Region Merging Driven by Deep Learning for RGB-D Segmentation and Labeling. - Umberto Michieli; Maria Camporese; Andrea Agiollo; Giampaolo Pagnutti; Pietro Zanuttigh (ICDSC, 2019)

Shallow2Deep: Restraining Neural Networks Opacity Through Neural Architecture Search. - Andrea Agiollo; Giovanni Ciatto; Andrea Omicini (EXTRAAMAS@AAMAS, 2021)

Graph Neural Networks as the Copula Mundi between Logic and Machine Learning: a Roadmap. - Andrea Agiollo; Giovanni Ciatto; Andrea Omicini (WOA, 2021)

DETONAR: Detection of Routing Attacks in RPL-Based IoT. - Andrea Agiollo; Mauro Conti; Pallavi Kaliyar; Tsung-Nan Lin; Luca Pajola (IEEE Trans. Netw. Serv. Manag., 2021)

GNN2GNN: Graph neural networks to generate neural networks. - Andrea Agiollo; Andrea Omicini (UAI, 2022)

Towards quality-of-service metrics for symbolic knowledge injection. - Andrea Agiollo; Andrea Rafanelli; Andrea Omicini (WOA, 2022)

DETONAR-Light: An IoT Network Intrusion Detection Using DETONAR without a Sniffer Network. - Victoria Bull; Niclas Finne; Andrea Agiollo; Pallavi Kaliyar; Luca Pajola; Thiemo Voigt; Mauro Conti (ESORICS Workshops (2), 2023)

GNN4IFA: Interest Flooding Attack Detection With Graph Neural Networks. - Andrea Agiollo; Enkeleda Bardhi; Mauro Conti; Riccardo Lazzeretti; Eleonora Losiouk; Andrea Omicini (EuroS&P, 2023)

The Quarrel of Local Post-hoc Explainers for Moral Values Classification in Natural Language Processing. - Andrea Agiollo; Luciano Cavalcante Siebert; Pradeep Kumar Murukannaiah; Andrea Omicini (EXTRAAMAS, 2023)

Measuring Trustworthiness in Neuro-Symbolic Integration. - Andrea Agiollo; Andrea Omicini (FedCSIS, 2023)

Peer-Reviewed Federated Learning. - Mattia Passeri; Andrea Agiollo; Andrea Omicini (WOA, 2023)

Symbolic knowledge injection meets intelligent agents: QoS metrics and experiments. - Andrea Agiollo; Andrea Rafanelli; Matteo Magnini; Giovanni Ciatto; Andrea Omicini (Auton. Agents Multi Agent Syst., 2023)

Approximating Memorization Using Loss Surface Geometry for Dataset Pruning and Summarization. - Andrea Agiollo; Young In Kim; Rajiv Khanna (KDD, 2024)

An Empirical Study on the Robustness of Knowledge Injection Techniques Against Data Degradation. - Andrea Rafanelli; Matteo Magnini; Andrea Agiollo; Giovanni Ciatto; Andrea Omicini (WOA, 2024)

EneA-FL: Energy-aware orchestration for serverless federated learning. - Andrea Agiollo; Paolo Bellavista; Matteo Mendula; Andrea Omicini (Future Gener. Comput. Syst., 2024)

Embedding AI into constrained devices: a multi-faceted approach. - Andrea Agiollo (2024)

Anonymous Federated Learning via Named-Data Networking. - Andrea Agiollo; Enkeleda Bardhi; Mauro Conti; Nicolò Dal Fabbro; Riccardo Lazzeretti (Future Gener. Comput. Syst., 2024)

Symbolic Knowledge Extraction and Injection with Sub-symbolic Predictors: A Systematic Literature Review. - Giovanni Ciatto; Federico Sabbatini; Andrea Agiollo; Matteo Magnini; Andrea Omicini (ACM Comput. Surv., 2024)

From large language models to small logic programs: building global explanations from disagreeing local post-hoc explainers. - Andrea Agiollo; Luciano Cavalcante Siebert; Pradeep K. Murukannaiah; Andrea Omicini (Auton. Agents Multi Agent Syst., 2024)

Large language models as oracles for instantiating ontologies with domain-specific knowledge. - Giovanni Ciatto; Andrea Agiollo; Matteo Magnini; Andrea Omicini (Knowl. Based Syst., 2025)