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This paper aims to explain how a deep neural network (DNN) gradually extracts new knowledge and forgets noisy features through layers in forward propagation.
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Saxe, A. M., Bansal, Y., Dapello, J., Advani, M., Kolchinsky, A., Tracey, B. D., and Cox, D. D · 2018
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Evaluating the robustness of neural networks: An extreme value theory approach
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Zhang, Q., Wang, X., Wu, Y. N., Zhou, H., and Zhu, S.-C · 2020
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Relative flatness and generalization
Petzka, H., Kamp, M., Adilova, L., Sminchisescu, C., and Boley, M · 2021
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Interpretable compositional convolutional neural networks
Shen, W., Wei, Z., Huang, S., Zhang, B., Fan, J., Zhao, P., and Zhang, Q · 2021
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Probing classifiers: Promises, shortcomings, and advances
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