Publikationen von Markus Reichstein

Vitus Benson, Claire Robin, Christian Requena Mesa, Lazaro Alonso, Nuno Carvalhais, José Cortés, Zhihan Gao, Nora Linscheid, Melanie Weynants, and Markus Reichstein, "Multi-modal learning for geospatial vegetation forecasting", in 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), (2024).

Henrik Voigt, Nuno Carvalhais, Monique Meuschke, Markus Reichstein, Sina Zarrie, and Kai Lawonn, "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, (Association for Computational Linguistics, Singapur, 2023), pp. 70-81.

Jana Sillmann, Ingrid Christensen, Stefan Hochrainer-Stigler, Jo-Ting Huang-Lachmann, Sirkku Juhola, Kai Kornhuber, Miguel D. Mahecha, Reinhard Mechler, Markus Reichstein, Alex C. Ruane, Pia-Johanna Schweizer, and Scott Williams, "Briefing note on systemic risk", in International Science Council, (2022), pp. 1-35.

Julia Gottfriedsen, Max Berrendorf, Pierre Gentine, Birgit Hassler, Markus Reichstein, Katja Weigel, and Veronika Eyring, "On the generalization of agricultural drought classification from climate data", in NeurIPS 2021, (2021).

Christian Requena Mesa, Vitus Benson, Markus Reichstein, Jakob Runge, and Joachim Denzler, "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), (IEEE, Nashville, TN, USA, 2021).

Jose E. Adsuara, Adrian Perez-Suay, Alvaro Moreno-Martınez, Gustau Camps-Valls, Guido Kraemer, Markus Reichstein, and Miguel D. Mahecha, "Discovering differential equations from earth observation data", in IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, (IEEE, 2021), pp. 3999-4002.

Gustau Camps-Valls, Markus Reichstein, Xiaoxiang Zhu, and Devis Tuia, "Advancing deep learning for earth sciences: From hybrid modeling to interpretability", in IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, (2020), pp. 3979-3982.

Thuy Le Toan, Jerome Chave, Jorgen Dall, Kostas Papathanassiou, Philippe Paillou, Markus Reichstein, Shaun Quegan, Sassan Saatchi, Klaus Scipal, Hank Shugart, Stefano Tebaldini, Lars Ulander, and Mathew Williams, "The biomass mission: Objectives and requirements", in IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, (2018), pp. 8563-8566.

Yanira Guanche García, Maha Shadaydeh, Miguel D. Mahecha, Markus Reichstein, and Joachim Denzler, "BACI: Towards a biosphere atmosphere change index - Detection of extreme events in the biosphere", in BigSkyEarth conference: AstroGeoInformatics, (2018), pp. 1-6.

David Martini, Javier Pacheco-Labrador, Oscar Perez‑Priego, Christiaan van der Tol, Tarek S. El-Madany, Tommaso Julitta, Micol Rossini, Anatoly Gitelson, Markus Reichstein, and Mirco Migliavacca, "Photosynthesis-sun induced fluorescence relationship in a mediterranean grassland", in IEEE International Geoscience and Remote Sensing Symposium, IGARSS, (Institute of Electrical and Electronics Engineers Inc., 2018), Vol. 4, pp. 5979-5982.

Javier Pacheco-Labrador, Nuno Carvalhais, Oscar Perez-Priego, Tarek S. El-Madany, Micol Rossini, Tommaso Julitta, Gerardo Moreno, Rosario González-Cascón, M. Pilar Martín, Markus Reichstein, Arnaud Carrara, Luis Guanter, and Mirco Migliavacca, "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, (Institute of Electrical and Electronics Engineers Inc., 2018), pp. 5975-5978.

Markus Reichstein, Simon Besnard, Nuno Carvalhais, Fabian Gans, Martin Jung, Basil Kraft, and Miguel D. Mahecha, "Modelling landsurface time-series with recurrent neural nets", in 2018 IEEE International geoscience and remote sensing symposium (IGARSS), (Valencia, 2018, 2018), pp. 7640-7643.

Christian Requena-Mesa, Markus Reichstein, Miguel D. Mahecha, Basil Kraft, and J. Denzler, "Predicting landscapes as seen from space from environmental conditions", in 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), (2018), pp. 1768-1771.

Maha Shadaydeh, Yanira Guanche Garcia, Miguel D. Mahecha, Markus Reichstein, and Joachim Denzler, "Causality analysis of ecological time series: a time-frequency approach", in 8th International Workshop on Climate Informatics: CI 2018, edited by C. Chen, D. Cooley, J. Runge, and E. Szekely (2018), pp. 111-114.

Erik Rodner, Björn Barz, Yanira Guanche, Milan Flach, Miguel D. Mahecha, Paul Bodesheim, Markus Reichstein, and Joachim Denzler, "Maximally divergent intervals for anomaly detection", in ICML 2016 Anomaly Detection Workshop, (2016).

Gustau Camps-Valls, Martin Jung, Kazuhito Ichii, Dario Papale, Gianluca Tramontana, Paul Bodesheim, Christopher Schwalm, Jakob Zscheischler, Miguel D. Mahecha, and Markus Reichstein, "Ranking drivers of global carbon and energy fluxes over land", in IEEE International Symposium on Geoscience and Remote Sensing IGARSS, (2015), pp. 4416-4419.

H. Shan, Jens Kattge, P Reich, A Banerjee, F Schrodt, and Markus Reichstein, "Gap filling in the plant kingdom - Trait prediction using hierarchical probabilistic matrix factorization.", in Proceedings of the International Conference for Machine Learning (ICML), edited by John Langford (International Conference on Machine Learning, Edinburgh, 2012), Vol. 2, pp. 1303-1310.

Markus Reichstein, "How can artificial intelligence enhance our understanding of the earth system?", in Latest Thinking Video, (2020).

Sinikka Paulus, Tarek S. El-Madany, Thomas Wutzler, Arnaud Carrara, Gerardo M. Moreno, Markus Reichstein, René Orth, Martin Hertel, Ramon López-Jimenez, and Mirco Migliavacca, "High-resolution large weighing lysimeter measurements with meteorological and soil-hydrological variables from a Mediterranean Savanna", in Zenodo, (2022).

Ranit De, Alexander Brenning, Markus Reichstein, Ladislav Sigut, Borja Ruiz Reverter, Mika Korkiakoski, Eugenie Paul-Limoges, Peter D. Blanken, Thomas Andrew Black, Bert Gielen, Torbern Tagesson, Georg Wohlfahrt, Leonardo Montagnani, Sebastian Wolf, Jiquan Chen, Michael Liddell, Ankur Desai, Sujan Koirala, and Nuno Carvalhais, "Inter–annual variability of hydrological parameters improves simulation of annual gross primary production", in ESS Open Archive, (2025).