Cloud and Local Servers for a Federation of Molecular Science Learning Object Repositories. - Sergio Tasso; Simonetta Pallottelli; Osvaldo Gervasi; Federico Sabbatini; Valentina Franzoni; Antonio Laganà (ICCSA (6), 2019)

Improvements to the G-Lorep Federation of Learning Object Repositories. - Federico Sabbatini; Sergio Tasso; Simonetta Pallottelli; Osvaldo Gervasi (ICCSA (7), 2020)

GridEx: An Algorithm for Knowledge Extraction from Black-Box Regressors. - Federico Sabbatini; Giovanni Ciatto; Andrea Omicini (EXTRAAMAS@AAMAS, 2021)

On the Design of PSyKE: A Platform for Symbolic Knowledge Extraction. - Federico Sabbatini; Giovanni Ciatto; Roberta Calegari; Andrea Omicini (WOA, 2021)

The PSyKE Technology for Trustworthy Artificial Intelligence. - Roberta Calegari; Federico Sabbatini (AI*IA, 2022)

Semantic Web-Based Interoperability for Intelligent Agents with PSyKE. - Federico Sabbatini; Giovanni Ciatto; Andrea Omicini (EXTRAAMAS@AAMAS, 2022)

Symbolic Knowledge Extraction from Opaque Machine Learning Predictors: GridREx & PEDRO. - Federico Sabbatini; Roberta Calegari (KR, 2022)

Hypercube-based methods for symbolic knowledge extraction: towards a unified model. - Federico Sabbatini; Giovanni Ciatto; Roberta Calegari; Andrea Omicini (WOA, 2022)

Symbolic Knowledge Extraction from Opaque Predictors Applied to Cosmic-Ray Data Gathered with LISA Pathfinder. - Federico Sabbatini; Catia Grimani (CoRR, 2022)

Clustering-Based Approaches for Symbolic Knowledge Extraction. - Federico Sabbatini; Roberta Calegari (CoRR, 2022)

Evaluation Metrics for Symbolic Knowledge Extracted from Machine Learning Black Boxes: A Discussion Paper. - Federico Sabbatini; Roberta Calegari (CoRR, 2022)

Symbolic knowledge extraction from opaque ML predictors in PSyKE: Platform design & experiments. - Federico Sabbatini; Giovanni Ciatto; Roberta Calegari; Andrea Omicini (Intelligenza Artificiale, 2022)

Unveiling Opaque Predictors via Explainable Clustering: The CReEPy Algorithm. - Federico Sabbatini; Roberta Calegari (BEWARE@AI*IA, 2023)

Symbolic Knowledge-Extraction Evaluation Metrics: The FiRe Score. - Federico Sabbatini; Roberta Calegari (ECAI, 2023)

Achieving Complete Coverage with Hypercube-Based Symbolic Knowledge-Extraction Techniques. - Federico Sabbatini; Roberta Calegari (ECAI Workshops (1), 2023)

Bottom-Up and Top-Down Workflows for Hypercube- And Clustering-Based Knowledge Extractors. - Federico Sabbatini; Roberta Calegari (EXTRAAMAS, 2023)

X-ray qualification of hydrogenated amorphous silicon sensors on flexible substrate. - Mauro Menichelli; Luca Antognini; Aishah Bashiri; Marco Bizzarri; Lucio Calcagnile; M. Caprai; Anna Paola Caricato; Roberto Catalano; Giuseppe Antonio Pablo Cirrone; Tommaso Croci; Giacomo Cuttone; Sylvain Dunand; et al. (IWASI, 2023)

ExACT Explainable Clustering: Unravelling the Intricacies of Cluster Formation. - Federico Sabbatini; Roberta Calegari (KoDis+CAKR@KR, 2023)

Explainable Clustering with CREAM. - Federico Sabbatini; Roberta Calegari (KR, 2023)

Unlocking Insights and Trust: The Value of Explainable Clustering Algorithms for Cognitive Agents. - Federico Sabbatini; Roberta Calegari (WOA, 2023)

Solar Wind Speed Estimate with Machine Learning Ensemble Models for LISA. - Federico Sabbatini; Catia Grimani (CoRR, 2023)

Towards a unified model for symbolic knowledge extraction with hypercube-based methods. - Federico Sabbatini; Giovanni Ciatto; Roberta Calegari; Andrea Omicini (Intelligenza Artificiale, 2023)

Unmasking the Shadows: Leveraging Symbolic Knowledge Extraction to Discover Biases and Unfairness in Opaque Predictive Models. - Federico Sabbatini; Roberta Calegari (AEQUITAS@ECAI, 2024)

ICE: An Evaluation Metric to Assess Symbolic Knowledge Quality. - Federico Sabbatini; Roberta Calegari (AI*IA, 2024)

Hierarchical Knowledge Extraction from Opaque Machine Learning Predictors. - Federico Sabbatini; Roberta Calegari (AI*IA, 2024)

Evaluating Machine Learning Models against Clinical Protocols for Enhanced Interpretability and Continuity of Care. - Christel Sirocchi; Muhammad Suffian Nizami; Federico Sabbatini; Alessandro Bogliolo; Sara Montagna (EXPLIMED@ECAI, 2024)

A Front-End Circuit in 28 nm CMOS for Hydrogenated Amorphous Silicon Detectors in Clinical Dosimetry. - Giovanni Mazza; Lorenzo Piccolo; Luca Antognini; Saba Aziz; Aishah Bashiri; Lucio Calcagnile; Daniela Calvo; Domenico Caputo; Anna Paola Caricato; Roberto Catalano; Roberto Cirio; Giuseppe Antonio Pablo Cirrone; et al. (MOCAST, 2024)

Symbolic Knowledge Comparison: Metrics and Methodologies for Multi-Agent Systems. - Federico Sabbatini; Christel Sirocchi; Roberta Calegari (WOA, 2024)

Untying black boxes with clustering-based symbolic knowledge extraction. - Federico Sabbatini; Roberta Calegari (Intelligenza Artificiale, 2024)

On the evaluation of the symbolic knowledge extracted from black boxes. - Federico Sabbatini; Roberta Calegari (AI Ethics, 2024)

Symbolic Knowledge Extraction and Injection with Sub-symbolic Predictors: A Systematic Literature Review. - Giovanni Ciatto; Federico Sabbatini; Andrea Agiollo; Matteo Magnini; Andrea Omicini (ACM Comput. Surv., 2024)