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Eleonora Giunchiglia
Eleonora Giunchiglia
TU Wien
Verified email at cs.ox.ac.uk
Title
Cited by
Cited by
Year
Rnn-surv: A deep recurrent model for survival analysis
E Giunchiglia, A Nemchenko, M van der Schaar
Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018
1142018
Coherent Hierarchical Multi-Label Classification Networks
E Giunchiglia, T Lukasiewicz
Proceedings of the 34th Annual Conference on Neural Information Processing …, 2020
692020
Can I trust the explainer? Verifying post-hoc explanatory methods.
OM Camburu, E Giunchiglia, J Foerster, T Lukasiewicz, P Blunsom
NeurIPS 2019 Workshop on Safety and Robustness in Decision Making, Vancouver …, 2019
57*2019
Engineering multi-agent systems: State of affairs and the road ahead
V Mascardi, D Weyns, A Ricci, CB Earle, A Casals, M Challenger, ...
ACM SIGSOFT Software Engineering Notes 44 (1), 18-28, 2019
452019
Deep Learning with Logical Constraints
E Giunchiglia, MC Stoian, T Lukasiewicz
Proceedings of the 31st International Joint Conference on Artificial …, 2022
422022
Multi-Label Classification Neural Networks with Hard Logical Constraints
E Giunchiglia, T Lukasiewicz
Journal of Artificial Intelligence Research (JAIR) 72, 759-818, 2021
362021
ROAD-R: The Autonomous Driving Dataset with Logical Requirements
E Giunchiglia, MC Stoian, S Khan, F Cuzzolin, T Lukasiewicz
Machine Learning, 2023
21*2023
Conditional behavior trees: Definition, executability, and applications
E Giunchiglia, M Colledanchise, L Natale, A Tacchella
2019 IEEE International Conference on Systems, Man and Cybernetics (SMC …, 2019
182019
The struggles of feature-based explanations: Shapley values vs. minimal sufficient subsets
OM Camburu, E Giunchiglia, J Foerster, T Lukasiewicz, P Blunsom
AAAI Explainable Agency in Artificial Intelligence Workshop 2021, 2020
172020
Knowledge Graph Extraction from Videos
L Mahon, E Giunchiglia, B Li, T Lukasiewicz
2020 IEEE International Conference on Machine Learning and Applications …, 2020
152020
Lightweight visual question answering using scene graphs
SV Nuthalapati, R Chandradevan, E Giunchiglia, B Li, M Kayser, ...
Proceedings of the 30th ACM International Conference on Information …, 2021
122021
Machine Learning with Requirements: a Manifesto
E Giunchiglia, F Imrie, M van der Schaar, T Lukasiewicz
arXiv preprint arXiv:2304.03674, 2023
42023
Timotheus Kampik, Geylani Kardas, Vincent J
V Mascardi, D Weyns, A Ricci, CB Earle, A Casals, M Challenger, ...
Koeman, John Bruntse Larsen, Simon Mayer, Tasio Méndez, Juan Carlos Nieves …, 2019
42019
Exploiting t-norms for deep learning in autonomous driving
MC Stoian, E Giunchiglia, T Lukasiewicz
arXiv preprint arXiv:2402.11362, 2024
22024
CCN+: A neuro-symbolic framework for deep learning with requirements
E Giunchiglia, A Tatomir, MC Stoian, T Lukasiewicz
International Journal of Approximate Reasoning, 109124, 2024
12024
To TTP or not to TTP? Exploiting TTPs to improve ML-based malware detection
Y Sharma, E Giunchiglia, S Birnbach, I Martinovic
IEEE International Conference on Cyber Security and Resilience (CSR), 8-15, 2023
12023
Deep learning with hard logical constraints
E Giunchiglia
University of Oxford, 2022
12022
How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
MC Stoian, S Dyrmishi, M Cordy, T Lukasiewicz, E Giunchiglia
Proceedings of the 12th International Conference on Learning Representations …, 2024
2024
Exploiting T-norms for Deep Learning in Autonomous Driving
M Cătălina Stoian, E Giunchiglia, T Lukasiewicz
arXiv e-prints, arXiv: 2402.11362, 2024
2024
How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
M Cătălina Stoian, S Dyrmishi, M Cordy, T Lukasiewicz, E Giunchiglia
arXiv e-prints, arXiv: 2402.04823, 2024
2024
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