Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Error Analysis Framework for Neural Network Modeling of Dynamical
  Systems   We propose a theoretical framework for investigating a modeling error caused
by numerical integration in the learning process of dynamics. Recently,
learning equations of motion to describe dynamics from data using neural
networks has been attracting attention. During such training, numerical
integration is used to compare the data with the solution of the neural network
model; however, discretization errors due to numerical integration prevent the
model from being trained correctly. In this study, we formulate the modeling
error using the Dahlquist test equation that is commonly used in the analysis
of numerical methods and apply it to some of the Runge--Kutta methods.

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The categories of this paper are: astro-ph
30
The categories of this paper are: q-alg
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
11
The categories of this paper are: hep-lat
36
The categories of this paper are: cmp-lg
16
The categories of this paper are: stat
17
The categories of this paper are: q-fin
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The categories of this paper are: hep-th
34
The categories of this paper are: chem-ph
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
32
The categories of this paper are: atom-ph
9
The categories of this paper are: nlin
31
The categories of this paper are: ao-sci