Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: CoST: Contrastive Learning of Disentangled Seasonal-Trend
  Representations for Time Series Forecasting   Deep learning has been actively studied for time series forecasting, and the
mainstream paradigm is based on the end-to-end training of neural network
architectures, ranging from classical LSTM/RNNs to more recent TCNs and
Transformers. Motivated by the recent success of representation learning in
computer vision and natural language processing, we argue that a more promising
paradigm for time series forecasting, is to first learn disentangled feature
representations, followed by a simple regression fine-tuning step -- we justify
such a paradigm from a causal perspective. Following this principle, we propose
a new time series representation learning framework for time series forecasting
named CoST, which applies contrastive learning methods to learn disentangled
seasonal-trend representations. CoST comprises both time domain and frequency
domain contrastive losses to learn discriminative trend and seasonal
representations, respectively. Extensive experiments on real-world datasets
show that CoST consistently outperforms the state-of-the-art methods by a
considerable margin, achieving a 21.3% improvement in MSE on multivariate
benchmarks. It is also robust to various choices of backbone encoders, as well
as downstream regressors. Code is available at
https://github.com/salesforce/CoST.

33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
8
The categories of this paper are: hep-ex
13
The categories of this paper are: quant-ph
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
16
The categories of this paper are: stat
21
The categories of this paper are: adap-org
25
The categories of this paper are: patt-sol
35
The categories of this paper are: mtrl-th
34
The categories of this paper are: chem-ph
11
The categories of this paper are: hep-lat
19
The categories of this paper are: eess
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con
20
The categories of this paper are: acc-phys