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A Survey on Neural Network Interpretability
[article]
2021
arXiv
pre-print
Along with the great success of deep neural networks, there is also growing concern about their black-box nature. The interpretability issue affects people's trust on deep learning systems. It is also related to many ethical problems, e.g., algorithmic discrimination. Moreover, interpretability is a desired property for deep networks to become powerful tools in other research fields, e.g., drug discovery and genomics. In this survey, we conduct a comprehensive review of the neural network
arXiv:2012.14261v3
fatcat:hrsunbookrhjhbxlmv6pcw44w4