3 citations · 4 across the 4 of their papers we have counts for
5 papers
SHRUG-FM: Reliability-Aware Foundation Models for Earth Observation
Maria Gonzalez-Calabuig, Kai-Hendrik Cohrs, Vishal Nedungadi +7
Geospatial foundation models (GFMs) for Earth observation often fail to perform reliably in environments underrepresented during pretraining. We introduce SHRUG-FM, a framework for…
Feature Extraction in the Remote Sensing Data Value Chain: A Systematic Review of Methods and Applications
Nathan Mankovich, Kai-Hendrik Cohrs, Homer Durand +3
Earth observation involves collecting, analyzing, and processing an ever-growing mass of data. This planetary data is crucial for addressing relevant societal, economic, and enviro…
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…
Large Language Models for Constrained-Based Causal Discovery
Kai-Hendrik Cohrs, Gherardo Varando, Emiliano Diaz +2
Causality is essential for understanding complex systems, such as the economy, the brain, and the climate. Constructing causal graphs often relies on either data-driven or expert-d…
Causal hybrid modeling with double machine learning
Kai-Hendrik Cohrs, Gherardo Varando, Nuno Carvalhais +2
Hybrid modeling integrates machine learning with scientific knowledge to enhance interpretability, generalization, and adherence to natural laws. Nevertheless, equifinality and reg…