Matteo Rizzo

According to our database, Matteo Rizzo authored at least 12 papers between 2019 and 2024.

Collaborative distances:

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

2024

Evaluating the Faithfulness of Causality in Saliency-Based Explanations of Deep Learning Models for Temporal Colour Constancy.

Matteo Rizzo, Cristina Conati, Daesik Jang, Hui Hu

Proceedings of the Explainable Artificial Intelligence, 2024

A Comparison of Machine Learning Techniques for Ethereum Smart Contract Vulnerability Detection.

Matteo Rizzo, Dalila Ressi, Andrea Gasparetto, Sabina Rossi

Proceedings of the Short Paper Proceedings of the 6th International Workshop on Artificial Intelligence and Formal Verification, 2024

On the Application of a Common Theoretical Explainability Framework in Information Retrieval.

Andrea Albarelli, Claudio Lucchese, Matteo Rizzo, Alberto Veneri

Proceedings of the 14th Italian Information Retrieval Workshop, 2024

Stop Overkilling Simple Tasks with Black-Box Models, Use More Transparent Models Instead.

Matteo Rizzo, Matteo Marcuzzo, Alessandro Zangari, Michele Schiavinato, Andrea Albarelli, Andrea Gasparetto

Proceedings of the Pattern Recognition and Artificial Intelligence, 2024

Crossing the Divide: Designing Layers of Explainability.

Alessandro Zangari, Matteo Marcuzzo, Matteo Rizzo, Andrea Albarelli, Andrea Gasparetto

Proceedings of the Artificial Intelligence and Soft Computing, 2024

2023

Cascading convolutional temporal color constancy.

Matteo Rizzo, Cristina Conati, Daesik Jang, Hui Hu

J. Electronic Imaging, 2023

A Theoretical Framework for AI Models Explainability with Application in Biomedicine.

Matteo Rizzo, Alberto Veneri, Andrea Albarelli, Claudio Lucchese, Marco S. Nobile, Cristina Conati

Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2023

2022

A Theoretical Framework for AI Models Explainability.

Matteo Rizzo, Alberto Veneri, Andrea Albarelli, Claudio Lucchese, Cristina Conati

CoRR, 2022

Fruit Ripeness Classification: a Survey.

Matteo Rizzo, Matteo Marcuzzo, Alessandro Zangari, Andrea Gasparetto, Andrea Albarelli

CoRR, 2022

Evaluating the Faithfulness of Saliency-based Explanations for Deep Learning Models for Temporal Colour Constancy.

Matteo Rizzo, Cristina Conati, Daesik Jang, Hui Hu

CoRR, 2022

2021

Cascading Convolutional Temporal Colour Constancy.

Matteo Rizzo, Cristina Conati, Daesik Jang, Hui Hu

CoRR, 2021

2019

Verifying software network functions with no verification expertise.

Arseniy Zaostrovnykh, Solal Pirelli, Rishabh R. Iyer, Matteo Rizzo, Luis Pedrosa, Katerina J. Argyraki, George Candea

Proceedings of the 27th ACM Symposium on Operating Systems Principles, 2019