| 2026 | ESANN | Learning and Reasoning on Knowledge and Heterogeneous Graphs in the era of Graph Foundation and Large Language Models. | Matteo Zignani, Pasquale Minervini, Roberto Interdonato, Manuel Dileo |
| 2026 | PERCOM | A deep reinforcement learning agent for distributed task offloading based on Graph Neural Networks. | Manuel Dileo, Christian Quadri |
| 2025 | DSAA | A discrete-time deep learning framework for temporal heterogeneous networks forecasting. | Manuel Dileo, Matteo Zignani, Sabrina Gaito |
| 2025 | ESANN | Enhancing neural link predictors for temporal knowledge graphs with temporal regularisers. | Manuel Dileo, Pasquale Minervini, Matteo Zignani, Sabrina Gaito |
| 2025 | ESANN | Network Science Meets AI: A Converging Frontier. | Matteo Zignani, Fragkiskos D. Malliaros, Ingo Scholtes, Roberto Interdonato, Manuel Dileo |
| 2024 | DIS | Network-wide shocking events through the lens of node representation shift. | Manuel Dileo, Matteo Zignani |
| 2024 | ESANN | Link prediction heuristics for temporal graph benchmark. | Manuel Dileo, Matteo Zignani |
| 2024 | ICLR | Can Graph Neural Networks learn node-level structural features? | Manuel Dileo, Matteo Zignani |
| 2022 | DIS | Link Prediction with Text in Online Social Networks: The Role of Textual Content on High-Resolution Temporal Data. | Manuel Dileo, Cheick Tidiane Ba, Matteo Zignani, Sabrina Gaito |