106 citations · 297 across the 8 of their papers we have counts for
3 papers · 1 filter
Deep Gaussian Processes for geophysical parameter retrieval
Daniel Heestermans Svendsen, Pablo Morales-Álvarez, Rafael Molina +1
This paper introduces deep Gaussian processes (DGPs) for geophysical parameter retrieval. Unlike the standard full GP model, the DGP accounts for complicated (modular, hierarchical…
Physics-Aware Gaussian Processes in Remote Sensing
Gustau Camps-Valls, Luca Martino, Daniel H. Svendsen +5
Earth observation from satellite sensory data poses challenging problems, where machine learning is currently a key player. In recent years, Gaussian Process (GP) regression has ex…
Living in the Physics and Machine Learning Interplay for Earth Observation
Gustau Camps-Valls, Daniel H. Svendsen, Jordi Cortés-Andrés +7
Most problems in Earth sciences aim to do inferences about the system, where accurate predictions are just a tiny part of the whole problem. Inferences mean understanding variables…