Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Accurate and Robust Deep Learning Framework for Solving Wave-Based
  Inverse Problems in the Super-Resolution Regime   We propose an end-to-end deep learning framework that comprehensively solves
the inverse wave scattering problem across all length scales. Our framework
consists of the newly introduced wide-band butterfly network coupled with a
simple training procedure that dynamically injects noise during training. While
our trained network provides competitive results in classical imaging regimes,
most notably it also succeeds in the super-resolution regime where other
comparable methods fail. This encompasses both (i) reconstruction of scatterers
with sub-wavelength geometric features, and (ii) accurate imaging when two or
more scatterers are separated by less than the classical diffraction limit. We
demonstrate these properties are retained even in the presence of strong noise
and extend to scatterers not previously seen in the training set. In addition,
our network is straightforward to train requiring no restarts and has an online
runtime that is an order of magnitude faster than optimization-based
algorithms. We perform experiments with a variety of wave scattering mediums
and we demonstrate that our proposed framework outperforms both classical
inversion and competing network architectures that specialize in oscillatory
wave scattering data.

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The categories of this paper are: atom-ph
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an
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The categories of this paper are: eess
29
The categories of this paper are: funct-an
24
The categories of this paper are: dg-ga
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The categories of this paper are: plasm-ph
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The categories of this paper are: alg-geom
17
The categories of this paper are: q-fin
3
The categories of this paper are: physics
18
The categories of this paper are: econ
8
The categories of this paper are: hep-ex
25
The categories of this paper are: patt-sol
13
The categories of this paper are: quant-ph
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The categories of this paper are: ao-sci