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Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)

, , , , , , and . Proceedings of the 35th International Conference on Machine Learning, volume 80 of Proceedings of Machine Learning Research, page 2668-2677. PMLR, (2018)

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Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV), , , , , , and . Proceedings of the 35th International Conference on Machine Learning, volume 80 of Proceedings of Machine Learning Research, page 2668-2677. PMLR, (2018)Underspecification Presents Challenges for Credibility in Modern Machine Learning., , , , , , , , , and 30 other author(s). J. Mach. Learn. Res., (2022)Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts., , , , , and . WWW, page 953-964. International World Wide Web Conferences Steering Committee / ACM, (2013)High-resolution imaging reveals highly selective nonface clusters in the fusiform face area., , and . Nature Neuroscience, 9 (9): 1177--1185 (2006)Towards Expert-Level Medical Question Answering with Large Language Models., , , , , , , , , and 21 other author(s). CoRR, (2023)Direct Uncertainty Prediction for Medical Second Opinions, , , , , , and . (2018)Identifying Distributed Object Representations in Human Extrastriate Visual Cortex., , and . NIPS, page 1169-1176. (2005)Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)., , , , , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 2673-2682. PMLR, (2018)Direct Uncertainty Prediction for Medical Second Opinions., , , , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 5281-5290. PMLR, (2019)Exploring Principled Visualizations for Deep Network Attributions., , , , and . IUI Workshops, volume 2327 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)