Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: NeuroView: Explainable Deep Network Decision Making   Deep neural networks (DNs) provide superhuman performance in numerous
computer vision tasks, yet it remains unclear exactly which of a DN's units
contribute to a particular decision. NeuroView is a new family of DN
architectures that are interpretable/explainable by design. Each member of the
family is derived from a standard DN architecture by vector quantizing the unit
output values and feeding them into a global linear classifier. The resulting
architecture establishes a direct, causal link between the state of each unit
and the classification decision. We validate NeuroView on standard datasets and
classification tasks to show that how its unit/class mapping aids in
understanding the decision-making process.

15
The categories of this paper are: nucl-ex
36
The categories of this paper are: cmp-lg
19
The categories of this paper are: eess
5
The categories of this paper are: gr-qc
26
The categories of this paper are: bayes-an
20
The categories of this paper are: acc-phys
31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
11
The categories of this paper are: hep-lat
14
The categories of this paper are: math-ph
8
The categories of this paper are: hep-ex
22
The categories of this paper are: chao-dyn
18
The categories of this paper are: econ