Alan Perotti

Claudio Borile

Arianna Miola

Francesco Paolo Nerini

Paolo Baracco

André Panisson

Proceedings of the Explainable Artificial Intelligence, 2024

Explainable Emotion Decoding for Human and Computer Vision.

[BibT_eX]

[DOI]

Proceedings of the Explainable Artificial Intelligence, 2024

Auditing Fairness and Explainability in Chest X-Ray Image Classifiers.

[BibT_eX]

[DOI]

Gemma Bel Bordes

Proceedings of the 16th International Conference on Agents and Artificial Intelligence, 2024

LLM-Generated Class Descriptions for Semantically Meaningful Image Classification.

[BibT_eX]

[DOI]

Simone Bertolotto

André Panisson

Carlos Andrés Méndez Guerrero

Proceedings of the 1st International Conference on Explainable AI for Neural and Symbolic Methods, 2024

2023

Co-design of Human-centered, Explainable AI for Clinical Decision Support.

[BibT_eX]

[DOI]

ACM Trans. Interact. Intell. Syst., December, 2023

Revealing the determinants of gender inequality in urban cycling with large-scale data.

[BibT_eX]

[DOI]

EPJ Data Sci., December, 2023

Convolutional neural networks for vision neuroscience: significance, developments, and outstanding issues.

[BibT_eX]

[DOI]

Giovanni Petri

Marco Tamietto

Frontiers Comput. Neurosci., February, 2023

Beyond One-Hot-Encoding: Injecting Semantics to Drive Image Classifiers.

[BibT_eX]

[DOI]

Proceedings of the Explainable Artificial Intelligence, 2023

HOLMES: HOLonym-MEronym Based Semantic Inspection for Convolutional Image Classifiers.

[BibT_eX]

[DOI]

Proceedings of the Explainable Artificial Intelligence, 2023

Evaluating Link Prediction Explanations for Graph Neural Networks.

[BibT_eX]

[DOI]

Claudio Borile

André Panisson

Proceedings of the Explainable Artificial Intelligence, 2023

Explaining Identity-aware Graph Classifiers through the Language of Motifs.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2023

Research Challenges in Trustworthy Artificial Intelligence and Computing for Health: The Case of the PRE-ACT project.

[BibT_eX]

[DOI]

Foivos Charalampakos

Thomas Tsouparopoulos

Iordanis Koutsopoulos

Proceedings of the 2023 Joint European Conference on Networks and Communications & 6G Summit, 2023

2022

GRAPHSHAP: Motif-based Explanations for Black-box Graph Classifiers.

[BibT_eX]

[DOI]

CoRR, 2022

Streamlining models with explanations in the learning loop.

[BibT_eX]

[DOI]

Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics, 2022

2021

To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods.

[BibT_eX]

[DOI]

Elvio G. Amparore

Gianmarco De Francisci Morales

Paolo Bajardi

PeerJ Comput. Sci., 2021

FairLens: Auditing black-box clinical decision support systems.

[BibT_eX]

[DOI]

Inf. Process. Manag., 2021

Continuous-Action Reinforcement Learning for Portfolio Allocation of a Life Insurance Company.

[BibT_eX]

[DOI]

Carlo Abrate

Alessio Angius

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2021

2020

Explainability Methods for Natural Language Processing: Applications to Sentiment Analysis.

[BibT_eX]

[DOI]

Proceedings of the 28th Italian Symposium on Advanced Database Systems, 2020

Doctor XAI: an ontology-based approach to black-box sequential data classification explanations.

[BibT_eX]

[DOI]

Cecilia Panigutti

Dino Pedreschi

Proceedings of the FAT* '20: Conference on Fairness, 2020

2019

Quantitative and Ontology-Based Comparison of Explanations for Image Classification.

[BibT_eX]

[DOI]

Valentina Ghidini

Rossano Schifanella

Proceedings of the Machine Learning, Optimization, and Data Science, 2019

Modeling Urban Traffic Data Through Graph-Based Neural Networks.

[BibT_eX]

[DOI]

Viviana Pinto

Tania Cerquitelli

Proceedings of the Recent Advances in Big Data and Deep Learning, 2019

2018

Understanding Network Traffic States using Transfer Learning.

[BibT_eX]

[DOI]

Panchamy Krishnakumari

Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

2017

Real-time behavioral DGA detection through machine learning.

[BibT_eX]

[DOI]

Proceedings of the International Carnahan Conference on Security Technology, 2017

2015

Neural-symbolic monitoring and adaptation.

[BibT_eX]

[DOI]

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014

Runtime Verification Through Forward Chaining.

[BibT_eX]

[DOI]

Proceedings of the Proceedings First Workshop on Horn Clauses for Verification and Synthesis, 2014

Scalable Process Monitoring through Rules and Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 4th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2014), 2014

Neural Networks for Runtime Verification.

[BibT_eX]

[DOI]

Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

2013

RuleRunner technical report.

[BibT_eX]

[DOI]

CoRR, 2013

Rewriting Rules for the Computation of Goal-Oriented Changes in an Argumentation System.

[BibT_eX]

[DOI]

Proceedings of the Computational Logic in Multi-Agent Systems, 2013

2012

Neural-Symbolic Rule-Based Monitoring.

[BibT_eX]

[DOI]

Proceedings of the Neural-Symbolic Learning and Reasoning (NeSy 2012), 2012

Learning and reasoning about norms using neural-symbolic systems.

[BibT_eX]

[DOI]

Silvano Colombo Tosatto

Valerio Genovese

Leendert W. N. van der Torre

Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 2012

2011

Multi-sorted Argumentation.

[BibT_eX]

[DOI]

Leendert W. N. van der Torre

Proceedings of the Theorie and Applications of Formal Argumentation, 2011

Argumentative Agents Negotiating on Potential Attacks.

[BibT_eX]

[DOI]

Dov M. Gabbay