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Integrating Domain Knowledge in Data-driven Earth Observation with Process Convolutions
The modelling of Earth observation data is a challenging problem, typica...
04/16/2021 ∙ by Daniel Heestermans Svendsen, et al. ∙
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Synergistic Integration of Optical and Microwave Satellite Data for Crop Yield Estimation
Developing accurate models of crop stress, phenology and productivity is...
12/11/2020 ∙ by Anna Mateo-Sanchis, et al. ∙
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Understanding Climate Impacts on Vegetation with Gaussian Processes in Granger Causality
Global warming is leading to unprecedented changes in our planet, with g...
12/06/2020 ∙ by Miguel Morata-Dolz, et al. ∙
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Learning drivers of climate-induced human migrations with Gaussian processes
In the current context of climate change, extreme heatwaves, droughts, a...
11/17/2020 ∙ by Jose M. Tarraga, et al. ∙
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Living in the Physics and Machine Learning Interplay for Earth Observation
Most problems in Earth sciences aim to do inferences about the system, w...
10/18/2020 ∙ by Gustau Camps-Valls, et al. ∙
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Gaussianizing the Earth: Multidimensional Information Measures for Earth Data Analysis
Information theory is an excellent framework for analyzing Earth system ...
10/13/2020 ∙ by J. Emmanuel Johnson, et al. ∙
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