Francesco Giannini

Orcid: 0000-0001-8492-8110

According to our database1, Francesco Giannini authored at least 51 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Embedding the State Trajectories of Nonlinear Systems via Multimodel Linear Descriptions: A Data-Driven-Based Algorithm.
IEEE Trans. Syst. Man Cybern. Syst., November, 2024

A Data-Driven Approach to Set-Theoretic Model Predictive Control for Nonlinear Systems.
Inf., July, 2024

Autonomous Vehicle Platoons in Urban Road Networks: A Joint Distributed Reinforcement Learning and Model Predictive Control Approach.
IEEE CAA J. Autom. Sinica, January, 2024

Interpretable Concept-Based Memory Reasoning.
CoRR, 2024

Explainable Malware Detection with Tailored Logic Explained Networks.
CoRR, 2024

Climbing the Ladder of Interpretability with Counterfactual Concept Bottleneck Models.
CoRR, 2024

Categorical Foundation of Explainable AI: A Unifying Theory.
Proceedings of the Explainable Artificial Intelligence, 2024

AnyCBMs: How to Turn Any Black Box into a Concept Bottleneck Model.
Proceedings of the Joint Proceedings of the xAI 2024 Late-breaking Work, 2024

Workshop on Human-Interpretable AI.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Logically Explainable Malware Detection.
Proceedings of the KDD Workshop on Human-Interpretable AI 2024 co-located with 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024), 2024

A distributed control architecture for sustainable routing decisions of autonomous vehicle platoons subject to cyber attacks.
Proceedings of the 10th International Conference on Control, 2024

A multi-tiered control framework designed for managing the logistical activities of self-driving vehicles within manufacturing environments.
Proceedings of the 20th IEEE International Conference on Automation Science and Engineering, 2024

2023
A Sustainable Multi-Agent Routing Algorithm for Vehicle Platoons in Urban Networks.
IEEE Trans. Intell. Transp. Syst., December, 2023

T-norms driven loss functions for machine learning.
Appl. Intell., August, 2023

Learning Logic Explanations by Neural Networks.
Proceedings of the Compendium of Neurosymbolic Artificial Intelligence, 2023

Relational Concept Based Models.
CoRR, 2023

Categorical Foundations of Explainable AI: A Unifying Formalism of Structures and Semantics.
CoRR, 2023

Logic Explained Networks.
Artif. Intell., 2023

Bridging Equational Properties and Patterns on Graphs: an AI-Based Approach.
Proceedings of the Topological, 2023

Interpretable Graph Networks Formulate Universal Algebra Conjectures.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Linguistic Feature Injection for Efficient Natural Language Processing.
Proceedings of the International Joint Conference on Neural Networks, 2023

Enhancing Embedding Representations of Biomedical Data using Logic Knowledge.
Proceedings of the International Joint Conference on Neural Networks, 2023

Interpretable Neural-Symbolic Concept Reasoning.
Proceedings of the International Conference on Machine Learning, 2023

Set-theoretic receding horizon control for nonlinear systems: a data-driven approach.
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.
Proceedings of the 9th International Conference on Control, 2023

A Neural Network and Model Predictive Control Based Resilient Architecture for Constrained Cyber-Physical Systems.
Proceedings of the 9th International Conference on Control, 2023

2022
Concept Embedding Models.
CoRR, 2022

Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off.
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.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Autonomous Vehicles in Smart Cities: a Deep Reinforcement Learning Solution.
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.
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.
Proceedings of the 18th IEEE International Conference on Automation Science and Engineering, 2022

Entropy-Based Logic Explanations of Neural Networks.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
A Constraint-Based Approach to Learning and Reasoning.
Proceedings of the Neuro-Symbolic Artificial Intelligence: The State of the Art, 2021

Learning Representations for Sub-Symbolic Reasoning.
CoRR, 2021

LENs: a Python library for Logic Explained Networks.
CoRR, 2021

2020
Human-Driven FOL Explanations of Deep Learning.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Inference in relational neural machines.
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.
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.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
On a Convex Logic Fragment for Learning and Reasoning.
IEEE Trans. Fuzzy Syst., 2019

Learning and T-Norms Theory.
CoRR, 2019

LYRICS: a General Interface Layer to Integrate AI and Deep Learning.
CoRR, 2019

Integrating Learning and Reasoning with Deep Logic Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

LYRICS: A General Interface Layer to Integrate Logic Inference and Deep Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

On the Relation Between Loss Functions and T-Norms.
Proceedings of the Inductive Logic Programming - 29th International Conference, 2019

Constraint-Based Visual Generation.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Image Processing, 2019

Conditions for Unnecessary Logical Constraints in Kernel Machines.
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.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Neural Networks for Beginners. A fast implementation in Matlab, Torch, TensorFlow.
CoRR, 2017

Learning Łukasiewicz Logic Fragments by Quadratic Programming.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017


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