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This paper aims to analyze knowledge consistency between pre-trained deep neural networks.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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The caltech-ucsd birds-200-2011 dataset
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2014
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M. Everingham, S. M. A. Eslami, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2015
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Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba · 2015
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Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel · 2016
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Alexey Dosovitskiy and Thomas Brox · 2016
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Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin · 2016
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David Bau, Bolei Zhou, Aditya Khosla, Aude Oliva, and Antonio Torralba · 2017
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Alessandro Achille and Stefano Soatto · 2018
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Evaluating capability of deep neural networks for image classification via information plane
Hao Cheng, Dongze Lian, Shenghua Gao, and Yanlin Geng · 2018
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Generating neural networkswith neural networks
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Net2vec: Quantifying and explaining how concepts are encoded by filters in deep neural networks
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Born again neural networks
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Learning how to explain neural networks: Patternnet and patternattribution
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Insights on representational similarity in neural networks with canonical correlation
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