6 papers
Quantum Circuit-Based Learning Models: Bridging Quantum Computing and Machine Learning
Fan Fan, Yilei Shi, Mihai Datcu +5
Machine Learning (ML) has been widely applied across numerous domains due to its ability to automatically identify informative patterns from data for various tasks. The availabilit…
Scaling Laws for Geospatial Foundation Models: A case study on PhilEO Bench
Nikolaos Dionelis, Riccardo Musto, Jente Bosmans +7
Foundation Models (FMs) have achieved state-of-the-art performance across domains by leveraging large-scale pretraining. In Earth Observation (EO), the availability of petabyte-sca…
Neural Plasticity-Inspired Multimodal Foundation Model for Earth Observation
Zhitong Xiong, Yi Wang, Fahong Zhang +7
Earth observation (EO) in open-world settings presents a unique challenge: different applications rely on diverse sensor modalities, each with varying ground sampling distances, sp…
Quantum Latent Diffusion Models
Francesca De Falco, Andrea Ceschini, Alessandro Sebastianelli +2
The introduction of quantum concepts is increasingly making its way into generative machine learning models. However, while there are various implementations of quantum Generative…
Leveraging Multi-Temporal Sentinel 1 and 2 Satellite Data for Leaf Area Index Estimation With Deep Learning
Clement Wang, Antoine Debouchage, Valentin Goldité +2
The Leaf Area Index (LAI) is a critical parameter to understand ecosystem health and vegetation dynamics. In this paper, we propose a novel method for pixel-wise LAI prediction by…
IceCloudNet: 3D reconstruction of cloud ice from Meteosat SEVIRI
Kai Jeggle, Mikolaj Czerkawski, Federico Serva +3
IceCloudNet is a novel method based on machine learning able to predict high-quality vertically resolved cloud ice water contents (IWC) and ice crystal number concentrations (N$_\t…