Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An explanation method for Siamese neural networks   A new method for explaining the Siamese neural network is proposed. It uses
the following main ideas. First, the explained feature vector is compared with
the prototype of the corresponding class computed at the embedding level (the
Siamese neural network output). The important features at this level are
determined as features which are close to the same features of the prototype.
Second, an autoencoder is trained in a special way in order to take into
account the embedding level of the Si-amese network, and its decoder part is
used for reconstructing input data with the corresponding changes. Numerical
experiments with the well-known dataset MNIST illustrate the propose method.

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The categories of this paper are: cond-mat
24
The categories of this paper are: dg-ga
0
The categories of this paper are: hep-ph
18
The categories of this paper are: econ
37
The categories of this paper are: supr-con
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
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The categories of this paper are: gr-qc
23
The categories of this paper are: solv-int
12
The categories of this paper are: nucl-th
29
The categories of this paper are: funct-an
21
The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
2
The categories of this paper are: math