Michele Fontanesi

According to our database, Michele Fontanesi authored at least 12 papers between 2023 and 2025.

Collaborative distances:

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

2025

Sensitivity analysis on protein-protein interaction networks through deep graph networks.

Alessandro Dipalma, Michele Fontanesi, Alessio Micheli, Paolo Milazzo, Marco Podda

BMC Bioinform., December, 2025

Addressing the Scarcity of Benchmarks for Graph XAI.

Michele Fontanesi, Alessio Micheli, Marco Podda, Domenico Tortorella

CoRR, May, 2025

An Empirical Investigation of Shortcuts in Graph Learning.

Domenico Tortorella, Michele Fontanesi, Alessio Micheli, Marco Podda

Proceedings of the Graph-Based Representations in Pattern Recognition, 2025

2024

Dynamical Properties of PPI Networks (DyPPIN).

Alessandro Dipalma, Paolo Milazzo, Alessio Micheli, Michele Fontanesi, Marco Podda

Dataset, December, 2024

Sensitivity Prediction on Protein Protein Interaction Networks.

Alessandro Dipalma, Michele Fontanesi, Alessio Micheli, Paolo Milazzo, Marco Podda

Dataset, December, 2024

Explaining Graph Classifiers by Unsupervised Node Relevance Attribution.

Michele Fontanesi, Alessio Micheli, Marco Podda

Proceedings of the Explainable Artificial Intelligence, 2024

XAI and Bias of Deep Graph Networks.

Michele Fontanesi, Alessio Micheli, Marco Podda

Proceedings of the 32nd European Symposium on Artificial Neural Networks, 2024

Analyzing Explanations of Deep Graph Networks Through Node Centrality and Connectivity.

Michele Fontanesi, Alessio Micheli, Marco Podda, Domenico Tortorella

Proceedings of the Discovery Science - 27th International Conference, 2024

Exposing Inductive Biases of Deep Graph Networks through Explainable AI (Short paper).

Michele Fontanesi, Alessio Micheli, Marco Podda

Proceedings of the AIxIA Doctoral Consortium 2024 co-located with the 23rd International Conference of the Italian Association for Artificial Intelligence (AIxIA 2024), 2024

Relating Explanations with the Inductive Biases of Deep Graph Networks.

Michele Fontanesi, Alessio Micheli, Marco Podda

Proceedings of the AIxIA 2024 - Advances in Artificial Intelligence, 2024

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., October, 2023

Biochemical networks with simulation-based estimations of dynamical properties.

Michele Fontanesi, Paolo Milazzo, Alessio Micheli, Marco Podda

Dataset, June, 2023