Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: ERIC: Extracting Relations Inferred from Convolutions   Our main contribution is to show that the behaviour of kernels across
multiple layers of a convolutional neural network can be approximated using a
logic program. The extracted logic programs yield accuracies that correlate
with those of the original model, though with some information loss in
particular as approximations of multiple layers are chained together or as
lower layers are quantised. We also show that an extracted program can be used
as a framework for further understanding the behaviour of CNNs. Specifically,
it can be used to identify key kernels worthy of deeper inspection and also
identify relationships with other kernels in the form of the logical rules.
Finally, we make a preliminary, qualitative assessment of rules we extract from
the last convolutional layer and show that kernels identified are symbolic in
that they react strongly to sets of similar images that effectively divide
output classes into sub-classes with distinct characteristics.

31
The categories of this paper are: ao-sci
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
30
The categories of this paper are: q-alg
28
The categories of this paper are: alg-geom
25
The categories of this paper are: patt-sol
16
The categories of this paper are: stat
3
The categories of this paper are: physics
11
The categories of this paper are: hep-lat
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
26
The categories of this paper are: bayes-an
36
The categories of this paper are: cmp-lg
23
The categories of this paper are: solv-int
19
The categories of this paper are: eess