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On the Understanding and Interpretation of Machine Learning Predictions in Clinical Gait Analysis Using Explainable Artificial Intelligence.

, , , , , , , , and . CoRR, (2019)

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Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations., , , and . CoRR, (2023)Selection of XAI Methods Matters: Evaluation of Feature Attribution Methods for Oculomotoric Biometric Identification., , , , , and . Gaze Meets ML, volume 210 of Proceedings of Machine Learning Research, page 66-97. PMLR, (2022)Towards Best Practice in Explaining Neural Network Decisions with LRP., , , , , and . IJCNN, page 1-7. IEEE, (2020)Explainable concept mappings of MRI: Revealing the mechanisms underlying deep learning-based brain disease classification., , , , , , , , , and 2 other author(s). CoRR, (2024)PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits., , , , and . CoRR, (2024)Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy., , , , and . CoRR, (2021)Measurably Stronger Explanation Reliability Via Model Canonization., , and . ICIP, page 516-520. IEEE, (2022)Human-Centered Evaluation of XAI Methods., , , , and . ICDM (Workshops), page 912-921. IEEE, (2023)XAI-based Comparison of Audio Event Classifiers with different Input Representations., , , , and . CBMI, page 126-132. ACM, (2023)From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space., , , , and . AAAI, page 21046-21054. AAAI Press, (2024)