| 2025 | ESANN | Towards Efficient Molecular Property Optimization with Graph Energy Based Models. | Luca Miglior, Lorenzo Simone, Marco Podda, Davide Bacciu |
| 2025 | ICANN | Investigating Time-Scales in Deep Echo State Networks for Natural Language Processing. | Corrado Baccheschi, Alessandro Bondielli, Alessandro Lenci, Alessio Micheli, Lucia C. Passaro, Marco Podda, Domenico Tortorella |
| 2024 | DIS | Analyzing Explanations of Deep Graph Networks Through Node Centrality and Connectivity. | Michele Fontanesi, Alessio Micheli, Marco Podda, Domenico Tortorella |
| 2024 | ESANN | XAI and Bias of Deep Graph Networks. | Michele Fontanesi, Alessio Micheli, Marco Podda |
| 2023 | ESANN | Graph Representation Learning. | Davide Bacciu, Federico Errica, Alessio Micheli, Nicol Navarin, Luca Pasa, Marco Podda, Daniele Zambon |
| 2021 | IJCNN | Graphgen-redux: a Fast and Lightweight Recurrent Model for labeled Graph Generation. | Davide Bacciu, Marco Podda |
| 2020 | AISTATS | A Deep Generative Model for Fragment-Based Molecule Generation. | Marco Podda, Davide Bacciu, Alessio Micheli |
| 2020 | ESANN | Biochemical Pathway Robustness Prediction with Graph Neural Networks. | Marco Podda, Alessio Micheli, Davide Bacciu, Paolo Milazzo |
| 2020 | ICLR | A Fair Comparison of Graph Neural Networks for Graph Classification. | Federico Errica, Marco Podda, Davide Bacciu, Alessio Micheli |
| 2019 | ESANN | Graph generation by sequential edge prediction. | Davide Bacciu, Alessio Micheli, Marco Podda |