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Federico Sabbatini
- Bridging machine learning and diagnostics of the ESA LISA space mission with equation discovery via explainable artificial intelligence (Advances in Space Research, 2024) — Federico Sabbatini, Catia Grimani, Roberta Calegari
- Untying black boxes with clustering-based symbolic knowledge extraction (Intelligenza Artificiale, 2024) — Federico Sabbatini, Roberta Calegari
- On the Evaluation of the Symbolic Knowledge Extracted from Black Boxes (AI and Ethics, 2024) — Federico Sabbatini, Roberta Calegari
- Symbolic Knowledge Extraction and Injection with Sub-symbolic Predictors: A Systematic Literature Review (ACM Computing Surveys, 2024) — Giovanni Ciatto, Federico Sabbatini, Andrea Agiollo, Matteo Magnini, Andrea Omicini
- Towards a Unified Model for Symbolic Knowledge Extraction with Hypercube-Based Methods (Intelligenza Artificiale, 2023) — Federico Sabbatini, Giovanni Ciatto, Roberta Calegari, Andrea Omicini
- Symbolic knowledge extraction from opaque ML predictors in PSyKE: Platform design & experiments (Intelligenza Artificiale, 2022) — Federico Sabbatini, Giovanni Ciatto, Roberta Calegari, Andrea Omicini
- Recurrent Galactic Cosmic-Ray Flux Modulation in L1 and Geomagnetic Activity during the Declining Phase of the Solar Cycle 24 (The Astrophysical Journal, 2020) — Catia Grimani, Andrea Cesarini, Michele Fabi, Federico Sabbatini, Daniele Telloni, Mattia Villani
- Characteristics and Energy Dependence of Recurrent Galactic Cosmic-Ray Flux Depressions and of a Forbush Decrease with LISA Pathfinder (The Astrophysical Journal, 2018) — M. Armano, H. Audley, J. Baird, M. Bassan, S. Benella, P. Binetruy, M. Born, D. Bortoluzzi, A. Cavalleri, A. Cesarini, A. M. Cruise, K. Danzmann, K. de Deus Silva, I. Diepholz, G. Dixon, R. Dolesi, M. Fabi, L. Ferraioli, V. Ferroni, N. Finetti, E. D. Fitzsimons, M. Freschi, L. Gesa, F. Gibert, D. Giardini, R. Giusteri, C. Grimani, J. Grzymisch, I. Harrison, G. Heinzel, M. Hewitson, D. Hollington, D. Hoyland, M. Hueller, H. Inchauspé, O. Jennrich, P. Jetzer, N. Karnesis, B. Kaune, N. Korsakova, C. J. Killow, M. Laurenza, J. A. Lobo, I. Lloro, L. Liu, J. P. López-Zaragoza, R. Maarschalkerweerd, D. Mance, V. Martín, L. Martin-Polo, J. Martino, F. Martin-Porqueras, I. Mateos, P. W. McNamara, J. Mendes, L. Mendes, M. Nofrarias, S. Paczkowski, M. Perreur-Lloyd, A. Petiteau, P. Pivato, E. Plagnol, J. Ramos-Castro, J. Reiche, D. I. Robertson, F. Rivas, G. Russano, Federico Sabbatini, J. Slutsky, C. F. Sopuerta, T. Sumner, D. Tellon, D. Texier, J. I. Thorpe, D. Vetrugno, S. Vitale, G. Wanner, H. Ward, P. Wass, W. J. Weber, L. Wissel, A. Wittchen, A. Zambotti, C. Zanoni, P. Zweifel
8 articoli in rivista •
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- ICE: An Evaluation Metric to Assess Symbolic Knowledge Quality (AIxIA 2024) — Federico Sabbatini, Roberta Calegari
- Hierarchical Knowledge Extraction from Opaque Machine Learning Predictors (AIxIA 2024) — Federico Sabbatini, Roberta Calegari
- Symbolic Knowledge Comparison: Metrics and Methodologies for Multi-Agent Systems (WOA 2024) — Federico Sabbatini, Christel Sirocchi, Roberta Calegari
- Unmasking the Shadows: Leveraging Symbolic Knowledge Extraction to Discover Biases and Unfairness in Opaque Predictive Models (AEQUITAS 2024) — Federico Sabbatini, Roberta Calegari
- Explainable Clustering with CREAM (KR 2023) — Federico Sabbatini, Roberta Calegari
- Symbolic Knowledge-Extraction Evaluation Metrics: The FiRe Score (ECAI-2023) — Federico Sabbatini, Roberta Calegari
- Unlocking Insights and Trust: The Value of Explainable Clustering Algorithms for Cognitive Agents (WOA 2023) — Federico Sabbatini, Roberta Calegari
- The PSyKE Technology for Trustworthy Artificial Intelligence (AIxIA 2022) — Roberta Calegari, Federico Sabbatini
- Unveiling Opaque Predictors via Explainable Clustering: The CReEPy Algorithm (2023) — Federico Sabbatini, Roberta Calegari
- ExACT Explainable Clustering: Unravelling the Intricacies of Cluster Formation (KoDis 2023 @ KR 2023) — Federico Sabbatini, Roberta Calegari
- Achieving Complete Coverage with Hypercube-Based Symbolic Knowledge-Extraction Techniques (ECAI-2023) — Federico Sabbatini, Roberta Calegari
- Bottom-Up and Top-Down Workflows for Hypercube- and Clustering-based Knowledge Extractors (EXTRAAMAS 2023 @ AAMAS 2023) — Federico Sabbatini, Roberta Calegari
- Hypercube-Based Methods for Symbolic Knowledge Extraction: Towards a Unified Model (WOA 2022) — Federico Sabbatini, Giovanni Ciatto, Roberta Calegari, Andrea Omicini
- Evaluation Metrics for Symbolic Knowledge Extracted from Machine Learning Black Boxes: A Discussion Paper (2022) — Federico Sabbatini, Roberta Calegari
- Semantic Web-based Interoperability for Intelligent Agents with PSyKE (EXTRAAMAS 2022 @ AAMAS 2022) — Federico Sabbatini, Giovanni Ciatto, Andrea Omicini
- Symbolic Knowledge Extraction from Opaque Machine Learning Predictors: GridREx & PEDRO (KR 2022) — Federico Sabbatini, Roberta Calegari
- Clustering-Based Approaches for Symbolic Knowledge Extraction (2022) — Federico Sabbatini, Roberta Calegari
- GridEx: An Algorithm for Knowledge Extraction from Black-Box Regressors (EXTRAAMAS 2021 @ AAMAS 2021) — Federico Sabbatini, Giovanni Ciatto, Andrea Omicini
- On the Design of PSyKE: A Platform for Symbolic Knowledge Extraction (WOA 2021) — Federico Sabbatini, Giovanni Ciatto, Roberta Calegari, Andrea Omicini
19 articoli in atti •
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1 capitolo di libro •
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0000-0002-0532-6777