Explainable Machine Learning in Industry 4.0: Evaluating Feature Importance in Anomaly Detection to Enable Root Cause Analysis. - Mattia Carletti; Chiara Masiero; Alessandro Beghi; Gian Antonio Susto (SMC, 2019)

Interpretable Anomaly Detection for Knowledge Discovery in Semiconductor Manufacturing. - Mattia Carletti; Marco Maggipinto; Alessandro Beghi; Gian Antonio Susto; Natalie Gentner; Yao Yang; Andreas Kyek (WSC, 2020)

Enhancing Scalability of Virtual Metrology: A Deep Learning-Based Approach for Domain Adaptation. - Natalie Gentner; Andreas Kyek; Yao Yang; Mattia Carletti; Gian Antonio Susto (WSC, 2020)

Algorithmic Audit of Italian Car Insurance: Evidence of Unfairness in Access and Pricing. - Alessandro Fabris; Alan Mishler; Stefano Gottardi; Mattia Carletti; Matteo Daicampi; Gian Antonio Susto; Gianmaria Silvello (AIES, 2021)

On the Properties of Adversarially-Trained CNNs. - Mattia Carletti; Matteo Terzi; Gian Antonio Susto (CoRR, 2022)

AcME - Accelerated model-agnostic explanations: Fast whitening of the machine-learning black box. - David Dandolo; Chiara Masiero; Mattia Carletti; Davide Dalle Pezze; Gian Antonio Susto (Expert Syst. Appl., 2023)

Interpretable Anomaly Detection with DIFFI: Depth-based feature importance of Isolation Forest. - Mattia Carletti; Matteo Terzi; Gian Antonio Susto (Eng. Appl. Artif. Intell., 2023)

Improving robustness with image filtering. - Matteo Terzi; Mattia Carletti; Gian Antonio Susto (Neurocomputing, 2024)

On the limitations of adversarial training for robust image classification with convolutional neural networks. - Mattia Carletti; Alberto Sinigaglia; Matteo Terzi; Gian Antonio Susto (Inf. Sci., 2024)