3 papers
q-bio.QM2026
FPLIER: Federated Pathway-Level Information Extractor
Daniele Malpetti, Christian Berchtold, Francesco Gualdi +3
In transcriptomics, gene-set-aware factorization methods such as the Pathway Level Information Extractor (PLIER) are most effective when trained on large, heterogeneous expression…
cs.RO2026
Tiny-DroNeRF: Tiny Neural Radiance Fields aboard Federated Learning-enabled Nano-drones
Ilenia Carboni, Elia Cereda, Lorenzo Lamberti +3
Sub-30g nano-sized aerial robots can leverage their agility and form factor to autonomously explore cluttered and narrow environments, like in industrial inspection and search and…
q-bio.OT2025
Technical and Legal Aspects of Federated Learning in Bioinformatics: Applications, Challenges and Opportunities
Daniele Malpetti, Marco Scutari, Francesco Gualdi +6
Federated learning leverages data across institutions to improve clinical discovery while complying with data-sharing restrictions and protecting patient privacy. This paper provid…