AMOROSA, LORENZO MARIO
AMOROSA, LORENZO MARIO
DEI - DIPARTIMENTO DI INGEGNERIA DELL'ENERGIA ELETTRICA E DELL'INFORMAZIONE "GUGLIELMO MARCONI"
5G Architectures Enabling Remaining Useful Life Estimation for Industrial IoT: A Holistic Study
2025 Longhi, Nicolò; Amorosa, Lorenzo Mario; Cavallero, Sara; Buracchini, Enrico; Verdone, Roberto
GUMBLE: Uncertainty-Aware Conditional Mobile Data Generation using Bayesian Learning
2024 Verdone, Roberto; Lombardi, Michele; Amorosa, Lorenzo Mario; Skocaj, Marco
Multi-Agent Reinforcement Learning for Power Control in Wireless Networks via Adaptive Graphs
2024 Amorosa, L. M.; Skocaj, M.; Verdone, R.; Gunduz, D.
An End-To-End Analysis of Deep Learning-Based Remaining Useful Life Algorithms for Satefy-Critical 5G-Enabled IIoT Networks
2023 Amorosa, Lorenzo Mario; Longhi, Nicolò; Cuozzo, Giampaolo; Bachan, Weronika Maria; Lieti, Valerio; Buracchini, Enrico; Verdone, Roberto
Multi-Agent Reinforcement Learning for Power Control in Wireless Networks via Adaptive Graphs
2023 Amorosa, LORENZO MARIO; Skocaj, Marco; Verdone, Roberto; Gündüz, Deniz
Cellular network capacity and coverage enhancement with MDT data and Deep Reinforcement Learning
2022 Marco Skocaj; Lorenzo M. Amorosa; Giorgio Ghinamo; Giuliano Muratore; Davide Micheli; Flavio Zabini; Roberto Verdone
| Titolo | Autore(i) | Anno | Periodico | Editore | Tipo | File |
|---|---|---|---|---|---|---|
| 5G Architectures Enabling Remaining Useful Life Estimation for Industrial IoT: A Holistic Study | Longhi, Nicolò; Amorosa, Lorenzo Mario; Cavallero, Sara; Buracchini, Enrico; Verdone, Roberto | 2025-01-01 | IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY | - | 1.01 Articolo in rivista | 5G_Architectures_Enabling_Remaining_Useful_Life_Estimation_for_Industrial_IoT_A_Holistic_Study.pdf |
| GUMBLE: Uncertainty-Aware Conditional Mobile Data Generation using Bayesian Learning | Verdone, Roberto; Lombardi, Michele; Amorosa, Lorenzo Mario; Skocaj, Marco | 2024-01-01 | IEEE TRANSACTIONS ON MOBILE COMPUTING | - | 1.01 Articolo in rivista | 2024_GUMBLE_Uncertainty_Aware_Conditional_Mobile_Data_Generation.pdf |
| Multi-Agent Reinforcement Learning for Power Control in Wireless Networks via Adaptive Graphs | Amorosa, L. M.; Skocaj, M.; Verdone, R.; Gunduz, D. | 2024-01-01 | - | Institute of Electrical and Electronics Engineers Inc. | 4.01 Contributo in Atti di convegno | - |
| An End-To-End Analysis of Deep Learning-Based Remaining Useful Life Algorithms for Satefy-Critical 5G-Enabled IIoT Networks | Amorosa, Lorenzo Mario; Longhi, Nicolò; Cuozzo, Giampaolo; Bachan, Weronika Maria; Lieti, Valerio...; Buracchini, Enrico; Verdone, Roberto | 2023-01-01 | - | IEEE | 4.01 Contributo in Atti di convegno | - |
| Multi-Agent Reinforcement Learning for Power Control in Wireless Networks via Adaptive Graphs | Amorosa, LORENZO MARIO; Skocaj, Marco; Verdone, Roberto; Gündüz, Deniz | 2023-01-01 | - | - | 4.01 Contributo in Atti di convegno | - |
| Cellular network capacity and coverage enhancement with MDT data and Deep Reinforcement Learning | Marco Skocaj; Lorenzo M. Amorosa; Giorgio Ghinamo; Giuliano Muratore; Davide Micheli; Flavio Zabi...ni; Roberto Verdone | 2022-01-01 | COMPUTER COMMUNICATIONS | - | 1.01 Articolo in rivista | cellular network post print.pdf |