Interpretability Is in the Mind of the Beholder: A Causal Framework for Human-Interpretable Representation Learning
Research on Explainable Artificial Intelligence has recently started exploring the idea of producing explanations that, rather than being expressed in terms of low-level features, are encoded in terms of <i>interpretable concepts learned from data</i>. How to reliably acquire such concep...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-11-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/25/12/1574 |