EgPDE-Net: Building Continuous Neural Networks for Time Series Prediction With Exogenous Variables-Reference-Cited by-同舟云学术

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EgPDE-Net: Building Continuous Neural Networks for Time Series Prediction With Exogenous Variables

Published:2024-09 Issue:9 Volume:54 Page:5381-5393
ISSN:2168-2267
Container-title:IEEE Transactions on Cybernetics
language:
Short-container-title:IEEE Trans. Cybern.

Author:

Gao Penglei¹^ORCID,Yang Xi²^ORCID,Zhang Rui³^ORCID,Guo Ping⁴^ORCID,Goulermas John Y.¹^ORCID,Huang Kaizhu⁵^ORCID

Affiliation:

1. Department of Computer Science, University of Liverpool, Liverpool, U.K

2. Department of Intelligent Science, Xi’an Jiaotong–Liverpool University, Suzhou, China

3. Department of Foundational Mathematics, Xi’an Jiaotong–Liverpool University, Suzhou, China

4. Department of School of Systems Science, Beijing Normal University, Beijing, China

5. Data Science Research Center, Duke Kunshan University, Kunshan, China

Funder

National Natural Science Foundation of China

Jiangsu Science and Technology Programme

Natural Science Foundation of the Jiangsu Higher Education Institutions of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221036/10646531/10453229.pdf?arnumber=10453229

Reference50 articles.

1. A Multiscale Interactive Recurrent Network for Time-Series Forecasting

2. CLVSA: A Convolutional LSTM Based Variational Sequence-to-Sequence Model with Attention for Predicting Trends of Financial Markets

3. Multitask Air-Quality Prediction Based on LSTM-Autoencoder Model

4. Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series

5. Spatiotemporal Graph Convolution Multifusion Network for Urban Vehicle Emission Prediction

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