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ORCIDDAO-XAI@ICANN 2021: Bratislava, Slovakia
- Roberto Confalonieri, Oliver Kutz, Diego Calvanese:
Proceedings of the Workshop on Data meets Applied Ontologies in Explainable AI (DAO-XAI 2021) part of Bratislava Knowledge September (BAKS 2021), Bratislava, Slovakia, September 18th to 19th, 2021. CEUR Workshop Proceedings 2998, CEUR-WS.org 2021
Invited Talks
- Luciano Serafini:
Learning and Reasoning with Logic Tensor Networks: The Framework and an Application (Abstract of Invited Talk).
Regular Papers
- Adel Memariani, Martin Glauer, Fabian Neuhaus, Till Mossakowski, Janna Hastings:
Automated and Explainable Ontology Extension based on Deep Learning: A Case Study in the Chemical Domain. - Jason Liartis, Edmund Dervakos, Orfeas Menis-Mastromichalakis, Alexandros Chortaras, Giorgos Stamou:
Semantic Queries Explaining Opaque Machine Learning Classifiers. - Paolo Tenti, Gabriella Pasi, Rafael Peñaloza:
Complementing Language Embeddings with Knowledge Bases for Specific Domains. - Alberto Olivares Alarcos, Sergi Foix, Guillem Alenyà:
Knowledge Representation for Explainability in Collaborative Robotics and Adaptation. - Roberto Confalonieri, Pietro Galliani, Oliver Kutz, Daniele Porello, Guendalina Righetti, Nicolas Troquard:
Towards Knowledge-driven Distillation and Explanation of Black-box Models. - Houcemeddine Turki, Mohamed Ali Hadj Taieb, Mohamed Ben Aouicha:
Knowledge-Based Construction of Confusion Matrices for Multi-Label Classification Algorithms using Semantic Similarity Measures.
Extended Abstracts
- Iker Esnaola-Gonzalez:
Can Ontologies help making Machine Learning Accountable? (Extended Abstract). - Roberto Confalonieri, Tillman Weyde, Tarek R. Besold, Fermín Moscoso del Prado Martín:
Using Ontologies for Human-understandable Explanations of Black-box Models (Extended Abstract).
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