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Giunchiglia, Eleonora
28  results:
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1

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

Giunchiglia, Eleonora ; Tatomir, Alex ; Stoian, Mihaela Cătălina.
International Journal of Approximate Reasoning.  171 (2024)  - p. 109124 , 2024
Link: https://doi.org/10.1016/..
 
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2

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

, In: 2023 IEEE International Conference on Cyber Security and Resilience (CSR),
Sharma, Yashovardhan ; Giunchiglia, Eleonora ; Birnbach, Simon. - p. 8-15 , 2023
Link: https://doi.org/10.1109/..
 
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3

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

Giunchiglia, Eleonora ; Stoian, Mihaela Cătălina ; Khan, Salman..
Machine Learning.  112 (2023)  9 - p. 3261-3291 , 2023
Link: https://doi.org/10.1007/..
 
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4

Lightweight Visual Question Answering using Scene Graphs:

, In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management,
Nuthalapati, Sai Vidyaranya ; Chandradevan, Ramraj ; Giunchiglia, Eleonora... - p. 3353-3357 , 2021
Link: https://dl.acm.org/doi/1..
 
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5

Engineering Multi-Agent Systems : State of Affairs and t..:

Mascardi, Viviana ; Weyns, Danny ; Ricci, Alessandro...
ACM SIGSOFT Software Engineering Notes.  44 (2019)  1 - p. 18-28 , 2019
Link: https://dl.acm.org/doi/1..
 
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6

Conditional Behavior Trees: Definition, Executability, and ..:

, In: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC),
Giunchiglia, Eleonora ; Colledanchise, Michele ; Natale, Lorenzo. - p. 1899-1906 , 2019
Link: https://doi.org/10.1109/..
 
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7

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

, In: Artificial Neural Networks and Machine Learning – ICANN 2018; Lecture Notes in Computer Science,
Giunchiglia, Eleonora ; Nemchenko, Anton ; van der Schaar, Mihaela - p. 23-32 , 2018
Link: https://doi.org/10.1007/..
 
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8

ROAD-R : the autonomous driving dataset for learning with r..:

Giunchiglia, Eleonora ; Stoian, Mihaela ; Khan, Salman..
https://radar.brookes.ac.uk/radar/items/26fc1e1d-8c3f-4dd2-abf4-20423d0f9801/1/.  , 2023
Link: https://radar.brookes.ac..
 
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9

Machine Learning with Requirements: a Manifesto:

Giunchiglia, Eleonora ; Imrie, Fergus ; van der Schaar, Mihaela.
http://arxiv.org/abs/2304.03674.  , 2023
Link: http://arxiv.org/abs/230..
 
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10

Deep Learning with Logical Constraints:

Giunchiglia, Eleonora ; Stoian, Mihaela Catalina ; Lukasiewicz, Thomas
http://arxiv.org/abs/2205.00523.  , 2022
Link: http://arxiv.org/abs/220..
 
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11

ROAD-R: The Autonomous Driving Dataset with Logical Require..:

Giunchiglia, Eleonora ; Stoian, Mihaela Cătălina ; Khan, Salman..
http://arxiv.org/abs/2210.01597.  , 2022
Link: http://arxiv.org/abs/221..
 
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12

ROAD-R: The autonomous driving dataset with logical require..:

Giunchiglia, Eleonora ; Stoian, Mihaela Catalina ; Khan, Salman..
https://radar.brookes.ac.uk/radar/items/15b592bb-19a2-4a59-bd14-34b35d4412ee/1/.  , 2022
Link: https://radar.brookes.ac..
 
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13

Multi-Label Classification Neural Networks with Hard Logica..:

Giunchiglia, Eleonora ; Lukasiewicz, Thomas
http://arxiv.org/abs/2103.13427.  , 2021
Link: http://arxiv.org/abs/210..
 
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14

Coherent Hierarchical Multi-Label Classification Networks:

Giunchiglia, Eleonora ; Lukasiewicz, Thomas
http://arxiv.org/abs/2010.10151.  , 2020
Link: http://arxiv.org/abs/201..
 
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15

The Struggles of Feature-Based Explanations: Shapley Values..:

Camburu, Oana-Maria ; Giunchiglia, Eleonora ; Foerster, Jakob..
http://arxiv.org/abs/2009.11023.  , 2020
Link: http://arxiv.org/abs/200..
 
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