Embedding Deep Networks into Visual Explanations

15 Sep 2017 Zhongang Qi Saeed Khorram Fuxin Li

In this paper, we propose a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by learning a nonlinear embedding of a high-dimensional activation vector of a deep network layer into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can be constructed from the few concepts extracted by our explanation network... (read more)

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Methods used in the Paper


METHOD TYPE
AutoEncoder
Generative Models