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Climate-Invariant Machine Learning., , , , , , , , , и 1 other автор(ы). CoRR, (2021)Observed strong atmospheric water constraints on forest photosynthesis using eddy covariance and satellite-based data across the Northern Hemisphere., , , , , и . Int. J. Appl. Earth Obs. Geoinformation, (2022)Deep Learning Based Cloud Cover Parameterization for ICON., , , , , и . CoRR, (2021)Achieving Conservation of Energy in Neural Network Emulators for Climate Modeling., , , и . CoRR, (2019)Towards Physically-Consistent, Data-Driven Models of Convection., , , и . IGARSS, стр. 3987-3990. IEEE, (2020)Differentiable modeling to unify machine learning and physical models and advance Geosciences., , , , , , , , , и 19 other автор(ы). CoRR, (2023)Tall Amazonian forests are less sensitive to precipitation variability, , , , , , и . Nature Geoscience, (28.05.2018)Exploring the Potential of Satellite Solar-Induced Fluorescence to Constrain Global Transpiration Estimates., , , , и . Remote. Sens., 11 (4): 413 (2019)On the Generalization of Agricultural Drought Classification from Climate Data., , , , , , и . CoRR, (2021)Multi-fidelity climate model parameterization for better generalization and extrapolation., , , и . CoRR, (2023)