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Correlation Recurrent Units A Novel Neural Architecture for Improving the Predictive Performance of Time-Series Data
| Date | 2024.07.30. |
|---|---|
| Speaker | 김찬호 |
- 이전글Dynamic Curriculum Learning for Imbalanced Data Classification 24.08.06
- 다음글Snake: a Periodic Activation Function 24.07.23
Topic:
Correlation Recurrent Units A Novel Neural Architecture for Improving the Predictive Performance of Time-Series Data
Keywords:
Neural network
RNN
STL Decomposition
Reference:
Sim, Sunghyun, Dohee Kim, and Hyerim Bae. "Correlation recurrent units: A novel neural architecture for improving the predictive performance of time-series data." IEEE Transactions on Pattern Analysis and Machine Intelligence (2023).
Cleveland, Robert B., et al. "STL: A seasonal-trend decomposition." J. off. Stat 6.1 (1990): 3-73.
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Correlation Recurrent Units A Novel Neural Architecture for Improving the Predictive Performance of Time-Series Data.pdf (2.4M)
4회 다운로드 | DATE : 2024-08-06 15:24:20
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