Researcher Portfolio
Hu, Xinting
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Researcher Profile
Position: Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Researcher ID: https://pure.mpg.de/cone/persons/resource/persons275006
Publications
(1 - 25 of 114)
: Poehls, J., Alonso, L., Koirala, S., Carvalhais, N., & Reichstein, M. (2025). Downscaling soil moisture to sub-km resolutions with simple machine learning ensembles. Journal of Hydrology, 652: 132624. doi:10.1016/j.jhydrol.2024.132624. [PubMan] : De, R., Brenning, A., Reichstein, M., Sigut, L., Reverter, B. R., Korkiakoski, M., Paul-Limoges, E., Blanken, P. D., Black, T. A., Gielen, B., Tagesson, T., Wohlfahrt, G., Montagnani, L., Wolf, S., Chen, J., Liddell, M., Desai, A., Koirala, S., & Carvalhais, N. (2025). Inter–annual variability of hydrological parameters improves simulation of annual gross primary production. ESS Open Archive. doi:10.22541/essoar.174349993.30198378/v1. [PubMan] : Karasante, I., Alonso, L., Prapas, I., Ahuja, A., Carvalhais, N., & Papoutsis, I. (2025). SeasFire cube - a multivariate dataset for global wildfire modeling. Scientific Data, 12: 368. doi:10.1038/s41597-025-04546-3. [PubMan] : Lee, H. T., Jung, M., Carvalhais, N., Reichstein, M., Forkel, M., Bloom, A. A., Pacheco-Labrador, J., & Koirala, S. (2025). Spatial attribution of temporal variability in global land-atmosphere CO2 exchange using a model-data integration framework. Journal of Advances in Modeling Earth Systems, 17(3): e2024MS004479v. doi:10.1029/2024MS004479. [PubMan] : Neigh, C. S. R., Montesano, P. M., Sexton, J. O., Wooten, M., Wagner, W., Feng, M., Carvalhais, N., Calle, L., & Carroll, M. L. (2025). Russian forests show strong potential for young forest growth. Communications Earth & Environment, 6: 71. doi:10.1038/s43247-025-02006-9. [PubMan] : Benson, V., Robin, C., Requena Mesa, C., Alonso, L., Carvalhais, N., Cortés, J., Gao, Z., Linscheid, N., Weynants, M., & Reichstein, M. (2024). Multi-modal learning for geospatial vegetation forecasting. In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). doi:10.1109/CVPR52733.2024.02625. [PubMan] : Raoult, N., Douglas, N., MacBean, N., Kolassa, J., Quaife, T., Roberts, A. G., Fisher, R. A., Fer, I., Bacour, C., Dagon, K., Hawkins, L., Carvalhais, N., Cooper, E., Dietze, M., Gentine, P., Kaminski, T., Kennedy, D., Liddy, H. M., Moore, D., Peylin, P., Pinnington, E., Sanderson, B. M., Scholze, M., Seiler, C., Smallman, T. L., Vergopolan, N., Viskari, T., Williams, M., & Zobitz, J. (2024). Parameter estimation in land surface models: Challenges and opportunities with data assimilation and machine learning. ESS Open Archive. doi:10.22541/essoar.172838640.01153603/v1. [PubMan] : De, R., Bao, S., Koirala, S., Brenning, A., Reichstein, M., Tagesson, T., Liddell, M., Ibrom, A., Wolf, S., Sigut, L., 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. (2024). Addressing challenges in simulating inter-annual variability of gross primary production. ESS Open Archive. doi:10.22541/essoar.172656939.93739740/v1. [PubMan] : Cohrs, K.-H., Varando, G., Camps-Valls, G., Carvalhais, N., & Reichstein, M. (2024). Causal hybrid modeling with double machine learning—applications in carbon flux modeling. Machine Learning: Science and Technology, 5(3): 035021. doi:10.1088/2632-2153/ad5a60. [PubMan] : Wang, S., Yang, H., Koirala, S., Forkel, M., Reichstein, M., & Carvalhais, N. (2024). Understanding disturbance regimes from patterns in modeled forest biomass. Journal of Advances in Modeling Earth Systems, 16(6): e2023MS004099. doi:10.1029/2023MS004099. [PubMan] : Dinh, T. L. A., Goll, D., Ciais, P., Carvalhais, N., & Lauerwald, R. (2024). Benchmarking simulations of forest regrowth across Europe. In EGU General Assembly 2024. doi:10.5194/egusphere-egu24-1784. [PubMan] : Bao, S., Carvalhais, N., Xu, J., Chen, J., Lei, Y., Tana, G., Lin, C., & Shi, J. (2024). Global distribution pattern in characteristics of gross primary productivity response to soil water availability. SSRN Research Paper Series. doi:10.2139/ssrn.4789075. [PubMan] : Yang, H., Wang, S., Son, R., Lee, H. T., Benson, V., Zhang, W., Zhang, Y., Zhang, Y., Kattge, J., Boenisch, G., Schepaschenko, D., Karaszewski, Z., Stereńczak, K., Moreno-Martínez, Á., Nabais, C., Birnbaum, P., Vieilledent, G., Weber, U., & Carvalhais, N. (2024). Global patterns of tree wood density. Global Change Biology, 30(3): e17224. doi:10.1111/gcb.17224. [PubMan] : Tao, F., Houlton, B. Z., Frey, S. D., Lehmann, J., Manzoni, S., Huang, Y., Jiang, L., Mishra, U., Hungate, B. A., Schmidt, M. W. I., Reichstein, M., Carvalhais, N., Ciais, P., Wang, Y.