Learning Łukasiewicz Logic Fragments by Quadratic Programming. - Francesco Giannini; Michelangelo Diligenti; Marco Gori; Marco Maggini (ECML/PKDD (1), 2017)

Neural Networks for Beginners. A fast implementation in Matlab, Torch, TensorFlow. - Francesco Giannini; Vincenzo Laveglia; Alessandro Rossi 002; Dario Zanca; Andrea Zugarini (CoRR, 2017)

Characterization of the Convex Łukasiewicz Fragment for Learning From Constraints. - Francesco Giannini; Michelangelo Diligenti; Marco Gori; Marco Maggini (AAAI, 2018)

Conditions for Unnecessary Logical Constraints in Kernel Machines. - Francesco Giannini; Marco Maggini (ICANN (2), 2019)

Constraint-Based Visual Generation. - Giuseppe Marra; Francesco Giannini; Michelangelo Diligenti; Marco Gori (ICANN (3), 2019)

On the Relation Between Loss Functions and T-Norms. - Francesco Giannini; Giuseppe Marra; Michelangelo Diligenti; Marco Maggini; Marco Gori (ILP, 2019)

LYRICS: A General Interface Layer to Integrate Logic Inference and Deep Learning. - Giuseppe Marra; Francesco Giannini; Michelangelo Diligenti; Marco Gori (ECML/PKDD (2), 2019)

Integrating Learning and Reasoning with Deep Logic Models. - Giuseppe Marra; Francesco Giannini; Michelangelo Diligenti; Marco Gori (ECML/PKDD (2), 2019)

LYRICS: a General Interface Layer to Integrate AI and Deep Learning. - Giuseppe Marra; Francesco Giannini; Michelangelo Diligenti; Marco Gori (CoRR, 2019)

Learning and T-Norms Theory. - Giuseppe Marra; Francesco Giannini; Michelangelo Diligenti; Marco Maggini; Marco Gori (CoRR, 2019)

On a Convex Logic Fragment for Learning and Reasoning. - Francesco Giannini; Michelangelo Diligenti; Marco Gori; Marco Maggini (IEEE Trans. Fuzzy Syst., 2019)

A Constraint-Based Approach to Learning and Explanation. - Gabriele Ciravegna; Francesco Giannini; Stefano Melacci; Marco Maggini; Marco Gori (AAAI, 2020)

Relational Neural Machines. - Giuseppe Marra; Michelangelo Diligenti; Francesco Giannini; Marco Gori; Marco Maggini (ECAI, 2020)

Inference in relational neural machines. - Giuseppe Marra; Francesco Giannini; Lapo Faggi; Michelangelo Diligenti; Marco Gori; Marco Maggini (NeHuAI@ECAI, 2020)

Human-Driven FOL Explanations of Deep Learning. - Gabriele Ciravegna; Francesco Giannini; Marco Gori; Marco Maggini; Stefano Melacci (IJCAI, 2020)

LENs: a Python library for Logic Explained Networks. - Pietro Barbiero; Gabriele Ciravegna; Dobrik Georgiev; Francesco Giannini (CoRR, 2021)

Learning Representations for Sub-Symbolic Reasoning. - Giuseppe Marra; Michelangelo Diligenti; Francesco Giannini; Marco Maggini (CoRR, 2021)

A Constraint-Based Approach to Learning and Reasoning. - Michelangelo Diligenti; Francesco Giannini; Marco Gori; Marco Maggini; Giuseppe Marra (Neuro-Symbolic Artificial Intelligence, 2021)

Entropy-Based Logic Explanations of Neural Networks. - Pietro Barbiero; Gabriele Ciravegna; Francesco Giannini; Pietro Lió; Marco Gori; Stefano Melacci (AAAI, 2022)

A Deep Q Learning-Model Predictive Control Approach to vehicle routing and control with platoon constraints. - Francesco Giannini; Giancarlo Fortino; Giuseppe Franzè; Francesco Pupo (CASE, 2022)

Path planning for vehicle platoons under routing decisions: a distributed approach combining Deep Reinforcement Learning and Model Predictive Control. - Francesco Giannini; Giancarlo Fortino; Giuseppe Franzè; Francesco Pupo (CoDIT, 2022)

Autonomous Vehicles in Smart Cities: a Deep Reinforcement Learning Solution. - Francesco Giannini; Giuseppe Franzè; Francesco Pupo; Giancarlo Fortino (DASC/PiCom/CBDCom/CyberSciTech, 2022)

Extending Logic Explained Networks to Text Classification. - Rishabh Jain; Gabriele Ciravegna; Pietro Barbiero; Francesco Giannini; Davide Buffelli; Pietro Liò (EMNLP, 2022)

Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off. - Mateo Espinosa Zarlenga; Pietro Barbiero; Gabriele Ciravegna; Giuseppe Marra; Francesco Giannini; Michelangelo Diligenti; Zohreh Shams; Frédéric Precioso; Stefano Melacci; Adrian Weller; Pietro Lió; Mateja Jamnik (NeurIPS, 2022)

