explainability.
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This post provides an overview of explainability in machine learning and includes illustrations of model-to-human and human-to-model explainability.
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[Submitted on 18 Apr 2022 (v1), last revised 27 Sep 2023 (this version, v2)] Download a PDF of the paper titled A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability, by Enyan Dai and 7 other authors