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NIF: A Framework for Quantifying Neural Information Flow in Deep Networks., , , , and . CoRR, (2019)Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty., , , , , , , , , and 4 other author(s). CoRR, (2020)Selective Concept Models: Permitting Stakeholder Customisation at Test-Time., , , , and . CoRR, (2023)DIVINE: Diverse Influential Training Points for Data Visualization and Model Refinement., , , and . CoRR, (2021)GeValDi: Generative Validation of Discriminative Models., , , , , and . Tiny Papers @ ICLR, OpenReview.net, (2023)Explainable machine learning in deployment., , , , , , , , , and . FAT*, page 648-657. ACM, (2020)You Shouldn't Trust Me: Learning Models Which Conceal Unfairness from Multiple Explanation Methods., , , and . ECAI, volume 325 of Frontiers in Artificial Intelligence and Applications, page 2473-2480. IOS Press, (2020)Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates., , and . AAAI, page 7390-7398. AAAI Press, (2022)Building Human-Machine Trust via Interpretability., , and . AAAI, page 9919-9920. AAAI Press, (2019)Approximating Full Conformal Prediction at Scale via Influence Functions., , , and . AAAI, page 6631-6639. AAAI Press, (2023)