Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: ODIN: ODE-Informed Regression for Parameter and State Inference in
  Time-Continuous Dynamical Systems   Parameter inference in ordinary differential equations is an important
problem in many applied sciences and in engineering, especially in a
data-scarce setting. In this work, we introduce a novel generative modeling
approach based on constrained Gaussian processes and leverage it to build a
computationally and data efficient algorithm for state and parameter inference.
In an extensive set of experiments, our approach outperforms the current state
of the art for parameter inference both in terms of accuracy and computational
cost. It also shows promising results for the much more challenging problem of
model selection.

9
The categories of this paper are: nlin
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
17
The categories of this paper are: q-fin
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
13
The categories of this paper are: quant-ph
24
The categories of this paper are: dg-ga
5
The categories of this paper are: gr-qc
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph
11
The categories of this paper are: hep-lat