Verifying software network functions with no verification expertise. - Arseniy Zaostrovnykh; Solal Pirelli; Rishabh R. Iyer; Matteo Rizzo; Luis Pedrosa; Katerina J. Argyraki; George Candea (SOSP, 2019)

Cascading Convolutional Temporal Colour Constancy. - Matteo Rizzo; Cristina Conati; Daesik Jang; Hui Hu (CoRR, 2021)

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)

Fruit Ripeness Classification: a Survey. - Matteo Rizzo; Matteo Marcuzzo; Alessandro Zangari; Andrea Gasparetto; Andrea Albarelli (CoRR, 2022)

A Theoretical Framework for AI Models Explainability. - Matteo Rizzo; Alberto Veneri; Andrea Albarelli; Claudio Lucchese; Cristina Conati (CoRR, 2022)

A Theoretical Framework for AI Models Explainability with Application in Biomedicine. - Matteo Rizzo; Alberto Veneri; Andrea Albarelli; Claudio Lucchese; Marco S. Nobile; Cristina Conati (CIBCB, 2023)

Cascading convolutional temporal color constancy. - Matteo Rizzo; Cristina Conati; Daesik Jang; Hui Hu (J. Electronic Imaging, 2023)

Crossing the Divide: Designing Layers of Explainability. - Alessandro Zangari; Matteo Marcuzzo; Matteo Rizzo; Andrea Albarelli; Andrea Gasparetto (ICAISC (1), 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 (ICPRAI (1), 2024)

On the Application of a Common Theoretical Explainability Framework in Information Retrieval. - Andrea Albarelli; Claudio Lucchese; Matteo Rizzo; Alberto Veneri (IIR, 2024)

A Comparison of Machine Learning Techniques for Ethereum Smart Contract Vulnerability Detection. - Matteo Rizzo; Dalila Ressi; Andrea Gasparetto; Sabina Rossi (OVERLAY, 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 (xAI (3), 2024)