3 papers
cs.LG2026
What's in an Earth Embedding? An Explainability Analysis of Location Encoders
Livia Betti, Sebastian Ricke, Ivica Obadic +2
Geographic implicit neural representations (INRs) learn to map any coordinate on Earth to a location embedding, implicitly encoding geospatial data into the weights of a neural net…
cs.LG2026
UST-GNN: A Unified Spatial--Topological Graph Neural Network Framework for Urban Analytics--Demonstrated through a Case Study on Urban Health Prediction
Minwei Zhao, Sanja Scepanovic, Stephen Law +3
Understanding how social, demographic, environmental, and spatial factors jointly shape urban outcomes is essential for sustainable urban development and evidence-based policy. Tra…
cs.CV2025
Exploring Self-Attention for Crop-type Classification Explainability
Ivica Obadic, Ribana Roscher, Dario Augusto Borges Oliveira +1
Transformer models have become a promising approach for crop-type classification. Although their attention weights can be used to understand the relevant time points for crop disam…