activity
20212026
most citedAI for Extreme Event Modeling and Understanding: Methodologies and Challenges

3 citations · 6 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2026

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

Carmen Oliver Huidobro, Mikolaj Czerkawski, Kevin Monsalvez-Pozo +3

Pretraining generalist Earth observation foundation models requires data that combine several sensors, varied temporal sampling and, increasingly, text, yet open datasets rarely pr…

cs.CV2025

Video Compression for Spatiotemporal Earth System Data

Oscar J. Pellicer-Valero, Cesar Aybar, Gustau Camps Valls

Large-scale Earth system datasets, from high-resolution remote sensing imagery to spatiotemporal climate model outputs, exhibit characteristics analogous to those of standard video…

cs.LG2024★ 1 cited

Explainable Earth Surface Forecasting under Extreme Events

Oscar J. Pellicer-Valero, Miguel-Ángel Fernández-Torres, Chaonan Ji +2

With climate change-related extreme events on the rise, high dimensional Earth observation data presents a unique opportunity for forecasting and understanding impacts on ecosystem…

cs.AI2024★ 3 cited

AI for Extreme Event Modeling and Understanding: Methodologies and Challenges

Gustau Camps-Valls, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs +22

In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences. Here, AI improved weather forecasting, model emulation, parameter…

cs.LG2024★ 2 cited

DeepExtremeCubes: Integrating Earth system spatio-temporal data for impact assessment of climate extremes

Chaonan Ji, Tonio Fincke, Vitus Benson +12

With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show prom…

physics.med-ph2021

Deep Learning for fully automatic detection, segmentation, and Gleason Grade estimation of prostate cancer in multiparametric Magnetic Resonance Images

Oscar J. Pellicer-Valero, José L. Marenco Jiménez, Victor Gonzalez-Perez +7

The emergence of multi-parametric magnetic resonance imaging (mpMRI) has had a profound impact on the diagnosis of prostate cancers (PCa), which is the most prevalent malignancy in…