AdaFed: Performance-based Adaptive Federated Learning. - Alessandro Giuseppi; Lucrezia Della Torre; Danilo Menegatti; Antonio Pietrabissa (ICAAI, 2021)

Decentralized Federated Learning for Nonintrusive Load Monitoring in Smart Energy Communities. - Alessandro Giuseppi; Sabato Manfredi; Danilo Menegatti; Antonio Pietrabissa; Cecilia Poli (MED, 2022)

Model Predictive Control for Collision-free Spacecraft Formation with Artificial Potential Functions. - Danilo Menegatti; Alessandro Giuseppi; Antonio Pietrabissa (MED, 2022)

Decentralised Federated Learning for Hospital Networks With Application to COVID-19 Detection. - Alessandro Giuseppi; Sabato Manfredi; Danilo Menegatti; Cecilia Poli; Antonio Pietrabissa (IEEE Access, 2022)

Stability of Non-Cooperative Load Balancing with Time-Varying Latency. - Alessandro Giuseppi; Danilo Menegatti; Antonio Pietrabissa (CDC, 2023)

Behavioural Cloning for Serious Games in Support of Pediatric Neurorehabilitation. - Federico Baldisseri; Edoardo Montecchiani; Arturo Maiani; Danilo Menegatti; Alessandro Giuseppi; Antonio Pietrabissa; Vincenzo Fogliati; Francesco Delli Priscoli (MED, 2023)

Landslide Susceptibility Prediction from Satellite Data through an Intelligent System based on Deep Learning. - Alessandro Giuseppi; Leonardo Pio Lo Porto; Andrea Wrona; Danilo Menegatti (MED, 2023)

Deep Image Inpainting to Support Endoscopic Procedures. - Danilo Menegatti; Filippo Betello; Francesco Delli Priscoli; Alessandro Giuseppi (MED, 2023)

Vertically-Advised Federated Learning for Multi-Strategic Stock Predictions through Stochastic Attention-based LSTM. - Danilo Menegatti; Emanuele Ciccarelli; Michele Viscione; Alessandro Giuseppi (MED, 2023)

Load Demand Prediction for Electric Vehicles Smart Charging through Consensus-based Federated Learning. - Danilo Menegatti; Antonio Pietrabissa; Sabato Manfredi; Alessandro Giuseppi (MED, 2023)

A Discrete-Time Multi-Hop Consensus Protocol for Decentralized Federated Learning. - Danilo Menegatti; Alessandro Giuseppi; Sabato Manfredi; Antonio Pietrabissa (IEEE Access, 2023)

Dynamic Topology Optimization for Efficient and Decentralised Federated Learning. - Danilo Menegatti; Alessandro Giuseppi; Cecilia Poli; Antonio Pietrabissa (IEEE Big Data, 2024)

Deep Reinforcement Learning Platooning Control of Non-Cooperative Autonomous Vehicles in a Mixed Traffic Environment. - Danilo Menegatti; Andrea Wrona; Antonio Di Paola; Simone Gentile; Alessandro Giuseppi (CASE, 2024)

AdaLightLog: Enhancing Application Logs Anomaly Detection via Adaptive Federating Learning. - Danilo Menegatti; Emanuele De Santis; Stefano Felli; Alessandro Giuseppi (CRITIS, 2024)

Deep Deterministic Policy Gradient Control of Type 1 Diabetes. - Federico Baldisseri; Danilo Menegatti; Andrea Wrona (ECC, 2024)

Deep Reinforcement Learning Control of Type-1 Diabetes with Cross-Patient Generalization. - Mohab M. H. Atanasious; Valentina Becchetti; Federico Baldisseri; Danilo Menegatti; Andrea Wrona (MED, 2024)

Dynamic Mode Decomposition for Individualized Model Predictive Control with Application to Type 1 Diabetes. - Valentina Becchetti; Mohab M. H. Atanasious; Danilo Menegatti; Federico Baldisseri; Alessandro Giuseppi (MED, 2024)

Identifying chaotic dynamics in noisy time series through multimodal deep neural networks. - Alessandro Giuseppi; Danilo Menegatti; Antonio Pietrabissa (Mach. Learn. Sci. Technol., 2024)

Decentralised learning for Intelligent Control Systems. - Danilo Menegatti (2024)

Tractable Data-Driven Model Predictive Control Using One-Step Neural Networks Predictors. - Danilo Menegatti; Alessandro Giuseppi; Antonio Pietrabissa (IEEE Trans Autom. Sci. Eng., 2025)