Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Initial state reconstruction on graphs   The presence of noise is an intrinsic problem in acquisition processes for
digital images. One way to enhance images is to combine the forward and
backward diffusion equations. However, the latter problem is well known to be
exponentially unstable with respect to any small perturbations on the final
data. In this scenario, the final data can be regarded as a blurred image
obtained from the forward process, and that image can be pixelated as a
network. Therefore, we study in this work a regularization framework for the
backward diffusion equation on graphs. Our aim is to construct a spectral
graph-based solution based upon a cut-off projection. Stability and convergence
results are provided together with some numerical experiments.

29
The categories of this paper are: funct-an
11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph
17
The categories of this paper are: q-fin
26
The categories of this paper are: bayes-an
8
The categories of this paper are: hep-ex
30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga
25
The categories of this paper are: patt-sol
12
The categories of this paper are: nucl-th
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
35
The categories of this paper are: mtrl-th
16
The categories of this paper are: stat
9
The categories of this paper are: nlin
10
The categories of this paper are: q-bio