Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: State Space representation of non-stationary Gaussian Processes   The state space (SS) representation of Gaussian processes (GP) has recently
gained a lot of interest. The main reason is that it allows to compute GPs
based inferences in O(n), where $n$ is the number of observations. This
implementation makes GPs suitable for Big Data. For this reason, it is
important to provide a SS representation of the most important kernels used in
machine learning. The aim of this paper is to show how to exploit the transient
behaviour of SS models to map non-stationary kernels to SS models.

9
The categories of this paper are: nlin
13
The categories of this paper are: quant-ph
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
2
The categories of this paper are: math
37
The categories of this paper are: supr-con
15
The categories of this paper are: nucl-ex
33
The categories of this paper are: plasm-ph
30
The categories of this paper are: q-alg
3
The categories of this paper are: physics
21
The categories of this paper are: adap-org
35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
6
The categories of this paper are: astro-ph