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2012.01545
Cited By
Machine learning prediction of critical transition and system collapse
Physical Review Research (PRResearch), 2020
2 December 2020
Ling-Wei Kong
Hua-wei Fan
C. Grebogi
Y. Lai
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Papers citing
"Machine learning prediction of critical transition and system collapse"
38 / 38 papers shown
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Versatile Reservoir Computing for Heterogeneous Complex Networks
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Attractor-merging Crises and Intermittency in Reservoir Computing
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17 Apr 2025
Unsupervised learning for anticipating critical transitions
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Bryan Glaz
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Reconstruction of neuromorphic dynamics from a single scalar time series using variational autoencoder and neural network map
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Ying-Cheng Lai
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Zero-shot forecasting of chaotic systems
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William Gilpin
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24 Sep 2024
Data-driven model discovery with Kolmogorov-Arnold networks
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Shirin Panahi
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Deep learning for predicting the occurrence of tipping points
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How more data can hurt: Instability and regularization in next-generation reservoir computing
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Miguel C. Soriano
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Thermodynamic limit in learning period three
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Kohei Nakajima
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Christoph Räth
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Machine-learning parameter tracking with partial state observation
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Zheng-Meng Zhai
Mohammadamin Moradi
Bryan Glaz
Mulugeta Haile
Ying-Cheng Lai
294
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Tipping Points of Evolving Epidemiological Networks: Machine Learning-Assisted, Data-Driven Effective Modeling
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Tianqi Cui
J. M. Bello-Rivas
Alexei Makeev
Ioannis G. Kevrekidis
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Model-free tracking control of complex dynamical trajectories with machine learning
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Mohammadamin Moradi
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Bryan Glaz
Mulugeta Haile
Ying-Cheng Lai
260
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20 Sep 2023
Digital twins of nonlinear dynamical systems: A perspective
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Ying-Cheng Lai
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Christoph Räth
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Qing Li
Huawei Fan
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Jinghua Xiao
Xingang Wang
183
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20 May 2023
Predicting discrete-time bifurcations with deep learning
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T. Bury
D. Dylewsky
C. Bauch
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L. Glass
A. Shrier
G. Bub
234
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16 Mar 2023
Emergence of a stochastic resonance in machine learning
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Ling-Wei Kong
Y. Lai
228
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Changes from Classical Statistics to Modern Statistics and Data Science
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Shan-Yu Liu
M. Xiong
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30 Oct 2022
Catch-22s of reservoir computing
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Yuanzhao Zhang
Sean P. Cornelius
359
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18 Oct 2022
Digital twins of nonlinear dynamical systems
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Yang Weng
Bryan Glaz
Mulugeta Haile
Y. Lai
204
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Using Machine Learning to Anticipate Tipping Points and Extrapolate to Post-Tipping Dynamics of Non-Stationary Dynamical Systems
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Dhruvit Patel
Edward Ott
341
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Junjie Jiang
Zi-Gang Huang
C. Grebogi
Ying-Cheng Lai
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189
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Discovering dynamical features of Hodgkin-Huxley-type model of physiological neuron using artificial neural network
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N. Stankevich
Elmira Bagautdinova
140
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C. Mirasso
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Miguel C. Soriano
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324
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Model-free prediction of emergence of extreme events in a parametrically driven nonlinear dynamical system by Deep Learning
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S. Sudharsan
M. Senthilvelan
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323
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Learning Hamiltonian dynamics by reservoir computer
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Huawei Fan
Liang Wang
Xingang Wang
149
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Anticipating synchronization with machine learning
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Huawei Fan
Ling-Wei Kong
Y. Lai
Xingang Wang
194
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Adaptable Hamiltonian neural networks
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Chen-Di Han
Bryan Glaz
Mulugeta Haile
Y. Lai
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242
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25 Feb 2021
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