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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Predicting critical transitions in multiscale dynamical systems using reservoir computing
Soon Hoe Lim, L. T. Giorgini, Woosok Moon, et al.
Chaos An Interdisciplinary Journal of Nonlinear Science (2020) Vol. 30, Iss. 12
Open Access | Times Cited: 23

Showing 23 citing articles:

Data-driven predictions of a multiscale Lorenz 96 chaotic system using machine-learning methods: reservoir computing, artificial neural network, and long short-term memory network
Ashesh Chattopadhyay, Pedram Hassanzadeh, Devika Subramanian
Nonlinear processes in geophysics (2020) Vol. 27, Iss. 3, pp. 373-389
Open Access | Times Cited: 177
Machine Learning with Neural Networks
B. Mehlig
(2021)
Open Access | Times Cited: 68
Using machine learning to predict statistical properties of non-stationary dynamical processes: System climate,regime transitions, and the effect of stochasticity
Dhruvit Patel, Daniel Canaday, Michelle Girvan, et al.
Chaos An Interdisciplinary Journal of Nonlinear Science (2021) Vol. 31, Iss. 3
Open Access | Times Cited: 56
Using machine learning to anticipate tipping points and extrapolate to post-tipping dynamics of non-stationary dynamical systems
Dhruvit Patel, Edward Ott
Chaos An Interdisciplinary Journal of Nonlinear Science (2023) Vol. 33, Iss. 2
Open Access | Times Cited: 30
Adaptable reservoir computing: A paradigm for model-free data-driven prediction of critical transitions in nonlinear dynamical systems
Shirin Panahi, Ying–Cheng Lai
Chaos An Interdisciplinary Journal of Nonlinear Science (2024) Vol. 34, Iss. 5
Closed Access | Times Cited: 9
Early warning signals for critical transitions in complex systems
Sandip V. George, Sneha Kachhara, G. Ambika
Physica Scripta (2023) Vol. 98, Iss. 7, pp. 072002-072002
Open Access | Times Cited: 14
Early warning signals of critical transitions in ecosystems: entropy reduction in vegetation spatial patterns
Yi-Zhi Pang, Li Li, Zhen Jin
Nonlinear Dynamics (2025)
Closed Access
Machine learning stochastic dynamics
Ying Tang
Zhongguo kexue. Wulixue Lixue Tianwenxue (2025) Vol. 55, Iss. 10, pp. 100501-100501
Closed Access
An Overview of Data-Driven Paradigms for Identification and Control of Robotic Systems
Chandan Kumar Sah, Rajpal Singh, Jishnu Keshavan
Journal of the Indian Institute of Science (2025)
Closed Access
Extrapolating tipping points and simulating non-stationary dynamics of complex systems using efficient machine learning
Daniel Köglmayr, Christoph Räth
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
Learning noise-induced transitions by multi-scaling reservoir computing
Zequn Lin, Zhaofan Lu, Zengru Di, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 3
Echo state network and classical statistical techniques for time series forecasting: A review
Fabian Corrêa Cardoso, Rafael A. Berri, Eduardo Nunes Borges, et al.
Knowledge-Based Systems (2024) Vol. 293, pp. 111639-111639
Closed Access | Times Cited: 2
Constraints on parameter choices for successful time-series prediction with echo-state networks
Lance Storm, K. Gustavsson, B. Mehlig
Machine Learning Science and Technology (2022) Vol. 3, Iss. 4, pp. 045021-045021
Open Access | Times Cited: 10
Reservoir computing with error correction: Long-term behaviors of stochastic dynamical systems
Cheng Fang, Yubin Lu, Ting Gao, et al.
Physica D Nonlinear Phenomena (2023) Vol. 456, pp. 133919-133919
Open Access | Times Cited: 5
Tipping points of evolving epidemiological networks: Machine learning-assisted, data-driven effective modeling
Nikolaos Evangelou, Tianqi Cui, Juan M. Bello‐Rivas, et al.
Chaos An Interdisciplinary Journal of Nonlinear Science (2024) Vol. 34, Iss. 6
Open Access | Times Cited: 1
Reduced Markovian models of dynamical systems
L. T. Giorgini, André Nunes de Souza, Peter J. Schmid
Physica D Nonlinear Phenomena (2024), pp. 134393-134393
Open Access | Times Cited: 1
Seeing double with a multifunctional reservoir computer
Andrew Flynn, Vassilios A. Tsachouridis, Andreas Amann
Chaos An Interdisciplinary Journal of Nonlinear Science (2023) Vol. 33, Iss. 11
Open Access | Times Cited: 4
Time-series-analysis-based detection of critical transitions in real-world non-autonomous systems
Klaus Lehnertz
Chaos An Interdisciplinary Journal of Nonlinear Science (2024) Vol. 34, Iss. 7
Open Access | Times Cited: 1
Dynamics reconstruction in the presence of bistability by using reservoir computer
Rencai Ma, Qionglin Dai, Haihong Li, et al.
Chaos Solitons & Fractals (2023) Vol. 172, pp. 113523-113523
Closed Access | Times Cited: 2
Dissecting cell fate dynamics in pediatric glioblastoma through the lens of complex systems and cellular cybernetics
Abicumaran Uthamacumaran
Biological Cybernetics (2022) Vol. 116, Iss. 4, pp. 407-445
Closed Access | Times Cited: 3
Echo State Property upon Noisy Driving Input
Junhyuk Woo, Hyeongmo Kim, Soon Ho Kim, et al.
Complexity (2024) Vol. 2024, pp. 1-15
Open Access
Variability of echo state network prediction horizon for partially observed dynamical systems
Ajit Mahata, Reetish Padhi, Amit Apte
Physical review. E (2023) Vol. 108, Iss. 6
Open Access | Times Cited: 1
Reservoir concatenation and the spectrum distribution of concatenated reservoir state matrices
Jaesung Choi, Eonyoung Park, Bongsoo Jang, et al.
AIP Advances (2023) Vol. 13, Iss. 11
Open Access | Times Cited: 1
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