Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Low-dimensional Flow Models from high-dimensional Flow data with Machine
  Learning and First Principles   Reduced-order modelling and system identification can help us figure out the
elementary degrees of freedom and the underlying mechanisms from the
high-dimensional and nonlinear dynamics of fluid flow. Machine learning has
brought new opportunities to these two processes and is revolutionising
traditional methods. We show a framework to obtain a sparse human-interpretable
model from complex high-dimensional data using machine learning and first
principles.

16
The categories of this paper are: stat
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
15
The categories of this paper are: nucl-ex
28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org
5
The categories of this paper are: gr-qc
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
0
The categories of this paper are: hep-ph