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Title:

Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information

Document type:
Konferenzbeitrag
Author(s):
Zhang, Yang; Khakzar, Ashkan; Li, Yawei; Farshad, Azade; Kim, Seong Tae; Navab, Nassir
Abstract:
One principal approach for illuminating a black-box neural network is feature attribution, i.e. identifying the importance of input features for the network’s prediction. The predictive information of features is recently proposed as a proxy for the measure of their importance. So far, the predictive information is only identified for latent features by placing an information bottleneck within the network. We propose a method to identify features with predictive information in the input domain....     »
Book / Congress title:
Thirty-Fifth Conference on Neural Information Processing Systems
Year:
2021
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