Concept Embedding Models. - Mateo Espinosa Zarlenga; Pietro Barbiero; Gabriele Ciravegna; Giuseppe Marra; Francesco Giannini; Michelangelo Diligenti; Zohreh Shams; Frédéric Precioso; Stefano Melacci; Adrian Weller; Pietro Liò; Mateja Jamnik (CoRR, 2022)

A Neural Network and Model Predictive Control Based Resilient Architecture for Constrained Cyber-Physical Systems. - Luigi D'Alfonso; Giuseppe Franzè; Francesco Giannini; Francesco Tedesco (CoDIT, 2023)

A Set-Theoretic Receding Horizon Control Based on a Q-Learning Approach for Sustainability Purposes. - Francesco Giannini; Giuseppe Franzè; Francesco Pupo; Giancarlo Fortino (CoDIT, 2023)

Set-theoretic receding horizon control for nonlinear systems: a data-driven approach. - Francesco Giannini; Giuseppe Franzè; Francesco Pupo; Giancarlo Fortino (EUROCON, 2023)

Enhancing Embedding Representations of Biomedical Data using Logic Knowledge. - Michelangelo Diligenti; Francesco Giannini; Stefano Fioravanti; Caterina Graziani; Moreno Falaschi; Giuseppe Marra (IJCNN, 2023)

Linguistic Feature Injection for Efficient Natural Language Processing. - Stefano Fioravanti; Andrea Zugarini; Francesco Giannini; Leonardo Rigutini; Marco Maggini; Michelangelo Diligenti (IJCNN, 2023)

Interpretable Neural-Symbolic Concept Reasoning. - Pietro Barbiero; Gabriele Ciravegna; Francesco Giannini; Mateo Espinosa Zarlenga; Lucie Charlotte Magister; Alberto Tonda; Pietro Liò; Frédéric Precioso; Mateja Jamnik; Giuseppe Marra (NeSy, 2023)

Logic Explained Networks. - Gabriele Ciravegna; Pietro Barbiero; Francesco Giannini; Marco Gori; Pietro Liò; Marco Maggini; Stefano Melacci (NeSy, 2023)

Interpretable Graph Networks Formulate Universal Algebra Conjectures. - Francesco Giannini; Stefano Fioravanti; Oguzhan Keskin; Alisia Maria Lupidi; Lucie Charlotte Magister; Pietro Lió; Pietro Barbiero (NeurIPS, 2023)

Bridging Equational Properties and Patterns on Graphs: an AI-Based Approach. - Oguzhan Keskin; Alisia Maria Lupidi; Stefano Fioravanti; Lucie Charlotte Magister; Pietro Barbiero; Pietro Lio; Francesco Giannini (TAG-ML, 2023)

Categorical Foundations of Explainable AI: A Unifying Formalism of Structures and Semantics. - Pietro Barbiero; Stefano Fioravanti; Francesco Giannini; Alberto Tonda; Pietro Liò; Elena Di Lavore (CoRR, 2023)

Relational Concept Based Models. - Pietro Barbiero; Francesco Giannini; Gabriele Ciravegna; Michelangelo Diligenti; Giuseppe Marra (CoRR, 2023)

Learning Logic Explanations by Neural Networks. - Gabriele Ciravegna; Francesco Giannini; Pietro Barbiero; Marco Gori; Pietro Lio; Marco Maggini; Stefano Melacci (Compendium of Neurosymbolic Artificial Intelligence, 2023)

T-norms driven loss functions for machine learning. - Francesco Giannini; Michelangelo Diligenti; Marco Maggini; Marco Gori; Giuseppe Marra (Appl. Intell., 2023)

A Sustainable Multi-Agent Routing Algorithm for Vehicle Platoons in Urban Networks. - Francesco Giannini; Giuseppe Franzè; Francesco Pupo; Giancarlo Fortino (IEEE Trans. Intell. Transp. Syst., 2023)

A multi-tiered control framework designed for managing the logistical activities of self-driving vehicles within manufacturing environments. - Domenico Famularo; Giuseppe Franzè; Francesco Giannini; Francesco Pupo; Giancarlo Fortino; Francesco Tedesco (CASE, 2024)

A distributed control architecture for sustainable routing decisions of autonomous vehicle platoons subject to cyber attacks. - Domenico Famularo; Francesco Giannini; Giancarlo Fortino; Giuseppe Franzè (CoDIT, 2024)

Tomorrow Brings Greater Knowledge: Large Language Models Join Dynamic Temporal Knowledge Graphs. - Christian Di Maio; Andrea Zugarini; Francesco Giannini; Marco Maggini; Stefano Melacci (CoLLAs, 2024)

Logically Explainable Malware Detection. - Peter Anthony; Francesco Giannini; Michelangelo Diligenti; Marco Gori; Martin Homola; Stefan Balogh; Ján Mojzis (HI-AI@KDD, 2024)

