G. Camps-Valls

MajorTOM:Elliot Pretrain, A Multi-Sensor, Multi-Temporal Pretraining Dataset for Earth Observation

Pretraining generalist Earth observation foundation models requires data that combine several sensors, varied temporal sampling and, increasingly, text, yet open datasets rarely provide all three in one consistent, easily accessible form. We introduce MajorTOM:Elliot Pretrain, a collection of 279,166 tiles of 10 km dra...

Enhancing reproducibility in hybrid Earth system models

Optimization Geometry of Equivalent Brownian RKHS Representations

Float64 tests over five grids numerically verify the finite identities, mapped one-layer and recursive trajectories, conditioning predictions, and theorem-matched Adam separation of a controlled finite Brownian RKHS with nodal, increment, and spectral coordinates.

Uncertainty-aware deep learning for wildfire danger forecasting

This work presents an uncertainty-aware DL framework that jointly captures epistemic (model) and aleatoric ( data) uncertainty to enhance short-term wildfire danger forecasting and significantly improves the accuracy and reliability of wildfire danger forecasting, advancing the development of trustworthy wildfire DL sy...