Eleonora Giunchiglia

Orcid: 0000-0001-9313-753X

Affiliations:
  • TU Wien, Vienna, Austria


According to our database1, Eleonora Giunchiglia authored at least 17 papers between 2018 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
CCN+: A neuro-symbolic framework for deep learning with requirements.
Int. J. Approx. Reason., 2024

ULLER: A Unified Language for Learning and Reasoning.
CoRR, 2024

PiShield: A NeSy Framework for Learning with Requirements.
CoRR, 2024

How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
ROAD-R: the autonomous driving dataset with logical requirements.
Mach. Learn., September, 2023

Machine Learning with Requirements: a Manifesto.
CoRR, 2023

Exploiting T-norms for Deep Learning in Autonomous Driving.
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.
Proceedings of the IEEE International Conference on Cyber Security and Resilience, 2023

2022
Deep Learning with Logical Constraints.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021
Multi-Label Classification Neural Networks with Hard Logical Constraints.
J. Artif. Intell. Res., 2021

Lightweight Visual Question Answering using Scene Graphs.
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.
CoRR, 2020

Coherent Hierarchical Multi-Label Classification Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Knowledge Graph Extraction from Videos.
Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

2019
Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods.
CoRR, 2019

Conditional Behavior Trees: Definition, Executability, and Applications.
Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

2018
RNN-SURV: A Deep Recurrent Model for Survival Analysis.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018


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