Alessio Ragno

According to our database, Alessio Ragno authored at least 18 papers between 2022 and 2026.

Collaborative distances:

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

2026

Differentiable parameter-less co-clustering using graph neural networks.

Alessio Ragno, Pierre-Angelo Peyrie, Marc Plantevit, Ruggero G. Pensa, Céline Robardet

Data Min. Knowl. Discov., August, 2026

LogiX-Me: Logic-based Self-Explainable Message Passing GNN.

Simone Palumbo, Alessio Ragno, Roberto Capobianco, Marc Plantevit, Céline Robardet

Proceedings of the Workshops of the EDBT/ICDT 2026 Joint Conference co-located with the EDBT/ICDT 2025 Joint Conference, 2026

CIP-Net: Continual Interpretable Prototype-based Network.

Federico Di Valerio, Michela Proietti, Alessio Ragno, Roberto Capobianco

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Leveraging internal representations of GNNs with Shapley values.

Ataollah Kamal, Alessio Ragno, Marc Plantevit, Céline Robardet

Data Min. Knowl. Discov., November, 2025

Topology-based explanations for neural networks.

Alessio Ragno

PhD thesis, 2025

Essential Oils as Antimicrobials against <i>Acinetobacter baumannii</i>: Experimental and Literature Data to Definite Predictive Quantitative Composition-Activity Relationship Models Using Machine Learning Algorithms.

Roberta Astolfi, Alessandra Oliva, Antonio Raffo, Filippo Sapienza, Alessio Ragno, Eleonora Proia, Claudio M. Mastroianni, Cristina Luceri, Mijat Bozovic, Milan Mladenovic, Rosanna Papa, Patrizia Bottoni, Elena Mazzinelli, Giuseppina Nocca, Rino Ragno

J. Chem. Inf. Model., 2025

IMPO: Interpretable Memory-based Prototypical Pooling.

Alessio Ragno, Roberto Capobianco

Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, 2025

Faithful Explanations for Graph Classification Using Logic.

Alessio Ragno, Marc Plantevit, Céline Robardet

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2025

On Logic-based Self-Explainable Graph Neural Networks.

Alessio Ragno, Marc Plantevit, Céline Robardet

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Prototype-Based Interpretable Graph Neural Networks.

Alessio Ragno, Biagio La Rosa, Roberto Capobianco

IEEE Trans. Artif. Intell., April, 2024

Explainable AI in drug discovery: self-interpretable graph neural network for molecular property prediction using concept whitening.

Michela Proietti, Alessio Ragno, Biagio La Rosa, Rino Ragno, Roberto Capobianco

Mach. Learn., April, 2024

Identifying Candidates for Protein-Protein Interaction: A Focus on NKp46's Ligands.

Alessia Borghini, Federico Di Valerio, Alessio Ragno, Roberto Capobianco

Proceedings of the First Workshop on Explainable Artificial Intelligence for the Medical Domain (EXPLIMED 2024) co-located with 27th European Conference on Artificial Intelligence (ECAI 2024), 2024

Transparent Explainable Logic Layers.

Alessio Ragno, Marc Plantevit, Céline Robardet, Roberto Capobianco

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

Memory Replay For Continual Learning With Spiking Neural Networks.

Michela Proietti, Alessio Ragno, Roberto Capobianco

Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Understanding Deep RL Agent Decisions: a Novel Interpretable Approach with Trainable Prototypes.

Caterina Borzillo, Alessio Ragno, Roberto Capobianco

Proceedings of the 4th Italian Workshop on Explainable Artificial Intelligence co-located with 22nd International Conference of the Italian Association for Artificial Intelligence(AIxIA 2023), 2023

2022

Ligand-based and structure-based studies to develop predictive models for SARS-CoV-2 main protease inhibitors through the 3d-qsar.com portal.

Eleonora Proia, Alessio Ragno, Lorenzo Antonini, Manuela Sabatino, Milan Mladenovic, Roberto Capobianco, Rino Ragno

J. Comput. Aided Mol. Des., 2022

Semi-Supervised GCN for learning Molecular Structure-Activity Relationships.

Alessio Ragno, Dylan Savoia, Roberto Capobianco

CoRR, 2022

Molecule Generation from Input-Attributions over Graph Convolutional Networks.

Dylan Savoia, Alessio Ragno, Roberto Capobianco

CoRR, 2022