OptiLIME: Optimized LIME Explanations for Diagnostic Computer Algorithms. - Giorgio Visani; Enrico Bagli; Federico Chesani (CIKM (Workshops), 2020)

Metrics for Multi-Class Classification: an Overview. - Margherita Grandini; Enrico Bagli; Giorgio Visani (CoRR, 2020)

PSD2 Explainable AI Model for Credit Scoring. - Neus Llop Torrent; Giorgio Visani; Enrico Bagli (CoRR, 2020)

Explanations of Machine Learning predictions: a mandatory step for its application to Operational Processes. - Giorgio Visani; Federico Chesani; Enrico Bagli; Davide Capuzzo; Alessandro Poluzzi (CoRR, 2020)

Enabling Synthetic Data adoption in regulated domains. - Giorgio Visani; Giacomo Graffi; Mattia Alfero; Enrico Bagli; Federico Chesani; Davide Capuzzo (DSAA, 2022)

Statistical stability indices for LIME: Obtaining reliable explanations for machine learning models. - Giorgio Visani; Enrico Bagli; Federico Chesani; Alessandro Poluzzi; Davide Capuzzo (J. Oper. Res. Soc., 2022)

Meaningful insights: explainability techniques for black-box models on tabular data. - Giorgio Visani (2023)

GLEAMS: Bridging the Gap Between Local and Global Explanations. - Giorgio Visani; Vincenzo Stanzione; Damien Garreau (HI-AI@KDD, 2024)

Parallel approaches for a decision tree-based explainability algorithm. - Daniela Loreti; Giorgio Visani (Future Gener. Comput. Syst., 2024)