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Frontiers of Computer Science

ISSN 2095-2228

ISSN 2095-2236(Online)

CN 10-1014/TP

Postal Subscription Code 80-970

2018 Impact Factor: 1.129

Front. Comput. Sci.    2024, Vol. 18 Issue (1) : 181324    https://doi.org/10.1007/s11704-023-2629-4
Artificial Intelligence
Credit assignment for trained neural networks based on Koopman operator theory
Zhen LIANG1, Changyuan ZHAO2, Wanwei LIU3(), Bai XUE2, Wenjing YANG1, Zhengbin PANG3
1. Institute for Quantum Information & State Key Laboratory of High Performance Computing, National University of Defense Technology, Changsha 410000, China
2. Institute of Software, Chinese Academy of Sciences, Beijing 100190, China
3. College of Computer Science and Technology, National University of Defense Technology, Changsha 410000, China
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Corresponding Author(s): Wanwei LIU   
Just Accepted Date: 11 May 2023   Issue Date: 24 July 2023
 Cite this article:   
Zhen LIANG,Changyuan ZHAO,Wanwei LIU, et al. Credit assignment for trained neural networks based on Koopman operator theory[J]. Front. Comput. Sci., 2024, 18(1): 181324.
 URL:  
https://academic.hep.com.cn/fcs/EN/10.1007/s11704-023-2629-4
https://academic.hep.com.cn/fcs/EN/Y2024/V18/I1/181324
Fig.1  Workflows of the credit assignment problem on trained NNs
Fig.2  Credit assignment of layers and convolution kernels in Lenet-5
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