Graph generation by sequential edge prediction. - Davide Bacciu; Alessio Micheli; Marco Podda (ESANN, 2019)

A Deep Generative Model for Fragment-Based Molecule Generation. - Marco Podda; Davide Bacciu; Alessio Micheli (AISTATS, 2020)

Prediction of Dynamical Properties of Biochemical Pathways with Graph Neural Networks. - Pasquale Bove; Alessio Micheli; Paolo Milazzo; Marco Podda (BIOINFORMATICS, 2020)

Classification of Biochemical Pathway Robustness with Neural Networks for Graphs. - Marco Podda; Pasquale Bove; Alessio Micheli; Paolo Milazzo (BIOSTEC (Selected Papers), 2020)

Biochemical Pathway Robustness Prediction with Graph Neural Networks. - Marco Podda; Alessio Micheli; Davide Bacciu; Paolo Milazzo (ESANN, 2020)

A Fair Comparison of Graph Neural Networks for Graph Classification. - Federico Errica; Marco Podda; Davide Bacciu; Alessio Micheli (ICLR, 2020)

Edge-based sequential graph generation with recurrent neural networks. - Davide Bacciu; Alessio Micheli; Marco Podda (Neurocomputing, 2020)

A gentle introduction to deep learning for graphs. - Davide Bacciu; Federico Errica; Alessio Micheli; Marco Podda (Neural Networks, 2020)

Graphgen-redux: a Fast and Lightweight Recurrent Model for labeled Graph Generation. - Davide Bacciu; Marco Podda (IJCNN, 2021)

Deep Learning on Graphs with Applications to the Life Sciences. - Marco Podda (2021)

Graph Representation Learning. - Davide Bacciu; Federico Errica; Alessio Micheli; Nicolò Navarin; Luca Pasa; Marco Podda; Daniele Zambon (ESANN, 2023)

Biochemical networks with simulation-based estimations of dynamical properties. - Michele Fontanesi; Paolo Milazzo; Alessio Micheli; Marco Podda (Zenodo, 2023)

Exploiting the structure of biochemical pathways to investigate dynamical properties with neural networks for graphs. - Michele Fontanesi; Alessio Micheli; Paolo Milazzo; Marco Podda (Bioinform., 2023)

Relating Explanations with the Inductive Biases of Deep Graph Networks. - Michele Fontanesi; Alessio Micheli; Marco Podda (AI*IA, 2024)

Exposing Inductive Biases of Deep Graph Networks through Explainable AI (Short paper). - Michele Fontanesi; Alessio Micheli; Marco Podda (DC@AI*IA, 2024)

How Much Do DNA and Protein Deep Embeddings Preserve Biological Information? - Matteo Tolloso; Silvia Giulia Galfrè; Arianna Pavone; Marco Podda; Alina Sîrbu; Corrado Priami (CMSB, 2024)

Analyzing Explanations of Deep Graph Networks Through Node Centrality and Connectivity. - Michele Fontanesi; Alessio Micheli; Marco Podda; Domenico Tortorella (DS (1), 2024)

XAI and Bias of Deep Graph Networks. - Michele Fontanesi; Alessio Micheli; Marco Podda (ESANN, 2024)

Classifier-Free Graph Diffusion for Molecular Property Targeting. - Matteo Ninniri; Marco Podda; Davide Bacciu (ECML/PKDD (4), 2024)

Explaining Graph Classifiers by Unsupervised Node Relevance Attribution. - Michele Fontanesi; Alessio Micheli; Marco Podda (xAI (2), 2024)

Deep Graph Networks for Drug Repurposing With Multi-Protein Targets. - Davide Bacciu; Federico Errica; Alessio Gravina; Lorenzo Madeddu; Marco Podda; Giovanni Stilo (IEEE Trans. Emerg. Top. Comput., 2024)

Sensitivity Prediction on Protein Protein Interaction Networks. - Alessandro Dipalma; Michele Fontanesi; Alessio Micheli; Paolo Milazzo; Marco Podda (Zenodo, 2024)

Dynamical Properties of PPI Networks (DyPPIN). - Alessandro Dipalma; Paolo Milazzo; Alessio Micheli; Michele Fontanesi; Marco Podda (Zenodo, 2024)

An Empirical Investigation of Shortcuts in Graph Learning. - Domenico Tortorella; Michele Fontanesi; Alessio Micheli; Marco Podda (GbRPR, 2025)

Towards Efficient Molecular Property Optimization with Graph Energy Based Models. - Luca Miglior; Lorenzo Simone; Marco Podda; Davide Bacciu (CoRR, 2025)

Learning to quantify graph nodes. - Alessio Micheli; Alejandro Moreo; Marco Podda; Fabrizio Sebastiani 001; William Simoni; Domenico Tortorella (CoRR, 2025)

Addressing the Scarcity of Benchmarks for Graph XAI. - Michele Fontanesi; Alessio Micheli; Marco Podda; Domenico Tortorella (CoRR, 2025)

Graph Diffusion that can Insert and Delete. - Matteo Ninniri; Marco Podda; Davide Bacciu (CoRR, 2025)

Sensitivity analysis on protein-protein interaction networks through deep graph networks. - Alessandro Dipalma; Michele Fontanesi; Alessio Micheli; Paolo Milazzo; Marco Podda (BMC Bioinform., 2025)