Emergence of Network Motifs in Deep Neural Networks. - Matteo Zambra; Amos Maritan; Alberto Testolin (Entropy, 2020)

A developmental approach for training deep belief networks. - Matteo Zambra; Alberto Testolin; Michele De Filippo De Grazia; Marco Zorzi (CoRR, 2022)

Learning-based estimation of in-situ wind speed from underwater acoustics. - Matteo Zambra; Dorian Cazau; Nicolas Farrugia; Alexandre Gensse; Sara Pensieri; Roberto Bozzano; Ronan Fablet (CoRR, 2022)

Multi-Modal Learning-based Reconstruction of High-Resolution Spatial Wind Speed Fields. - Matteo Zambra; Nicolas Farrugia; Dorian Cazau; Alexandre Gensse; Ronan Fablet (CoRR, 2023)

A Developmental Approach for Training Deep Belief Networks. - Matteo Zambra; Alberto Testolin; Marco Zorzi (Cogn. Comput., 2023)

Multi-modal AI methods in the context of heterogeneous oceanic observations and multisensor maritime surveillance. (Méthodes IA multimodales dans des contextes d'observation océanographique et de surveillance maritime multi-capteurs hétérogènes). - Matteo Zambra (2024)