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Explaining Aha! moments in artificial agents through IKE-XAI: Implicit Knowledge Extraction for eXplainable AI.

, , , , and . Neural Networks, (2022)

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Greybox XAI: A Neural-Symbolic learning framework to produce interpretable predictions for image classification., , , , and . Knowl. Based Syst., (2022)T-Rep: Representation Learning for Time Series using Time-Embeddings., , and . CoRR, (2023)Towards Explainable Neural-Symbolic Visual Reasoning., , , and . NeSy@IJCAI, (2019)Highlighting Bias with Explainable Neural-Symbolic Visual Reasoning., , , and . CoRR, (2019)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)Explaining Aha! moments in artificial agents through IKE-XAI: Implicit Knowledge Extraction for eXplainable AI., , , , and . Neural Networks, (2022)Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI., , , , , , , , , and 2 other author(s). CoRR, (2019)A Practical Tutorial on Explainable AI Techniques., , , , , , , , , and 3 other author(s). CoRR, (2021)Should artificial agents ask for help in human-robot collaborative problem-solving?, , and . CoRR, (2020)Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI, , , , , , , , , and 2 other author(s). Information Fusion, (2020)