Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Time Series is a Special Sequence: Forecasting with Sample Convolution
  and Interaction   Time series is a special type of sequence data, a set of observations
collected at even time intervals and ordered chronologically. Existing deep
learning techniques use generic sequence models (e.g., recurrent neural
network, Transformer model, or temporal convolutional network) for time series
analysis, which ignore some of its unique properties. In particular, three
components characterize time series: trend, seasonality, and irregular
components, and the former two components enable us to perform forecasting with
reasonable accuracy. Other types of sequence data do not have such
characteristics. Motivated by the above, in this paper, we propose a novel
neural network architecture that conducts sample convolution and interaction
for temporal modeling and apply it for the time series forecasting problem,
namely \textbf{SCINet}. Compared to conventional dilated causal convolution
architectures, the proposed downsample-convolve-interact architecture enables
multi-resolution analysis besides expanding the receptive field of the
convolution operation, which facilitates extracting temporal relation features
with enhanced predictability. Experimental results show that SCINet achieves
significant prediction accuracy improvement over existing solutions across
various real-world time series forecasting datasets.

13
The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
15
The categories of this paper are: nucl-ex
18
The categories of this paper are: econ
30
The categories of this paper are: q-alg
17
The categories of this paper are: q-fin
2
The categories of this paper are: math
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th
19
The categories of this paper are: eess
0
The categories of this paper are: hep-ph
29
The categories of this paper are: funct-an
5
The categories of this paper are: gr-qc
31
The categories of this paper are: ao-sci