Francesco Giannini

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 58

Top Topics

Reinforcement Learning

Model Predictive Control

Symbolic Reasoning

Receding Horizon

Top Venues

Publications

Gabriele Ciravegna, Mateo Espinosa Zarlenga, Pietro Barbiero, Francesco Giannini, Zohreh Shams, Damien Garreau, Mateja Jamnik, Tania Cerquitelli
Workshop on Human-Interpretable AI. KDD (2024)
Luigi D'Alfonso, Francesco Giannini, Giuseppe Franzè, Giuseppe Fedele, Francesco Pupo, Giancarlo Fortino
Autonomous Vehicle Platoons in Urban Road Networks: A Joint Distributed Reinforcement Learning and Model Predictive Control Approach. IEEE CAA J. Autom. Sinica 11 (1) (2024)
Francesco Giannini, Domenico Famularo
A Data-Driven Approach to Set-Theoretic Model Predictive Control for Nonlinear Systems. Inf. 15 (7) (2024)
David Debot, Pietro Barbiero, Francesco Giannini, Gabriele Ciravegna, Michelangelo Diligenti, Giuseppe Marra
Interpretable Concept-Based Memory Reasoning. CoRR (2024)
Peter Anthony, Francesco Giannini, Michelangelo Diligenti, Martin Homola, Marco Gori, Stefan Balogh, Ján Mojzis
Explainable Malware Detection with Tailored Logic Explained Networks. CoRR (2024)
Gabriele Dominici, Pietro Barbiero, Francesco Giannini, Martin Gjoreski, Marc Langheinrich
AnyCBMs: How to Turn Any Black Box into a Concept Bottleneck Model. CoRR (2024)
Gabriele Dominici, Pietro Barbiero, Francesco Giannini, Martin Gjoreski, Giuseppe Marra, Marc Langheinrich
Climbing the Ladder of Interpretability with Counterfactual Concept Bottleneck Models. CoRR (2024)
Francesco Giannini, Giuseppe Franzè, Francesco Pupo, Giancarlo Fortino
A Sustainable Multi-Agent Routing Algorithm for Vehicle Platoons in Urban Networks. IEEE Trans. Intell. Transp. Syst. 24 (12) (2023)
Stefano Fioravanti, Andrea Zugarini, Francesco Giannini, Leonardo Rigutini, Marco Maggini, Michelangelo Diligenti
Linguistic Feature Injection for Efficient Natural Language Processing. IJCNN (2023)
Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Lio', Frédéric Precioso, Mateja Jamnik, Giuseppe Marra
Interpretable Neural-Symbolic Concept Reasoning. CoRR (2023)
Pietro Barbiero, Stefano Fioravanti, Francesco Giannini, Alberto Tonda, Pietro Liò, Elena Di Lavore
Categorical Foundations of Explainable AI: A Unifying Formalism of Structures and Semantics. CoRR (2023)
Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin, Alisia Maria Lupidi, Lucie Charlotte Magister, Pietro Lió, Pietro Barbiero
Interpretable Graph Networks Formulate Universal Algebra Conjectures. NeurIPS (2023)
Luigi D'Alfonso, Giuseppe Franzè, Francesco Giannini, Francesco Tedesco
A Neural Network and Model Predictive Control Based Resilient Architecture for Constrained Cyber-Physical Systems. CoDIT (2023)
Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin, Alisia Maria Lupidi, Lucie Charlotte Magister, Pietro Lio, Pietro Barbiero
Interpretable Graph Networks Formulate Universal Algebra Conjectures. CoRR (2023)
Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Liò, Marco Maggini, Stefano Melacci
Logic Explained Networks. Artif. Intell. 314 (2023)
Oguzhan Keskin, Alisia Maria Lupidi, Stefano Fioravanti, Lucie Charlotte Magister, Pietro Barbiero, Pietro Lio, Francesco Giannini
Bridging Equational Properties and Patterns on Graphs: an AI-Based Approach. TAG-ML (2023)
Francesco Giannini, Giuseppe Franzè, Francesco Pupo, Giancarlo Fortino
Set-theoretic receding horizon control for nonlinear systems: a data-driven approach. EUROCON (2023)
Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Liò, Marco Maggini, Stefano Melacci
Logic Explained Networks. NeSy (2023)
Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Lio, Frédéric Precioso, Mateja Jamnik, Giuseppe Marra
Interpretable Neural-Symbolic Concept Reasoning. ICML (2023)
Francesco Giannini, Michelangelo Diligenti, Marco Maggini, Marco Gori, Giuseppe Marra
T-norms driven loss functions for machine learning. Appl. Intell. 53 (15) (2023)
Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Liò, Frédéric Precioso, Mateja Jamnik, Giuseppe Marra
Interpretable Neural-Symbolic Concept Reasoning. NeSy (2023)
Michelangelo Diligenti, Francesco Giannini, Stefano Fioravanti, Caterina Graziani, Moreno Falaschi, Giuseppe Marra
Enhancing Embedding Representations of Biomedical Data using Logic Knowledge. IJCNN (2023)
Pietro Barbiero, Francesco Giannini, Gabriele Ciravegna, Michelangelo Diligenti, Giuseppe Marra
Relational Concept Based Models. CoRR (2023)
Michelangelo Diligenti, Francesco Giannini, Stefano Fioravanti, Caterina Graziani, Moreno Falaschi, Giuseppe Marra
Enhancing Embedding Representations of Biomedical Data using Logic Knowledge. CoRR (2023)
Francesco Giannini, Giuseppe Franzè, Francesco Pupo, Giancarlo Fortino
A Set-Theoretic Receding Horizon Control Based on a Q-Learning Approach for Sustainability Purposes. CoDIT (2023)
