440 citations · 789 across the 16 of their papers we have counts for
Showing 2022Show all
2 papers · 1 filter
eess.SP2022★ 9 cited
Channel-driven Decentralized Bayesian Federated Learning for Trustworthy Decision Making in D2D Networks
Luca Barbieri, Osvaldo Simeone, Monica Nicoli
Bayesian Federated Learning (FL) offers a principled framework to account for the uncertainty caused by limitations in the data available at the nodes implementing collaborative tr…
eess.SP2022
Motion Estimation and Compensation in Automotive MIMO SAR
Marco Manzoni, Dario Tagliaferri, Marco Rizzi +8
With the advent of self-driving vehicles, autonomous driving systems will have to rely on a vast number of heterogeneous sensors to perform dynamic perception of the surrounding en…