3 papers
cs.LG2025
Assessing the Geographic Generalization and Physical Consistency of Generative Models for Climate Downscaling
Carlo Saccardi, Maximilian Pierzyna, Haitz Sáez de Ocáriz Borde +6
Kilometer-scale weather data is crucial for real-world applications but remains computationally intensive to produce using traditional weather simulations. An emerging solution is…
cs.CV2024
Deep Probability Segmentation: Are segmentation models probability estimators?
Simone Fassio, Simone Monaco, Daniele Apiletti
Deep learning has revolutionized various fields by enabling highly accurate predictions and estimates. One important application is probabilistic prediction, where models estimate…
physics.ao-ph2024
Uncertainty-aware segmentation for rainfall prediction post processing
Simone Monaco, Luca Monaco, Daniele Apiletti
Accurate precipitation forecasts are crucial for applications such as flood management, agricultural planning, water resource allocation, and weather warnings. Despite advances in…