Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multi-Resolution Spatio-Temporal Prediction with Application to Wind
  Power Generation   This paper proposes a spatio-temporal model for wind speed prediction which
can be run at different resolutions. The model assumes that the wind prediction
of a cluster is correlated to its upstream influences in recent history, and
the correlation between clusters is represented by a directed dynamic graph. A
Bayesian approach is also described in which prior beliefs about the predictive
errors at different data resolutions are represented in a form of Gaussian
processes. The joint framework enhances the predictive performance by combining
results from predictions at different data resolution and provides reasonable
uncertainty quantification. The model is evaluated on actual wind data from the
Midwest U.S. and shows a superior performance compared to traditional
baselines.

24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
26
The categories of this paper are: bayes-an
20
The categories of this paper are: acc-phys
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
10
The categories of this paper are: q-bio
0
The categories of this paper are: hep-ph
17
The categories of this paper are: q-fin