Eleonora Giunchiglia

According to our database, Eleonora Giunchiglia authored at least 20 papers between 2018 and 2024.

Collaborative distances:

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

2024

CCN+: A neuro-symbolic framework for deep learning with requirements.

Eleonora Giunchiglia, Alex Tatomir, Mihaela Catalina Stoian, Thomas Lukasiewicz

Int. J. Approx. Reason., 2024

ROAD-Waymo: Action Awareness at Scale for Autonomous Driving.

Salman Khan, Izzeddin Teeti, Reza Javanmard Alitappeh, Mihaela C. Stoian, Eleonora Giunchiglia, Gurkirt Singh, Andrew Bradley, Fabio Cuzzolin

CoRR, 2024

Deep generative models as an adversarial attack strategy for tabular machine learning.

Salijona Dyrmishi, Mihaela Catalina Stoian, Eleonora Giunchiglia, Maxime Cordy

CoRR, 2024

PiShield: A NeSy Framework for Learning with Requirements.

Mihaela Catalina Stoian, Alex Tatomir, Thomas Lukasiewicz, Eleonora Giunchiglia

CoRR, 2024

ULLER: A Unified Language for Learning and Reasoning.

Emile van Krieken, Samy Badreddine, Robin Manhaeve, Eleonora Giunchiglia

Proceedings of the Neural-Symbolic Learning and Reasoning - 18th International Conference, 2024

PiShield: A PyTorch Package for Learning with Requirements.

Mihaela C. Stoian, Alex Tatomir, Thomas Lukasiewicz, Eleonora Giunchiglia

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data.

Mihaela C. Stoian, Salijona Dyrmishi, Maxime Cordy, Thomas Lukasiewicz, Eleonora Giunchiglia

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

ROAD-R: the autonomous driving dataset with logical requirements.

Eleonora Giunchiglia, Mihaela Catalina Stoian, Salman Khan, Fabio Cuzzolin, Thomas Lukasiewicz

Mach. Learn., September, 2023

Machine Learning with Requirements: a Manifesto.

Eleonora Giunchiglia, Fergus Imrie, Mihaela van der Schaar, Thomas Lukasiewicz

CoRR, 2023

Exploiting T-norms for Deep Learning in Autonomous Driving.

Mihaela C. Stoian, Eleonora Giunchiglia, Thomas Lukasiewicz

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

To TTP or not to TTP?: Exploiting TTPs to Improve ML-based Malware Detection.

Yashovardhan Sharma, Eleonora Giunchiglia, Simon Birnbach, Ivan Martinovic

Proceedings of the IEEE International Conference on Cyber Security and Resilience, 2023

2022

Deep Learning with Logical Constraints.

Eleonora Giunchiglia, Mihaela Catalina Stoian, Thomas Lukasiewicz

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Multi-Label Classification Neural Networks with Hard Logical Constraints.

Eleonora Giunchiglia, Thomas Lukasiewicz

J. Artif. Intell. Res., 2021

Lightweight Visual Question Answering using Scene Graphs.

Sai Vidyaranya Nuthalapati, Ramraj Chandradevan, Eleonora Giunchiglia, Bowen Li, Maxime Kayser, Thomas Lukasiewicz, Carl Yang

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

The Struggles of Feature-Based Explanations: Shapley Values vs. Minimal Sufficient Subsets.

Oana-Maria Camburu, Eleonora Giunchiglia, Jakob N. Foerster, Thomas Lukasiewicz, Phil Blunsom

CoRR, 2020

Coherent Hierarchical Multi-Label Classification Networks.

Eleonora Giunchiglia, Thomas Lukasiewicz

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Knowledge Graph Extraction from Videos.

Louis Mahon, Eleonora Giunchiglia, Bowen Li, Thomas Lukasiewicz

Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

2019

Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods.

Oana-Maria Camburu, Eleonora Giunchiglia, Jakob N. Foerster, Thomas Lukasiewicz, Phil Blunsom

CoRR, 2019

Conditional Behavior Trees: Definition, Executability, and Applications.

Eleonora Giunchiglia, Michele Colledanchise, Lorenzo Natale, Armando Tacchella

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

2018

RNN-SURV: A Deep Recurrent Model for Survival Analysis.

Eleonora Giunchiglia, Anton Nemchenko, Mihaela van der Schaar

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018