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RNN-SURV: A Deep Recurrent Model for Survival Analysis.
Eleonora Giunchiglia, Anton Nemchenko, Mihaela van der Schaar: RNN-SURV: A Deep Recurrent Model for Survival Analysis. ICANN (3) 2018: 23-32
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Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods.
Oana-Maria Camburu, Eleonora Giunchiglia, Jakob N. Foerster, Thomas Lukasiewicz, Phil Blunsom: Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods. CoRR abs/1910.02065 (2019)
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Conditional Behavior Trees: Definition, Executability, and Applications.
Eleonora Giunchiglia, Michele Colledanchise, Lorenzo Natale, Armando Tacchella: Conditional Behavior Trees: Definition, Executability, and Applications. SMC 2019: 1899-1906
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Coherent Hierarchical Multi-Label Classification Networks.
Eleonora Giunchiglia, Thomas Lukasiewicz: Coherent Hierarchical Multi-Label Classification Networks. CoRR abs/2010.10151 (2020)
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The Struggles of Feature-Based Explanations: Shapley Values vs. Minimal...
Oana-Maria Camburu, Eleonora Giunchiglia, Jakob N. Foerster, Thomas Lukasiewicz, Phil Blunsom: The Struggles of Feature-Based Explanations: Shapley Values vs. Minimal Sufficient Subsets. CoRR...
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Knowledge Graph Extraction from Videos.
Louis Mahon, Eleonora Giunchiglia, Bowen Li, Thomas Lukasiewicz: Knowledge Graph Extraction from Videos. CoRR abs/2007.10040 (2020)
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Coherent Hierarchical Multi-Label Classification Networks.
Eleonora Giunchiglia, Thomas Lukasiewicz: Coherent Hierarchical Multi-Label Classification Networks. NeurIPS 2020
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Knowledge Graph Extraction from Videos.
Louis Mahon, Eleonora Giunchiglia, Bowen Li, Thomas Lukasiewicz: Knowledge Graph Extraction from Videos. ICMLA 2020: 25-32
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Multi-Label Classification Neural Networks with Hard Logical Constraints.
Eleonora Giunchiglia, Thomas Lukasiewicz: Multi-Label Classification Neural Networks with Hard Logical Constraints. CoRR abs/2103.13427 (2021)
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Lightweight Visual Question Answering using Scene Graphs.
Sai Vidyaranya Nuthalapati, Ramraj Chandradevan, Eleonora Giunchiglia, Bowen Li, Maxime Kayser, Thomas Lukasiewicz, Carl Yang: Lightweight Visual Question Answering using Scene Graphs. CIKM 2021:...
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Multi-Label Classification Neural Networks with Hard Logical Constraints.
Eleonora Giunchiglia, Thomas Lukasiewicz: Multi-Label Classification Neural Networks with Hard Logical Constraints. J. Artif. Intell. Res. 72: 759-818 (2021)
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ROAD-R: The Autonomous Driving Dataset with Logical Requirements.
Eleonora Giunchiglia, Mihaela Catalina Stoian, Salman Khan, Fabio Cuzzolin, Thomas Lukasiewicz: ROAD-R: The Autonomous Driving Dataset with Logical Requirements. CoRR abs/2210.01597 (2022)
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Deep Learning with Logical Constraints.
Eleonora Giunchiglia, Mihaela Catalina Stoian, Thomas Lukasiewicz: Deep Learning with Logical Constraints. CoRR abs/2205.00523 (2022)
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Proceedings of the 7th Workshop on Representation Learning for NLP,...
Spandana Gella, He He, Bodhisattwa Prasad Majumder, Burcu Can, Eleonora Giunchiglia, Samuel Cahyawijaya, Sewon Min, Maximilian Mozes, Xiang Lorraine Li, Isabelle Augenstein, Anna Rogers, Kyunghyun Cho,...
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Deep Learning with Logical Constraints.
Eleonora Giunchiglia, Mihaela Catalina Stoian, Thomas Lukasiewicz: Deep Learning with Logical Constraints. IJCAI 2022: 5478-5485
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Machine Learning with Requirements: a Manifesto.
Eleonora Giunchiglia, Fergus Imrie, Mihaela van der Schaar, Thomas Lukasiewicz: Machine Learning with Requirements: a Manifesto. CoRR abs/2304.03674 (2023)
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Exploiting T-norms for Deep Learning in Autonomous Driving.
Mihaela C. Stoian, Eleonora Giunchiglia, Thomas Lukasiewicz: Exploiting T-norms for Deep Learning in Autonomous Driving. NeSy 2023: 369-380
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To TTP or not to TTP?: Exploiting TTPs to Improve ML-based Malware Detection.
Yashovardhan Sharma, Eleonora Giunchiglia, Simon Birnbach, Ivan Martinovic: To TTP or not to TTP?: Exploiting TTPs to Improve ML-based Malware Detection. CSR 2023: 8-15
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ROAD-R: the autonomous driving dataset with logical requirements.
Eleonora Giunchiglia, Mihaela Catalina Stoian, Salman Khan, Fabio Cuzzolin, Thomas Lukasiewicz: ROAD-R: the autonomous driving dataset with logical requirements. Mach. Learn. 112(9): 3261-3291 (2023)
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How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for...
Mihaela Catalina Stoian, Salijona Dyrmishi, Maxime Cordy, Thomas Lukasiewicz, Eleonora Giunchiglia: How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data. CoRR...
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Exploiting T-norms for Deep Learning in Autonomous Driving.
Mihaela Catalina Stoian, Eleonora Giunchiglia, Thomas Lukasiewicz: Exploiting T-norms for Deep Learning in Autonomous Driving. CoRR abs/2402.11362 (2024)
View ArticlePiShield: A NeSy Framework for Learning with Requirements.
Mihaela Catalina Stoian, Alex Tatomir, Thomas Lukasiewicz, Eleonora Giunchiglia: PiShield: A NeSy Framework for Learning with Requirements. CoRR abs/2402.18285 (2024)
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