Publications

Research Output & Scientific Contributions

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Explainable Artificial Intelligence in Drug Discovery

Proietti, M.; Astolfi, R.; Ragno, A.
Chapter in Lavecchia, A. (eds) Applied Artificial Intelligence for Drug Discovery. Springer, Cham, 2026
DOI
CIP-Net publication

CIP-Net: Continual Interpretable Prototype-based Network

Di Valerio, F.; Proietti, M.; Ragno, A.; Capobianco, R.
AAAI 2026
arXiv
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XAI-Guided Continual Learning: Rationale, Methods, and Future Directions

Proietti, M.; Ragno, A.; Capobianco, R.
WIREs Data Mining and Knowledge Discovery, 2025
DOI
NeurIPS 2025 publication

On Logic-based Self-Explainable Graph Neural Networks

Ragno, A.; Plantevit, M.; Robardet, C.
NeurIPS 2025
Paper
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Leveraging internal representations of GNNs with Shapley Values

Kamal, A.; Ragno, A.; Plantevit, M.; Robardet, C.
Data Mining and Knowledge Discovery, 2025
DOI
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Faithful Explanations for Graph Classification using Logic

Ragno, A.; Plantevit, M.; Robardet, C.
ECML-PKDD 2025
DOI
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IMPO: Interpretable Memory-based Prototypical Pooling

Ragno, A.; Capobianco, R.
WSDM 2025
DOI
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Essential Oils as Antimicrobials against Acinetobacter baumannii: Experimental and Literature Data to Definite Predictive Quantitative Composition–Activity Relationship Models Using Machine Learning Algorithms

Astolfi, R.; Oliva, A.; Raffo, A.; Sapienza, F.; Ragno, A.; Proia, E.; Mastroianni, C. M.; Luceri, C.; Bozovic, M.; Mladenovic, M.; Papa, R.; Bottoni, P.; Mazzinelli, E.; Nocca, G.; Ragno, R.
Journal of Chemical Information and Modeling, 2024
DOI
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Transparent Explainable Logic Layers

Ragno, A.; Plantevit, M.; Robardet, C; Capobianco, R.
ECAI 2024
DOI
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Identifying Candidates for Protein-Protein Interaction: A Focus on NKp46's Ligands

Borghini, A.; Di Valerio, F.; Ragno, A.; Capobianco, R.
CEUR Workshop Proceedings, 2024
PDF
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Memory Replay For Continual Learning With Spiking Neural Networks

Proietti, M.; Ragno, A.; Capobianco, R.
MLSP 2023
DOI
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Understanding Deep RL Agent Decisions: a Novel Interpretable Approach with Trainable Prototypes

Ragno, A.; La Rosa, B.; Capobianco, R.
XAI4RL Workshop, 2023
PDF
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Prototype-based Interpretable Graph Neural Networks

Ragno, A.; La Rosa, B.; Capobianco, R.
IEEE Transactions on Artificial Intelligence, 2022
DOI
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Explainable AI in drug design: self-interpretable graph neural network for molecular property prediction using concept whitening

Proietti, M.; Ragno, A.; Capobianco, R.
Journal of Cheminformatics, 2022
DOI
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Ligand-based and structure-based studies to develop predictive models for SARS-CoV-2 main protease inhibitors through the 3d-qsar.com portal

Proia, E.; Ragno, A.; Antonini, L.; Sabatino, M.; Mladenovič, M.; Capobianco, R.; Ragno, R.
Journal of Computer-Aided Molecular Design, 2022
DOI
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Machine Learning Data Augmentation as a Tool to Enhance Quantitative Composition–Activity Relationships of Complex Mixtures. A New Application to Dissect the Role of Main Chemical Components in Bioactive Essential Oils

Ragno, A.; Baldissarotto, A.; Antonini, L.; Sabatino, M.; Sapienza, F.; Baldini, E.; Buzzi, R.; Vertuani, S.; Manfredini, S.
Molecules, 2021
DOI
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Semi-Supervised GCN for learning Molecular Structure-Activity Relationships

Ragno, A.; Savoia, D.; Capobianco, R.
ELLIS Machine Learning for Molecules Workshop (ML4Molecules), 2021
arXiv