Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Student-t Process Quadratures for Filtering of Non-Linear Systems with
  Heavy-Tailed Noise   The aim of this article is to design a moment transformation for Student- t
distributed random variables, which is able to account for the error in the
numerically computed mean. We employ Student-t process quadrature, an instance
of Bayesian quadrature, which allows us to treat the integral itself as a
random variable whose variance provides information about the incurred
integration error. Advantage of the Student- t process quadrature over the
traditional Gaussian process quadrature, is that the integral variance depends
also on the function values, allowing for a more robust modelling of the
integration error. The moment transform is applied in nonlinear sigma-point
filtering and evaluated on two numerical examples, where it is shown to
outperform the state-of-the-art moment transforms.

11
The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
12
The categories of this paper are: nucl-th
15
The categories of this paper are: nucl-ex
2
The categories of this paper are: math
13
The categories of this paper are: quant-ph
34
The categories of this paper are: chem-ph
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
26
The categories of this paper are: bayes-an
28
The categories of this paper are: alg-geom
19
The categories of this paper are: eess
17
The categories of this paper are: q-fin