Workshop on Human-Interpretable AI. - Gabriele Ciravegna; Mateo Espinosa Zarlenga; Pietro Barbiero; Francesco Giannini; Zohreh Shams; Damien Garreau; Mateja Jamnik; Tania Cerquitelli (KDD, 2024)

Relational Concept Bottleneck Models. - Pietro Barbiero; Francesco Giannini; Gabriele Ciravegna; Michelangelo Diligenti; Giuseppe Marra (NeurIPS, 2024)

Interpretable Concept-Based Memory Reasoning. - David Debot; Pietro Barbiero; Francesco Giannini; Gabriele Ciravegna; Michelangelo Diligenti; Giuseppe Marra (NeurIPS, 2024)

AnyCBMs: How to Turn Any Black Box into a Concept Bottleneck Model. - Gabriele Dominici; Pietro Barbiero; Francesco Giannini; Martin Gjoreski; Marc Langheinrich (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2024)

Categorical Foundation of Explainable AI: A Unifying Theory. - Francesco Giannini; Stefano Fioravanti; Pietro Barbiero; Alberto Tonda; Pietro Liò; Elena Di Lavore (xAI (3), 2024)

Climbing the Ladder of Interpretability with Counterfactual Concept Bottleneck Models. - Gabriele Dominici; Pietro Barbiero; Francesco Giannini; Martin Gjoreski; Giuseppe Marra; Marc Langheinrich (CoRR, 2024)

Explainable Malware Detection with Tailored Logic Explained Networks. - Peter Anthony; Francesco Giannini; Michelangelo Diligenti; Martin Homola; Marco Gori; Stefan Balogh; Ján Mojzis (CoRR, 2024)

Autonomous Vehicle Platoons in Urban Road Networks: A Joint Distributed Reinforcement Learning and Model Predictive Control Approach. - Luigi D'Alfonso; Francesco Giannini; Giuseppe Franzè; Giuseppe Fedele; Francesco Pupo; Giancarlo Fortino (IEEE CAA J. Autom. Sinica, 2024)

A Data-Driven Approach to Set-Theoretic Model Predictive Control for Nonlinear Systems. - Francesco Giannini; Domenico Famularo (Inf., 2024)

Embedding the State Trajectories of Nonlinear Systems via Multimodel Linear Descriptions: A Data-Driven-Based Algorithm. - Giuseppe Franzè; Francesco Giannini; Vicenç Puig; Giancarlo Fortino (IEEE Trans. Syst. Man Cybern. Syst., 2024)

Counterfactual Concept Bottleneck Models. - Gabriele Dominici; Pietro Barbiero; Francesco Giannini; Martin Gjoreski; Giuseppe Marra; Marc Langheinrich (ICLR, 2025)

Grounding Methods for Neural-Symbolic AI. - Rodrigo Castellano Ontiveros; Francesco Giannini; Marco Gori; Giuseppe Marra; Michelangelo Diligenti (IJCAI, 2025)

Mathematical Foundation of Interpretable Equivariant Surrogate Models. - Jacopo Joy Colombini; Filippo Bonchi; Francesco Giannini; Fosca Giannotti; Roberto Pellungrini; Patrizio Frosini (xAI (2), 2025)

Interpretable Link Prediction via Neural-Symbolic Reasoning. - Rodrigo Castellano Ontiveros; Ehsan Bonabi Mobaraki; Francesco Giannini; Pietro Barbiero; Marco Gori; Michelangelo Diligenti (xAI (2), 2025)

Relational reasoning networks. - Giuseppe Marra; Michelangelo Diligenti; Francesco Giannini (Knowl. Based Syst., 2025)

An Intelligent Multi-Layer Control Architecture for Logistics Operations of Autonomous Vehicles in Manufacturing Systems. - Domenico Famularo; Giancarlo Fortino; Francesco Pupo; Francesco Giannini; Giuseppe Franzè (IEEE Trans Autom. Sci. Eng., 2025)

Neural Interpretable Reasoning. - Pietro Barbiero; Giuseppe Marra; Gabriele Ciravegna; David Debot; Francesco De Santis; Michelangelo Diligenti; Mateo Espinosa Zarlenga; Francesco Giannini (CoRR, 2025)

Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts. - Andrea Pugnana; Riccardo Massidda; Francesco Giannini; Pietro Barbiero; Mateo Espinosa Zarlenga; Roberto Pellungrini; Gabriele Dominici; Fosca Giannotti; Davide Bacciu (CoRR, 2025)

Logic Explanation of AI Classifiers by Categorical Explaining Functors. - Stefano Fioravanti; Francesco Giannini; Paolo Frazzetto; Fabio Zanasi; Pietro Barbiero (CoRR, 2025)

If Concept Bottlenecks are the Question, are Foundation Models the Answer? - Nicola Debole; Pietro Barbiero; Francesco Giannini; Andrea Passerini; Stefano Teso; Emanuele Marconato (CoRR, 2025)