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Respecting Time Series Properties Makes Deep Time Series Forecasting
  Perfect

Respecting Time Series Properties Makes Deep Time Series Forecasting Perfect

22 July 2022
Li Shen
Yuning Wei
Yangzhu Wang
    AI4TS
ArXiv (abs)PDFHTMLGithub (12★)

Papers citing "Respecting Time Series Properties Makes Deep Time Series Forecasting Perfect"

3 / 3 papers shown
Soft Contrastive Learning for Time Series
Soft Contrastive Learning for Time Series
Seunghan Lee
Taeyoung Park
Kibok Lee
AI4TS
523
59
0
27 Dec 2023
GBT: Two-stage transformer framework for non-stationary time series
  forecasting
GBT: Two-stage transformer framework for non-stationary time series forecastingNeural Networks (Neural Netw.), 2023
Li Shen
Yuning Wei
Yangzhu Wang
AI4TS
257
38
0
17 Jul 2023
FDNet: Focal Decomposed Network for Efficient, Robust and Practical Time
  Series Forecasting
FDNet: Focal Decomposed Network for Efficient, Robust and Practical Time Series ForecastingKnowledge-Based Systems (KBS), 2023
Li Shen
Yuning Wei
Yangzhu Wang
Huaxin Qiu
OODAI4TS
230
15
0
19 Jun 2023
1
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