle, A.; Jocher, G.; Reverter, B. R.; Holl, D.; Chen, J.; Vitale, L.; Arain, M. A.; Carvalhais, N.: Addressing challenges in simulating inter-annual variability of gross primary production. ESS Open Archive (2024)