25 citations · 36 across the 4 of their papers we have counts for
4 papers
Multi-Modal Learning-based Reconstruction of High-Resolution Spatial Wind Speed Fields
Matteo Zambra, Nicolas Farrugia, Dorian Cazau +2
Wind speed at sea surface is a key quantity for a variety of scientific applications and human activities. Due to the non-linearity of the phenomenon, a complete description of suc…
Learning-based estimation of in-situ wind speed from underwater acoustics
Matteo Zambra, Dorian Cazau, Nicolas Farrugia +4
Wind speed retrieval at sea surface is of primary importance for scientific and operational applications. Besides weather models, in-situ measurements and remote sensing technologi…
A developmental approach for training deep belief networks
Matteo Zambra, Alberto Testolin, Marco Zorzi
Deep belief networks (DBNs) are stochastic neural networks that can extract rich internal representations of the environment from the sensory data. DBNs had a catalytic effect in t…
Emergence of Network Motifs in Deep Neural Networks
Matteo Zambra, Alberto Testolin, Amos Maritan
Network science can offer fundamental insights into the structural and functional properties of complex systems. For example, it is widely known that neuronal circuits tend to orga…