Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Forecasting time series with encoder-decoder neural networks   In this paper, we consider high-dimensional stationary processes where a new
observation is generated from a compressed version of past observations. The
specific evolution is modeled by an encoder-decoder structure. We estimate the
evolution with an encoder-decoder neural network and give upper bounds for the
expected forecast error under specific structural and sparsity assumptions. The
results are shown separately for conditions either on the absolutely regular
mixing coefficients or the functional dependence measure of the observed
process. In a quantitative simulation we discuss the behavior of the network
estimator under different model assumptions. We corroborate our theory by a
real data example where we consider forecasting temperature data.

15
The categories of this paper are: nucl-ex
36
The categories of this paper are: cmp-lg
27
The categories of this paper are: comp-gas
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
29
The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph
20
The categories of this paper are: acc-phys
6
The categories of this paper are: astro-ph
8
The categories of this paper are: hep-ex
17
The categories of this paper are: q-fin
14
The categories of this paper are: math-ph
18
The categories of this paper are: econ