-P., Ahrens, B., Hugelius, G., Hocking, T. D., Lu, X., Shi, Z., Viatkin, K., Vargas, R., Yigini, Y., Omuto, C., Malik, A. A., Peralta, G., Cuevas-Corona, R., Paolo, L. E. D., Luotto, I., Liao, C., Liang, Y.-S., Saynes, V. S., Huang, X., & Luo, Y. (2024). Reply to: Model uncertainty obscures major driver of soil carbon. Nature, 627, E4-E6. doi:10.1038/s41586-023-07000-9. [PubMan] : Son, R., Stacke, T., Gayler, V., Nabel, J. E. M. S., Schnur, R., Alonso, L., Requena Mesa, C., Winkler, A., Hantson, S., Zaehle, S., Weber, U., & Carvalhais, N. (2024). Integration of a deep-learning-based fire model into a global land surface model. Journal of Advances in Modeling Earth Systems, 16(1): e2023MS003710. doi:10.1029/2023MS003710. [PubMan] : Yang, H., Stereńczak, K., Karaszewski, Z., & Carvalhais, N. (2023). Similar importance of inter-tree and intra-tree variations in wood density observations in Central Europe. EGUsphere. doi:10.5194/egusphere-2023-2691. [PubMan] : Voigt, H., Carvalhais, N., Meuschke, M., Reichstein, M., Zarrie, S., & Lawonn, K. (2023). 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). Singapur: Association for Computational Linguistics. doi:10.18653/v1/2023.emnlp-demo.5. [PubMan] : Fan, N., Santoro, M., Besnard, S., Cartus, O., Koirala, S., & Carvalhais, N. (2023). Implications of the steady-state assumption for the global vegetation carbon turnover. Environmental Research Letters, 18(10): 104036. doi:10.1088/1748-9326/acfb22. [PubMan] : Bao, S., Alonso, L., Wang, S., Gensheimer, J., De, R., & Carvalhais, N. (2023). Toward robust parameterizations in ecosystem‐level photosynthesis models. Journal of Advances in Modeling Earth Systems, 15(8): e2022MS003464. doi:10.1029/2022MS003464. [PubMan] : Tao, F., Houlton, B. Z., Frey, S. D., Lehmann, J., Manzoni, S., Huang, Y., Jiang, L., Mishra, U., Hungate, B. A., Schmidt, M. W. I., Reichstein, M., Carvalhais, N., Ciais, P., Wang, Y.-P., Ahrens, B., Hugelius, G., Hocking, T. D., Lu, X., Shi, Z., Viatkin, K., Vargas, R., Yigini, Y., Omuto, C., Malik, A. A., Peralta, G., Cuevas-Corona, R., Paolo, L. E. D., Luotto, I., Liao, C., Liang, Y.-S., Saynes, V. S., Huang, X., & Luo, Y. (2023). Reply to: Contribution of carbon inputs to soil carbon accumulation cannot be neglected. bioRxiv: the preprint server for biology. doi:10.1101/2023.08.20.552557. [PubMan] : Tao, Feng, F., Huang, Y., Hungate, B. A., Manzoni, S., Frey, S. D., Schmidt, M. W. I., Reichstein, M., Carvalhais, N., Ciais, P., Jiang, L., Lehmann, J., Wang, Y.-P., Houlton, B. Z., Ahrens, B., Mishra, U., Hugelius, G., Hocking, T. D., Lu, X., Shi, Z., Viatkin, K., Vargas, R., Yigini, Y., Omuto, C., Malik, A. A., Peralta, G., Cuevas-Corona, R., Di Paolo, L. E., Luotto, I., Liao, C., Liang, Y.-S., Saynes, V. S., Huang, X., & Luo, Y. (2023). Microbial carbon use efficiency promotes global soil carbon storage. Nature, 618, 981-985. doi:10.1038/s41586-023-06042-3. [PubMan] : Pacheco-Labrador, J., de Bello, F., Migliavacca, M., Ma, X., Carvalhais, N., & Wirth, C. (2023). A generalizable normalization for assessing plant functional diversity metrics across scales from remote sensing. Methods in Ecology and Evolution, 14(8), 2123-2136. doi:10.1111/2041-210X.14163. [PubMan] : Lee, H. T., Jung, M., Carvalhais, N., Trautmann, T., Kraft, B., Reichstein, M., Forkel, M., & Koirala, S. (2023). Diagnosing modeling errors in global terrestrial water storage interannual variability. Hydrology and Earth System Sciences, 27(7), 1531-1563. doi:10.5194/hess-27-1531-2023. [PubMan] : Yang, H., Munson, S. M., Huntingford, C., Carvalhais, N., Knapp, A. K., Li, X., Peñuelas, J., Zscheischler, J., & Chen, A. (2023). The detection and attribution of extreme reductions in vegetation growth across the global land surface. Global Change Biology, 29(8), 2351-2362. doi:10.1111/gcb.16595. [PubMan] : Zhang, W., Jung, M., Migliavacca, M., Poyatos, R., Miralles, D. G., El-Madany, T. S., Galvagno, M., Carrara, A., Arriga, N., Ibrom, A., Mammarella, I., Papale, D., Cleverly, J. R., Liddell, M., Wohlfahrt, G., Markwitz, C., Mauder, M., Paul-Limoges, E., Schmidt, M., Wolf, S., Brümmer, C., Arain, M. A., Fares, S., Kato, T., Ardö, J., Oechel, W., Hanson, C., Korkiakoski, M., Biraud, S., Steinbrecher, R., Billesbach, D., Montagnani, L., Woodgate, W., Shao, C., Carvalhais, N., Reichstein, M., & Nelson, J. A. (2023). The effect of relative humidity on eddy covariance latent heat flux measurements and its implication for partitioning into transpiration and evaporation. Agricultural and Forest Meteorology, 330: 109305. doi:10.1016/j.agrformet.2022.109305. [PubMan]