ML interpretability: Simple isn't easy

Studies in History and Philosophy of Science Part A 103 (C):159-167 (2024)
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10.1016/j.shpsa.2023.12.007

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Tim Räz
University of Bern

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References found in this work

Understanding from Machine Learning Models.Emily Sullivan - 2022 - British Journal for the Philosophy of Science 73 (1):109-133.
Transparency in Complex Computational Systems.Kathleen A. Creel - 2020 - Philosophy of Science 87 (4):568-589.
Deep learning: A philosophical introduction.Cameron Buckner - 2019 - Philosophy Compass 14 (10):e12625.

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