Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Understanding Convolutional Networks with APPLE : Automatic Patch
  Pattern Labeling for Explanation   With the success of deep learning, recent efforts have been focused on
analyzing how learned networks make their classifications. We are interested in
analyzing the network output based on the network structure and information
flow through the network layers. We contribute an algorithm for 1) analyzing a
deep network to find neurons that are 'important' in terms of the network
classification outcome, and 2)automatically labeling the patches of the input
image that activate these important neurons. We propose several measures of
importance for neurons and demonstrate that our technique can be used to gain
insight into, and explain how a network decomposes an image to make its final
classification.

12
The categories of this paper are: nucl-th
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex
19
The categories of this paper are: eess
14
The categories of this paper are: math-ph
17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin
34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
13
The categories of this paper are: quant-ph
22
The categories of this paper are: chao-dyn
2
The categories of this paper are: math
25
The categories of this paper are: patt-sol