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Learning Structures in Earth Observation Data with Gaussian Processes., , , , and . AALTD@PKDD/ECML (Revised Selected Papers), volume 9785 of Lecture Notes in Computer Science, page 78-94. Springer, (2015)Unsupervised Deep Feature Extraction for Remote Sensing Image Classification., , and . IEEE Trans. Geoscience and Remote Sensing, 54 (3): 1349-1362 (2016)Emulation as an Accurate Alternative to Interpolation in Sampling Radiative Transfer Codes., , , , , , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 11 (12): 4918-4931 (2018)The FLUXCOM ensemble of global land-atmosphere energy fluxes., , , , , , , , , and . CoRR, (2018)Sensitivity maps of the Hilbert-Schmidt independence criterion., and . Appl. Soft Comput., (2018)Replacing radiative transfer models by surrogate approximations through machine learning., , , , and . IGARSS, page 633-636. IEEE, (2015)Ranking drivers of global carbon and energy fluxes over land., , , , , , , , , and . IGARSS, page 4416-4419. IEEE, (2015)Active emulation of computer codes with Gaussian processes - Application to remote sensing., , and . CoRR, (2019)Multioutput Automatic Emulator for Radiative Transfer Models., , , and . IGARSS, page 4019-4022. IEEE, (2018)Gap Filling of Biophysical Parameter Time Series with Multi-Output Gaussian Processes., , , , and . IGARSS, page 4039-4042. IEEE, (2018)