3 citations · 3 across the 5 of their papers we have counts for
4 papers · 1 filter
LUME-DBN: Full Bayesian Learning of DBNs from Incomplete data in Intensive Care
Federico Pirola, Fabio Stella, Marco Grzegorczyk
Dynamic Bayesian networks (DBNs) are increasingly used in healthcare due to their ability to model complex temporal relationships in patient data while maintaining interpretability…
Towards Privacy-Aware Bayesian Networks: A Credal Approach
Niccolò Rocchi, Fabio Stella, Cassio de Campos
Bayesian networks (BN) are probabilistic graphical models that enable efficient knowledge representation and inference. These have proven effective across diverse domains, includin…
Tackling Federated Unlearning as a Parameter Estimation Problem
Antonio Balordi, Lorenzo Manini, Fabio Stella +1
Privacy regulations require the erasure of data from deep learning models. This is a significant challenge that is amplified in Federated Learning, where data remains on clients, m…
Industrial Energy Disaggregation with Digital Twin-generated Dataset and Efficient Data Augmentation
Christian Internò, Andrea Castellani, Sebastian Schmitt +2
Industrial Non-Intrusive Load Monitoring (NILM) is limited by the scarcity of high-quality datasets and the complex variability of industrial energy consumption patterns. To addres…