Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Adaptive Wavelet Network   Even though convolutional neural networks have become the method of choice in
many fields of computer vision, they still lack interpretability and are
usually designed manually in a cumbersome trial-and-error process. This paper
aims at overcoming those limitations by proposing a deep neural network, which
is designed in a systematic fashion and is interpretable, by integrating
multiresolution analysis at the core of the deep neural network design. By
using the lifting scheme, it is possible to generate a wavelet representation
and design a network capable of learning wavelet coefficients in an end-to-end
form. Compared to state-of-the-art architectures, the proposed model requires
less hyper-parameter tuning and achieves competitive accuracy in image
classification tasks

27
The categories of this paper are: comp-gas
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat
23
The categories of this paper are: solv-int
30
The categories of this paper are: q-alg
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
2
The categories of this paper are: math
28
The categories of this paper are: alg-geom
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
11
The categories of this paper are: hep-lat
18
The categories of this paper are: econ