Data-driven joint representation and prediction of nonlinear dynamical systems 
from unlabeled trajectories

Feng, Jing; Wang, Xiaolong; Liu, Qi; Ma, Jinzhong; Yue, Xiaole; Leng, Siyang; Kurths, Jürgen; Xu, Yong

doi:10.1016/j.cma.2026.119192

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Data-driven joint representation and prediction of nonlinear dynamical systems from unlabeled trajectories

Feng, J., Wang, X., Liu, Q., Ma, J., Yue, X., Leng, S., Kurths, J., Xu, Y. (2026 online): Data-driven joint representation and prediction of nonlinear dynamical systems from unlabeled trajectories. - Computer Methods in Applied Mechanics and Engineering, 461, Part A, 119192.
https://doi.org/10.1016/j.cma.2026.119192

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Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_35186 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_35186_1

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Creators:
Feng, Jing¹, Author
Wang, Xiaolong¹, Author
Liu, Qi¹, Author
Ma, Jinzhong¹, Author
Yue, Xiaole¹, Author
Leng, Siyang¹, Author
Kurths, Jürgen², Author
Xu, Yong¹, Author

Affiliations:
1External Organizations, ou_persistent22
2Potsdam Institute for Climate Impact Research, ou_persistent13

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Language(s): eng - English

Dates: Published Online: 2026-06-26

Publication Status: Published online

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Rev. Type: Peer

Identifiers: DOI: 10.1016/j.cma.2026.119192
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Model / method: Machine Learning
Model / method: Nonlinear Data Analysis

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Title: Computer Methods in Applied Mechanics and Engineering

Source Genre: Journal

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Pages: - Volume / Issue: 461 (Part A) Sequence Number: 119192 Start / End Page: - Identifier: Publisher: Elsevier
CoNE: https://publications.pik-potsdam.de/cone/journals/resource/1879-2138