Description:
Within this project, the Data Semantics Laboratory focuses on the development of methods to explain the behavior of deep learning systems.
Funding Agency:
Ohio Federal Research Network
From:
September, 2016
To:
May, 2019
Publications
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, “Efficient Concept Induction for Description Logics”, in AAAI Conference on Artificial Intelligence, Honolulu, US, 2019, vol. 33.
Efficient Concept Induction for Description Logics.pdf (288.86 KB) -
, “Explaining Trained Neural Networks with Semantic Web Technologies: First Steps”, Twelveth International Workshop on Neural-Symbolic Learning and Reasoning, NeSy. London, UK, 2017. 2017-nesy-xai.pdf (2.09 MB)
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, “ Propositional rule extraction from neural networks under background knowledge”, in Twelfth International Workshop on Neural-Symbolic Learning and Reasoning, 2017. main.pdf (270.11 KB)
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, “Relating Input Concepts to Convolutional Neural Network Decisions”, NIPS 2017 Workshop: Interpreting, Explaining and Visualizing Deep Learning, NIPS IEVDL 2017. NIPS, CA, USA, 2017. Relating Input Concepts to Convolutional Neural Network Decisions.pdf (2.35 MB)