Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: $\text{A}^3$: Activation Anomaly Analysis   Inspired by recent advances in coverage-guided analysis of neural networks,
we propose a novel anomaly detection method. We show that the hidden activation
values contain information useful to distinguish between normal and anomalous
samples. Our approach combines three neural networks in a purely data-driven
end-to-end model. Based on the activation values in the target network, the
alarm network decides if the given sample is normal. Thanks to the anomaly
network, our method even works in strict semi-supervised settings. Strong
anomaly detection results are achieved on common data sets surpassing current
baseline methods. Our semi-supervised anomaly detection method allows to
inspect large amounts of data for anomalies across various applications.

21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
19
The categories of this paper are: eess
5
The categories of this paper are: gr-qc
2
The categories of this paper are: math
37
The categories of this paper are: supr-con
6
The categories of this paper are: astro-ph
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
16
The categories of this paper are: stat
35
The categories of this paper are: mtrl-th
12
The categories of this paper are: nucl-th
25
The categories of this paper are: patt-sol
33
The categories of this paper are: plasm-ph
30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga