Requena-Mesa, C.; Reichstein, M.; Mahecha, M. D.; Kraft, B.; Denzler, J.: Predicting landscapes from environmental conditions using generative networks. In: Pattern Recognition, DAGM GCPR 2019, pp. 203 - 217 (Eds. FInk, G. A.; Frintrop, S.; Jiang, X.). Springer, Cham (2019)

Shadaydeh, M.; Denzler, J.; Garcia, Y. G.; Mahecha, M. D.: Time-frequency causal inference uncovers anomalous events in environmental systems. In: Pattern Recognition, DAGM GCPR 2019, pp. 499 - 512 (Eds. FInk, G. A.; Frintrop, S.; Jiang, X.). Springer, Cham (2019)

Trifunov, V. T.; Shadaydeh, M.; Runge, J.; Eyring, V.; Reichstein, M.; Denzler, J.: Nonlinear causal link estimation under hidden confounding with an application to time series anomaly detection. In: Pattern Recognition, DAGM GCPR 2019, pp. 261 - 273 (Eds. Fink, G. A.; Frintrop, S.; Jiang, X.). Springer, Cham (2019)

Flach, M.; Lange, H.; Foken, T.; Hauhs, M.: Recurrence analysis of Eddy covariance fluxes. In: Recurrence Plots and Their Quantifications: Expanding Horizons, Vol. 180, pp. 301 - 319 (Eds. Webber Jr., C. L.; Ioana, C.; Marwan, N.). Springer International Publishing, Switzerland (2016)

Lange, H.; Boese, S.: Recurrence quantification and recurrence network analysis of global photosynthetic activity. In: Recurrence Quantification Analysis: Theory and Best Practices, pp. 349 - 374 (Eds. Webber, C. L.; Marwan, N.). Springer, Cham [u.a.] (2014)

Reichstein, M.; Richardson, A. D.; Migliavacca, M.; Carvalhais, N.: Plant–environment interactions across multiple scales. In: Ecology and the Environment, pp. 1 - 27 (Ed. Monson, R. K.). Springer, New York (2014)

Ciais, P.; Sabine, C.; Bala, G.; Bopp, L.; Brovkin, V.; Canadell, J.; Chhabra, A.; DeFries, R.; Galloway, J.; Heimann, M. et al.; Jones, C.; Le Quéré, C.; Mynen, R. B.; Piao, S.; Thornton, P.; Ahlström, A.; Anav, A.; Andrews, O.; Archer, D.; Arora, V.; Bonan, G.; Borges, A. V.; Bousquet, P.; Bouwman, L.; Bruhwiler, L. M.; Caldeira, K.; Cao, L.; Chappellaz, J.; Chevallier, F.; Cleveland, C.; Cox, P.; Dentener, F. J.; Doney, S. C.; Erisman, J. W.; Euskirchen, E. S.; Friedlingstein, P.; Gruber, N.; Gurney, K.; Holland, E. A.; Hopwood, B.; Houghton, R. A.; House, J. I.; Houweling, S.; Hunter, S.; Hurtt, G.; Jacobson, A. D.; Jain, A.; Joos, F.; Jungclaus, J.; Kaplan, J. O.; Kato, E.; Keeling, R.; Khatiwala, S.; Kirschke, S.; Goldewijk, K. K.; Kloster, S.; Koven, C.; Kroeze, C.; Lamarque, J.-F.; Lassey, K.; Law, R. M.; Lenton, A.; Lomas, M. R.; Luo, Y.; Maki, T.; Marland, G.; Matthews, H. D.; Mayorga, E.; Melton, J. R.; Metzl, N.; Munhoven, G.; Niwa), Y.; Norby, R. J.; O’Connor, F.; Orr, J.; Park, G.-H.; Patra, P.; Peregon, A.; Peters, W.; Peylin, P.; Piper, S.; Pongratz, J.; Poulter, B.; Raymond, P. A.; Rayner, P.; Ridgwell, A.; Ringeval, B.; Rödenbeck, C.; Saunois, M.; Schmittner, A.; Schuur, E.; Sitch, S.; Spahni, R.; Stocker, B.; Takahashi, T.; Thompson, R. L.; Tjiputra, J.; van der Werf, G.; van Vuuren, D.; Voulgarakis, A.; Wania, R.; Zaehle, S.; Zeng, N.: Carbon and other biogeochemical cycles. In: Climate Change 2013, The Physical Science Basis, WG I, Contribution to the fifth assessment report of the IPCC, pp. 465 - 570 (Eds. Stocker, T. F.; Qin, D.). Cambridge University Press, New York, USA (2013)

