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Part-prototype networks have recently become methods of interest as an interpretable alternative to many of the current black-box image classifiers.
Prototype classification and feature selection with fuzzy sets
Bezdek, J. C. & Castelaz, P. F · 1977
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Improved versions of learning vector quantization
Kohonen, T · 1990
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Nearest prototype classification: Clustering, genetic algorithms, or random search?
Kuncheva, L. I. & Bezdek, J. C · 1998
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Soft nearest prototype classification
Seo, S., Bode, M. & Obermayer, K · 2003
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Prototype classification: Insights from machine learning
Graf, A. B., Bousquet, O., Rätsch, G. & Schölkopf, B · 2009
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Imagenet: A large-scale hierarchical image database
Deng, J. et al · 2009
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Cub-200-2011 dataset
Wah, C., Branson, S., Welinder, P., Perona, P. & Belongie, S · 2011
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3d object representations for fine-grained categorization
Krause, J., Stark, M., Deng, J. & Fei-Fei, L · 2013
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Deep learning for case-based reasoning through prototypes: A neural network that explains its predictions
Li, O., Liu, H., Chen, C. & Rudin, C · 2018
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Questionnaire Design , 439–455 (Springer International Publishing, Cham, 2018)
Krosnick, J. A · 2018
Cited alongside, same era.
Human-in-the-loop interpretability prior
Lage, I., Ross, A., Gershman, S. J., Kim, B. & Doshi-Velez, F · 2018
Cited alongside, same era.
This looks like that: deep learning for interpretable image recognition
Chen, C. et al · 2019
Cited alongside, same era.
Towards automatic concept-based explanations
Ghorbani, A., Wexler, J., Zou, J. Y. & Kim, B · 2019
Cited alongside, same era.
Interpretable machine learning (Lulu. com, 2020)
Molnar, C · 2020
Cited alongside, same era.
Toward faithful case-based reasoning through learning prototypes in a nearest neighbor-friendly space
Davoudi, S. O. & Komeili, M · 2021
Cited alongside, same era.
Neural prototype trees for interpretable fine-grained image recognition
Nauta, M., Van Bree, R. & Seifert, C · 2021
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Interpretable image recognition by constructing transparent embedding space
Wang, J., Liu, H., Wang, X. & Jing, L · 2021
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Concept-level debugging of part-prototype networks
Bontempelli, A., Teso, S., Tentori, K., Giunchiglia, F. & Passerini, A · 2022
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Hive: Evaluating the human interpretability of visual explanations
Kim, S. S., Meister, N., Ramaswamy, V. V., Fong, R. & Russakovsky, O · 2022
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What i cannot predict, i do not understand: A human-centered evaluation framework for explainability methods
Colin, J., Fel, T., Cadène, R. & Serre, T · 2022
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Hoffmann, A., Fanconi, C., Rade, R. & Kohler, J · 2021
Cited alongside, same era.
Sparrow: semantically coherent prototypes for image classification
Kraft, S. et al · 2021
Cited alongside, same era.
Deformable protopnet: An interpretable image classifier using deformable prototypes
Donnelly, J., Barnett, A. J. & Chen, C · 2022
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Interpretable image classification with differentiable prototypes assignment
Rymarczyk, D. et al · 2022
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Evaluation and improvement of interpretability for self-explainable part-prototype networks (2023)
Huang, Q. et al · 2023
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