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A self-explanatory method for the black problem on discrimination part of CNN
However, it is hard for the interpretable models to approximate the discrimination part because of the tradeoff problem between interpretability performance and generalization performance of the discrimination part.
A game method for improving the interpretability of convolution neural network
The reason is, we believe that: the network is essentially a perceptual model.
How to improve the interpretability of kernel learning
In this paper, a quantitative index of the interpretability is proposed and its rationality is proved, and equilibrium problem between the interpretability and the generalization performance is analyzed.
How far from automatically interpreting deep learning
In other words, there is a gap between the deep learning model and the cognitive mode.
