Concept whitening for interpretable image recognition

Author:

Chen ZhiORCID,Bei YijieORCID,Rudin CynthiaORCID

Funder

National Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Vision and Pattern Recognition,Human-Computer Interaction,Software

Reference51 articles.

1. Zhou, B., Bau, D., Oliva, A. & Torralba, A. Interpreting deep visual representations via network dissection. IEEE Trans. Pattern Anal. Mach. Intell. 41, 2131–2145 (2018).

2. Zhou, B., Khosla, A., Lapedriza, A., Oliva, A. & Torralba, A. Object detectors emerge in deep scene CNNs. In Proc. International Conference on Learning Representations (2015).

3. Kim, B. et al. Interpretability beyond feature attribution: quantitative testing with concept activation vectors (TCAV). In Proc. 35th International Conference on Machine Learning 2668–2677 (ICML, 2018).

4. Zhou, B., Sun, Y., Bau, D. & Torralba, A. Interpretable basis decomposition for visual explanation. In Proc. European Conference on Computer Vision (ECCV) 119–134 (2018).

5. Ghorbani, A., Wexler, J., Zou, J. Y. & Kim, B. Towards automatic concept-based explanations. In Proc. Conference on Advances in Neural Information Processing Systems 9273–9282 (NeurIPS, 2019).

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