Francesco Giannini

According to our database, Francesco Giannini authored at least 41 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, January, 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

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., December, 2023

T-norms driven loss functions for machine learning.

Francesco Giannini, Michelangelo Diligenti, Marco Maggini, Marco Gori, Giuseppe Marra

Appl. Intell., August, 2023

Learning Logic Explanations by Neural Networks.

Gabriele Ciravegna, Francesco Giannini, Pietro Barbiero, Marco Gori, Pietro Lio, Marco Maggini, Stefano Melacci

Proceedings of the Compendium of Neurosymbolic Artificial Intelligence, 2023

Relational Concept Based Models.

Pietro Barbiero, Francesco Giannini, Gabriele Ciravegna, Michelangelo Diligenti, Giuseppe Marra

CoRR, 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

Logic Explained Networks.

Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Liò, Marco Maggini, Stefano Melacci

Artif. Intell., 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

Proceedings of the Topological, 2023

Interpretable Graph Networks Formulate Universal Algebra Conjectures.

Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin, Alisia Maria Lupidi, Lucie Charlotte Magister, Pietro Lió, Pietro Barbiero

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Proceedings of the 17th International Workshop on Neural-Symbolic Learning and Reasoning, 2023

Linguistic Feature Injection for Efficient Natural Language Processing.

Stefano Fioravanti, Andrea Zugarini, Francesco Giannini, Leonardo Rigutini, Marco Maggini, Michelangelo Diligenti

Proceedings of the International Joint Conference on Neural Networks, 2023

Enhancing Embedding Representations of Biomedical Data using Logic Knowledge.

Michelangelo Diligenti, Francesco Giannini, Stefano Fioravanti, Caterina Graziani, Moreno Falaschi, Giuseppe Marra

Proceedings of the International Joint Conference on Neural Networks, 2023

Set-theoretic receding horizon control for nonlinear systems: a data-driven approach.

Francesco Giannini, Giuseppe Franzè, Francesco Pupo, Giancarlo Fortino

Proceedings of the 20th IEEE International Conference on Smart Technologies, 2023

A Set-Theoretic Receding Horizon Control Based on a Q-Learning Approach for Sustainability Purposes.

Francesco Giannini, Giuseppe Franzè, Francesco Pupo, Giancarlo Fortino

Proceedings of the 9th International Conference on Control, 2023

A Neural Network and Model Predictive Control Based Resilient Architecture for Constrained Cyber-Physical Systems.

Luigi D'Alfonso, Giuseppe Franzè, Francesco Giannini, Francesco Tedesco

Proceedings of the 9th International Conference on Control, 2023

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

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Extending Logic Explained Networks to Text Classification.

Rishabh Jain, Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Davide Buffelli, Pietro Liò

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Autonomous Vehicles in Smart Cities: a Deep Reinforcement Learning Solution.

Francesco Giannini, Giuseppe Franzè, Francesco Pupo, Giancarlo Fortino

Proceedings of the IEEE Intl. Conf. on Dependable, 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

Proceedings of the 8th International Conference on Control, 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

Proceedings of the 18th IEEE International Conference on Automation Science and Engineering, 2022

Entropy-Based Logic Explanations of Neural Networks.

Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Pietro Lió, Marco Gori, Stefano Melacci

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

A Constraint-Based Approach to Learning and Reasoning.

Michelangelo Diligenti, Francesco Giannini, Marco Gori, Marco Maggini, Giuseppe Marra

Proceedings of the Neuro-Symbolic Artificial Intelligence: The State of the Art, 2021

Learning Representations for Sub-Symbolic Reasoning.

Giuseppe Marra, Michelangelo Diligenti, Francesco Giannini, Marco Maggini

CoRR, 2021

LENs: a Python library for Logic Explained Networks.

Pietro Barbiero, Gabriele Ciravegna, Dobrik Georgiev, Francesco Giannini

CoRR, 2021

2020

Human-Driven FOL Explanations of Deep Learning.

Gabriele Ciravegna, Francesco Giannini, Marco Gori, Marco Maggini, Stefano Melacci

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Inference in relational neural machines.

Giuseppe Marra, Francesco Giannini, Lapo Faggi, Michelangelo Diligenti, Marco Gori, Marco Maggini

Proceedings of the First International Workshop on New Foundations for Human-Centered AI (NeHuAI) co-located with 24th European Conference on Artificial Intelligence (ECAI 2020), 2020

Relational Neural Machines.

Giuseppe Marra, Michelangelo Diligenti, Francesco Giannini, Marco Gori, Marco Maggini

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

A Constraint-Based Approach to Learning and Explanation.

Gabriele Ciravegna, Francesco Giannini, Stefano Melacci, Marco Maggini, Marco Gori

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

On a Convex Logic Fragment for Learning and Reasoning.

Francesco Giannini, Michelangelo Diligenti, Marco Gori, Marco Maggini

IEEE Trans. Fuzzy Syst., 2019

Learning and T-Norms Theory.

Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Maggini, Marco Gori

CoRR, 2019

LYRICS: a General Interface Layer to Integrate AI and Deep Learning.

Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Gori

CoRR, 2019

Integrating Learning and Reasoning with Deep Logic Models.

Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Gori

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

LYRICS: A General Interface Layer to Integrate Logic Inference and Deep Learning.

Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Gori

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

On the Relation Between Loss Functions and T-Norms.

Francesco Giannini, Giuseppe Marra, Michelangelo Diligenti, Marco Maggini, Marco Gori

Proceedings of the Inductive Logic Programming - 29th International Conference, 2019

Constraint-Based Visual Generation.

Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Gori

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Image Processing, 2019

Conditions for Unnecessary Logical Constraints in Kernel Machines.

Francesco Giannini, Marco Maggini

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning, 2019

2018

Characterization of the Convex Łukasiewicz Fragment for Learning From Constraints.

Francesco Giannini, Michelangelo Diligenti, Marco Gori, Marco Maggini

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Neural Networks for Beginners. A fast implementation in Matlab, Torch, TensorFlow.

Francesco Giannini, Vincenzo Laveglia, Alessandro Rossi, Dario Zanca, Andrea Zugarini

CoRR, 2017

Learning Łukasiewicz Logic Fragments by Quadratic Programming.

Francesco Giannini, Michelangelo Diligenti, Marco Gori, Marco Maggini

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017