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Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI

, , , , , , , , , , , and . (2019)cite arxiv:1910.10045Comment: 67 pages, 13 figures, accepted for its publication in Information Fusion.

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Towards Explainable Neural-Symbolic Visual Reasoning., , , and . NeSy@IJCAI, (2019)T-Rep: Representation Learning for Time Series using Time-Embeddings., , and . CoRR, (2023)Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classification., , , , and . CoRR, (2022)Explaining Aha! moments in artificial agents through IKE-XAI: Implicit Knowledge Extraction for eXplainable AI., , , , and . Neural Networks, (2022)A Neural-Symbolic learning framework to produce interpretable predictions for image classification. (Modèle d'apprentissage neuro-symbolique pour produire des prédictions interprétables pour de la classification d'imagines).. Sorbonne University, Paris, France, (2022)Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI, , , , , , , , , and 2 other author(s). Information Fusion, (2020)Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI., , , , , , , , , and 2 other author(s). Inf. Fusion, (2020)Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI, , , , , , , , , and 2 other author(s). (2019)cite arxiv:1910.10045Comment: 67 pages, 13 figures, accepted for its publication in Information Fusion.