Jung, Martin

Deep learning and process understanding for data-driven Earth system science

Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J., Carvalhais, N., & Prabhat (2019) · Nature

Hydrological Forecasting Using AIModel Reduction and Neural Networks

Cited by 5,673

Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach

Jung, M., Schwalm, C., Migliavacca, M., Walther, S., Camps-Valls, G., Koirala, S., Anthoni, P., Besnard, S., Bodesheim, P., Carvalhais, N., et al. (2020) · Biogeosciences

Plant Water Relations and Carbon DynamicsAtmospheric and Environmental Gas Dynamics

Cited by 866

Towards hybrid modeling of the global hydrological cycle

Kraft, B., Jung, M., Körner, M., Koirala, S., & Reichstein, M. (2022) · Hydrology and Earth System Sciences

Hydrological Forecasting Using AISoil Moisture and Remote Sensing

Cited by 173

X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X

Nelson, J. A., Walther, S., Gans, F., Kraft, B., Weber, U., Novick, K., Buchmann, N., Migliavacca, M., Wohlfahrt, G., Šigut, L., et al. (2024) · Biogeosciences

Plant Water Relations and Carbon DynamicsAtmospheric and Environmental Gas Dynamics

Cited by 136