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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:

Model-free prediction of multistability using echo state network
Mousumi Roy, Swarnendu Mandal, Chittaranjan Hens, et al.
Chaos An Interdisciplinary Journal of Nonlinear Science (2022) Vol. 32, Iss. 10
Open Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Reservoir-computing based associative memory and itinerancy for complex dynamical attractors
Ling-Wei Kong, Gene A. Brewer, Ying–Cheng Lai
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 7
Inferring attracting basins of power system with machine learning
Yao Du, Qing Li, Huawei Fan, et al.
Physical Review Research (2024) Vol. 6, Iss. 1
Open Access | Times Cited: 5
Data-informed reservoir computing for efficient time-series prediction
Felix Köster, Dhruvit Patel, Alexander Wikner, et al.
Chaos An Interdisciplinary Journal of Nonlinear Science (2023) Vol. 33, Iss. 7
Open Access | Times Cited: 13
Reconstructing bifurcation diagrams of chaotic circuits with reservoir computing
Haibo Luo, Yao Du, Huawei Fan, et al.
Physical review. E (2024) Vol. 109, Iss. 2
Open Access | Times Cited: 5
Extreme events in the Higgs oscillator: A dynamical study and forecasting approach
Wasif Ahamed M, R. Kavitha, V. Chithiika Ruby, et al.
Chaos An Interdisciplinary Journal of Nonlinear Science (2025) Vol. 35, Iss. 2
Open Access
Learning hidden dynamics using echo state network
Jianming Liu, Xu Xu, Wenjing Guo, et al.
Nonlinear Dynamics (2025)
Closed Access
Intermittency in predicting the behavior of stochastic systems using reservoir computing
Nikita Kulagin, Andrey Andreev, А. А. Короновский, et al.
Physical review. E (2025) Vol. 111, Iss. 2
Closed Access
Multifunctional reservoir computing
Yao Du, Haibo Luo, Jianmin Guo, et al.
Physical review. E (2025) Vol. 111, Iss. 3
Closed Access
Predicting critical transitions induced by the saddle-node bifurcation in electronic circuits using parameter space estimation
Yoshitaka Itoh
Chaos An Interdisciplinary Journal of Nonlinear Science (2025) Vol. 35, Iss. 3
Closed Access
Strong and weak prediction of stochastic dynamics using reservoir computing
Alexander E. Hramov, Nikita Kulagin, Alexander N. Pisarchik, et al.
Chaos An Interdisciplinary Journal of Nonlinear Science (2025) Vol. 35, Iss. 3
Closed Access
Catch-22s of reservoir computing
Yuanzhao Zhang, Sean P. Cornelius
Physical Review Research (2023) Vol. 5, Iss. 3
Open Access | Times Cited: 12
Application of next-generation reservoir computing for predicting chaotic systems from partial observations
Irmantas Ratas, K. Pyragas
Physical review. E (2024) Vol. 109, Iss. 6
Closed Access | Times Cited: 3
Machine learning based prediction of phase ordering dynamics
Swati Chauhan, Swarnendu Mandal, Vijay Kumar Yadav, et al.
Chaos An Interdisciplinary Journal of Nonlinear Science (2023) Vol. 33, Iss. 6
Closed Access | Times Cited: 7
Predicting nonsmooth chaotic dynamics by reservoir computing
Lufa Shi, Hengtong Wang, Sheng-Jun Wang, et al.
Physical review. E (2024) Vol. 109, Iss. 1
Closed Access | Times Cited: 2
Learning unidirectional coupling using an echo-state network
Swarnendu Mandal, Manish Dev Shrimali
Physical review. E (2023) Vol. 107, Iss. 6
Open Access | Times Cited: 6
Forecasting coherence resonance in a stochastic Fitzhugh–Nagumo neuron model using reservoir computing
Alexander E. Hramov, Nikita Kulagin, Andrey Andreev, et al.
Chaos Solitons & Fractals (2023) Vol. 178, pp. 114354-114354
Closed Access | Times Cited: 6
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
Delayed self-feedback echo state network for long-term dynamics of hyperchaotic systems
Xu Xu, Jianming Liu, Eric Li
Physical review. E (2024) Vol. 109, Iss. 6
Closed Access | Times Cited: 1
Machine Learning of Nonlinear Dynamical Systems with Control Parameters Using Feedforward Neural Networks
Hidetsugu Sakaguchi
Journal of the Physical Society of Japan (2024) Vol. 93, Iss. 10
Closed Access | Times Cited: 1
Predicting multi-parametric dynamics of an externally forced oscillator using reservoir computing and minimal data
Manish Yadav, Swati Chauhan, Manish Dev Shrimali, et al.
Nonlinear Dynamics (2024)
Open Access | Times Cited: 1
Predicting aging transition using Echo state network
Biswambhar Rakshit, S Aryalakshmi, Arjun J. Kartha, et al.
Chaos An Interdisciplinary Journal of Nonlinear Science (2023) Vol. 33, Iss. 8
Closed Access | Times Cited: 4
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
Data-driven computation of adjoint sensitivities without adjoint solvers: An application to thermoacoustics
Defne Ege Ozan, Luca Magri
Physical Review Fluids (2024) Vol. 9, Iss. 10
Open Access
Adjoint Sensitivities of Chaotic Flows Without Adjoint Solvers: A Data-Driven Approach
Defne Ege Ozan, Luca Magri
Lecture notes in computer science (2024), pp. 345-352
Closed Access
Hardware Implementation of Next Generation Reservoir Computing with RRAM‐Based Hybrid Digital‐Analog System
Danian Dong, Woyu Zhang, Yuanlu Xie, et al.
Advanced Intelligent Systems (2024) Vol. 6, Iss. 10
Open Access
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