Lorenzo Mario Amorosa

According to our database, Lorenzo Mario Amorosa authored at least 8 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Reconstruction of Sparse Urban Wireless Signals via Group Equivariant Non-Expansive Operators.

Lorenzo Mario Amorosa, Francesco Conti, Nicola Quercioli, Flavio Zabini, Tayebeh Lotfi Mahyari, Yiqun Ge, Patrizio Frosini

CoRR, July, 2025

5G Architectures Enabling Remaining Useful Life Estimation for Industrial IoT: A Holistic Study.

Nicolò Longhi, Lorenzo Mario Amorosa, Sara Cavallero, Enrico Buracchini, Roberto Verdone

IEEE Open J. Commun. Soc., 2025

Path Selection Based on Network Service Quality for Infrastructure-Assisted Automated Driving.

Andrea Giovannini, Claudia Campolo, Vittorio Todisco, Antonella Molinaro, Lorenzo Mario Amorosa, Lu Lei, Alessandro Bazzi

Proceedings of the 2025 IEEE Wireless Communications and Networking Conference (WCNC), 2025

Goal-Oriented Uplink Scheduling Requests in Wireless Networks via Graph Neural Networks.

Lorenzo Mario Amorosa, Leonardo Spampinato, Chiara Buratti, Roberto Verdone

Proceedings of the 21st IEEE International Conference on Smart Technologies, 2025

2024

GUMBLE: Uncertainty-Aware Conditional Mobile Data Generation Using Bayesian Learning.

Marco Skocaj, Lorenzo Mario Amorosa, Michele Lombardi, Roberto Verdone

IEEE Trans. Mob. Comput., December, 2024

Multi-Agent Reinforcement Learning for Power Control in Wireless Networks via Adaptive Graphs.

Lorenzo Mario Amorosa, Marco Skocaj, Roberto Verdone, Deniz Gündüz

Proceedings of the IEEE International Conference on Communications, 2024

2023

An End-To-End Analysis of Deep Learning-Based Remaining Useful Life Algorithms for Satefy-Critical 5G-Enabled IIoT Networks.

Lorenzo Mario Amorosa, Nicolò Longhi, Giampaolo Cuozzo, Weronika Maria Bachan, Valerio Lieti, Enrico Buracchini, Roberto Verdone

Proceedings of the 34th IEEE Annual International Symposium on Personal, 2023

2022

Cellular Network Capacity and Coverage Enhancement with MDT Data and Deep Reinforcement Learning.

Marco Skocaj, Lorenzo Mario Amorosa, Giorgio Ghinamo, Giuliano Muratore, Davide Micheli, Flavio Zabini, Roberto Verdone

Comput. Commun., 2022