Francesco Giannini, Giancarlo Fortino, Giuseppe Franzè, Francesco Pupo
Path planning for vehicle platoons under routing decisions: a distributed approach combining Deep Reinforcement Learning and Model Predictive Control. CoDIT (2022)
Francesco Giannini, Giuseppe Franzè, Francesco Pupo, Giancarlo Fortino
Autonomous Vehicles in Smart Cities: a Deep Reinforcement Learning Solution. DASC/PiCom/CBDCom/CyberSciTech (2022)
Francesco Giannini, Giancarlo Fortino, Giuseppe Franzè, Francesco Pupo
A Deep Q Learning-Model Predictive Control Approach to vehicle routing and control with platoon constraints. CASE (2022)
Rishabh Jain, Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Davide Buffelli, Pietro Liò
Extending Logic Explained Networks to Text Classification. EMNLP (2022)
Rishabh Jain, Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Davide Buffelli, Pietro Liò
Extending Logic Explained Networks to Text Classification. CoRR (2022)
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
Concept Embedding Models. CoRR (2022)
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
Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off. NeurIPS (2022)
Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Pietro Lió, Marco Gori, Stefano Melacci
Entropy-Based Logic Explanations of Neural Networks. AAAI (2022)
Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Lió, Marco Maggini, Stefano Melacci
Logic Explained Networks. CoRR (2021)
Giuseppe Marra, Michelangelo Diligenti, Francesco Giannini, Marco Maggini
Learning Representations for Sub-Symbolic Reasoning. CoRR (2021)
Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Pietro Lió, Marco Gori, Stefano Melacci
Entropy-based Logic Explanations of Neural Networks. CoRR (2021)
Pietro Barbiero, Gabriele Ciravegna, Dobrik Georgiev, Francesco Giannini
LENs: a Python library for Logic Explained Networks. CoRR (2021)
Giuseppe Marra, Michelangelo Diligenti, Francesco Giannini, Marco Gori, Marco Maggini
Relational Neural Machines. CoRR (2020)
Giuseppe Marra, Michelangelo Diligenti, Francesco Giannini, Marco Gori, Marco Maggini
Relational Neural Machines. ECAI (2020)
Gabriele Ciravegna, Francesco Giannini, Marco Gori, Marco Maggini, Stefano Melacci
Human-Driven FOL Explanations of Deep Learning. IJCAI (2020)
Giuseppe Marra, Francesco Giannini, Lapo Faggi, Michelangelo Diligenti, Marco Gori, Marco Maggini
Inference in relational neural machines. NeHuAI@ECAI (2020)
Gabriele Ciravegna, Francesco Giannini, Stefano Melacci, Marco Maggini, Marco Gori
A Constraint-Based Approach to Learning and Explanation. AAAI (2020)
Francesco Giannini, Michelangelo Diligenti, Marco Gori, Marco Maggini
On a Convex Logic Fragment for Learning and Reasoning. IEEE Trans. Fuzzy Syst. 27 (7) (2019)
Francesco Giannini, Marco Maggini
Conditions for Unnecessary Logical Constraints in Kernel Machines. CoRR (2019)
Francesco Giannini, Giuseppe Marra, Michelangelo Diligenti, Marco Maggini, Marco Gori
On the Relation Between Loss Functions and T-Norms. ILP (2019)
Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Gori
LYRICS: a General Interface Layer to Integrate AI and Deep Learning. CoRR (2019)
Francesco Giannini, Marco Maggini
Conditions for Unnecessary Logical Constraints in Kernel Machines. ICANN (2) (2019)
Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Gori
LYRICS: A General Interface Layer to Integrate Logic Inference and Deep Learning. ECML/PKDD (2) (2019)
Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Gori
Constraint-Based Visual Generation. ICANN (3) (2019)
Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Gori
Integrating Learning and Reasoning with Deep Logic Models. ECML/PKDD (2) (2019)
Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Maggini, Marco Gori
Learning and T-Norms Theory. CoRR (2019)
Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Gori
Integrating Learning and Reasoning with Deep Logic Models. CoRR (2019)
Francesco Giannini, Giuseppe Marra, Michelangelo Diligenti, Marco Maggini, Marco Gori
On the relation between Loss Functions and T-Norms. CoRR (2019)
Francesco Giannini, Michelangelo Diligenti, Marco Gori, Marco Maggini
Characterization of the Convex Łukasiewicz Fragment for Learning From Constraints. AAAI (2018)
Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Gori
Constraint-Based Visual Generation. CoRR (2018)
Francesco Giannini, Michelangelo Diligenti, Marco Gori, Marco Maggini
On a Convex Logic Fragment for Learning and Reasoning. CoRR (2018)
Francesco Giannini, Michelangelo Diligenti, Marco Gori, Marco Maggini
Learning Łukasiewicz Logic Fragments by Quadratic Programming. ECML/PKDD (1) (2017)
Francesco Giannini, Vincenzo Laveglia, Alessandro Rossi, Dario Zanca, Andrea Zugarini
Neural Networks for Beginners. A fast implementation in Matlab, Torch, TensorFlow. CoRR (2017)