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  Sequence-to-sequence prediction of spatiotemporal systems

Shen, G., Kurths, J., Yuan, Y. (2020): Sequence-to-sequence prediction of spatiotemporal systems. - Chaos, 30, 2, 023102.
https://doi.org/10.1063/1.5133405

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Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_24198 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_24198_3
Genre: Journal Article

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 Creators:
Shen, Guorui1, Author
Kurths, Jürgen2, Author              
Yuan, Ye1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Dates: 2020
 Publication Status: Finally published
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1063/1.5133405
PIKDOMAIN: RD4 - Complexity Science
MDB-ID: No data to archive
Working Group: Network- and machine-learning-based prediction of extreme events
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Title: Chaos
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 30 (2) Sequence Number: 023102 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/180808
Publisher: American Institute of Physics (AIP)