Reliable AI Through SVDD and Rule Extraction. - Alberto Carlevaro; Maurizio Mongelli (CD-MAKE, 2021)

On The Detection Of Adversarial Attacks Through Reliable AI. - Ivan Vaccari; Alberto Carlevaro; Sara Narteni; Enrico Cambiaso; Maurizio Mongelli (INFOCOM Workshops, 2022)

Characterization of Type 2 Diabetes Using Counterfactuals and Explainable AI. - Marta Lenatti; Alberto Carlevaro; Karim Keshavjee; Aziz Guergachi; Alessia Paglialonga; Maurizio Mongelli (MIE, 2022)

Counterfactual Building and Evaluation via eXplainable Support Vector Data Description. - Alberto Carlevaro; Marta Lenatti; Alessia Paglialonga; Maurizio Mongelli (IEEE Access, 2022)

eXplainable and Reliable Against Adversarial Machine Learning in Data Analytics. - Ivan Vaccari; Alberto Carlevaro; Sara Narteni; Enrico Cambiaso; Maurizio Mongelli (IEEE Access, 2022)

A New SVDD Approach to Reliable and Explainable AI. - Alberto Carlevaro; Maurizio Mongelli (IEEE Intell. Syst., 2022)

CONFIDERAI: CONFormal Interpretable-by-Design score function for Explainable and Reliable Artificial Intelligence. - Sara Narteni; Alberto Carlevaro; Fabrizio Dabbene; Marco Muselli; Maurizio Mongelli (COPA, 2023)

CONFIDERAI: a novel CONFormal Interpretable-by-Design score function for Explainable and Reliable Artificial Intelligence. - Alberto Carlevaro; Sara Narteni; Fabrizio Dabbene; Marco Muselli; Maurizio Mongelli (CoRR, 2023)

Probabilistic Safety Regions Via Finite Families of Scalable Classifiers. - Alberto Carlevaro; Teodoro Alamo; Fabrizio Dabbene; Maurizio Mongelli (CoRR, 2023)

Artichoke deep learning detection network for site-specific agrochemicals UAS spraying. - Alberto Sassu; Jacopo Motta; Alessandro Deidda; Luca Ghiani; Alberto Carlevaro; Giovanni Garibotto; Filippo Gambella (Comput. Electron. Agric., 2023)

A probabilistic scaling approach to conformal predictions in binary image classification. - Alberto Carlevaro; Sara Narteni; Fabrizio Dabbene; Teodoro Alamo; Maurizio Mongelli (COPA, 2024)

Ensuring Safe Social Navigation via Explainable Probabilistic and Conformal Safety Regions. - Sara Narteni; Alberto Carlevaro; Jérôme Guzzi; Maurizio Mongelli (xAI (4), 2024)

Mathematical Methods for eXplainable and Reliable Machine Learning in Trustworthy Artificial Intelligence. - Alberto Carlevaro (2024)

Multiclass Counterfactual Explanations Using Support Vector Data Description. - Alberto Carlevaro; Marta Lenatti; Alessia Paglialonga; Maurizio Mongelli (IEEE Trans. Artif. Intell., 2024)

Conformal predictions for probabilistically robust scalable machine learning classification. - Alberto Carlevaro; Teodoro Alamo; Fabrizio Dabbene; Maurizio Mongelli (Mach. Learn., 2024)

Provably Efficient and Robust Conformal Prediction under a Realistic Threat Model. - Alberto Carlevaro; Luca Oneto; Davide Anguita; Fabio Roli (COPA, 2025)

Physics-Aware Conformal Prediction for Deep Learning-based Wheelchair Local Navigation. - Sara Narteni; Alberto Carlevaro; Zeming Duan; Serge Autexier; Maurizio Mongelli (COPA, 2025)

Exact characterization of ε-Safe Decision Regions for exponential family distributions and Multi Cost SVM approximation. - Alberto Carlevaro; Teodoro Alamo; Fabrizio Dabbene; Maurizio Mongelli (CoRR, 2025)

Safe and Efficient Social Navigation through Explainable Safety Regions Based on Topological Features. - Víctor Toscano-Durán; Sara Narteni; Alberto Carlevaro; Rocío González-Díaz; Maurizio Mongelli; Jerome Guzzi (CoRR, 2025)

A novel score function for conformal prediction in rule-based binary classification. - Sara Narteni; Alberto Carlevaro; Fabrizio Dabbene; Marco Muselli; Maurizio Mongelli (Pattern Recognit., 2026)