Frank, D.; Reichstein, M.; Miglietta, F.; Pereira, J.S.: Impact of climate variability and extremes on the carbon cycle of the Mediterranean region. In: Regional Assessment of Climate Change in the Mediterranean; Volume 2: Agriculture, Forests and Ecosystem Services and People, Vol. 51, pp. 31 - 47 (Eds. Navarra, A.; Tubiana, L.). Springer, New York (2013)

Aubinet, M.; Feigenwinter, C.; Heinesch, B.; Laffineur, Q.; Papale, D.; Reichstein, M.; Rinne, J.; van Gorsel, E.: Nighttime flux correction. In: Eddy Covariance: A Practical Guide to Measurement and Data Analysis Series: Springer Atmospheric Sciences (Eds. Aubinet, M.; Vesala, T.; Papale, D.) (2012)

Reichstein, M.; Stoy, P. C.; Desai, A. R.; Lasslop, G.; Richardson, A. D.: Partitioning of net fluxes. In: Eddy Covariance: A Practical Guide to Measurement and Data Analysis, pp. 263 - 289 (Eds. Aubinet, M.; Vasala, T.; Papale, D.). Springer, Atmospheric Sciences (2012)

Richardson, A.D.; Aubinet, M.; Barr, A.G.; Hollinger, D.Y.; Ibrom, A.; Lasslop, G.; Reichstein, M.: Uncertainty quantification. In: Eddy Covariance: A Practical Guide to Measurement and Data Analysis (Eds. Aubinet, M.; Vesala, T.; Papale, D.) (2012)

Seneviratne, S. I.; Easterling, D.; Goodess, C. M.; Kanae, S.; Kossin, J.; Luo, Y.; Marengo, J.; McInnes, K.; Rahimi, M.; Reichstein, M. et al.; Sorteberg, A.; Vera, C.; Zhang, X.: Changes in climate extremes and their impacts on the natural physical environment. In: Managing the risks of extreme events and disasters to advance climate change adaptation: Special report of the Intergovernmental Panel on Climate Change, pp. 109 - 230 (Eds. Field, C. B.; Barros, V.; Stocker, T. F.; Qin, D.; Dokken, D. J. et al.). Cambridge University Press, Cambridge (2012)

Dinh, T. L. A.; Goll, D.; Ciais, P.; Carvalhais, N.; Lauerwald, R.: Benchmarking simulations of forest regrowth across Europe. In: EGU General Assembly 2024. EGU General Assembly 2024, Vienna, Austria, April 14, 2024 - April 19, 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, pp. 70 - 81. The 2023 Conference on Empirical Methods in Natural Language Processing, Singapure, December 06, 2023 - December 10, 2023. Association for Computational Linguistics, Singapur (2023)

Friede, D.; Reimers, C.; Stuckenschmidt, H.; Niepert, M.: Learning disentangled discrete representations. Machine learning and knowledge discovery in databases: Research track. ECML PKDD 2023. Lecture Notes in Computer Science 14172, pp. 593 - 609 (2023)

Brandt, G.; Balfanz, A.; Fomferra, N.; Harish, T. M.; Mahecha, M.; Kraemer, G.; Montero, D.; Meißl, S.; Achtsnit, S.; Umlauft, J. et al.; Neumann, A.; Horton, A.; Ewart, M.; Gans, F.; Anghelea, A.: DeepESDL – an open platform for research and collaboration in Earth Sciences. EGU General Assembly 2023, EGU23-15225, Vienna, Austria, April 24, 2023 - April 28, 2023. EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15225, (2023)

Bastos, A.: Carbon budgets from global to regional scales: current challenges and future perspectives. In: EGU General Assembly 2022, Vienna, Austria. (accepted)

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, pp. 1 - 35 (2022)

Pacheco-Labrador, J.; Weber, U.; Ma, X.; Mahecha, M. D.; Carvalhais, N.; Wirth, C.; Huth, A.; Bohn, F. J.; Kraemer, G.; Heiden, U. et al.; members, F.; Migliavacca, M.: Evalutating the potential of desis to infer plant taxonomical and functional diversities in europwean forests. In: 1st DESIS User Workshop – Imaging Spectrometer Space Mission, Calibration and Validation, Applications, Methods, Vol. XLVI-1/W1-2021, pp. 49 - 55. 1st DESIS User Workshop on Imaging Spectrometer Space Mission, Calibration and Validation, Applications, Methods, ELECTR NETWORK, September 28, 2021 - October 01, 2021. (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)