Machine learning prediction of critical transition and system collapse

2 December 2020

Papers citing "Machine learning prediction of critical transition and system collapse"

34 / 34 papers shown

Title
Learning Beyond Experience: Generalizing to Unseen State Space with Reservoir Computing Declan A. Norton Yuanzhao Zhang M. Girvan 87 0 0 05 Jun 2025
Versatile Reservoir Computing for Heterogeneous Complex Networks Yao Du Huawei Fan Xingang Wang 97 0 0 21 May 2025
Attractor-merging Crises and Intermittency in Reservoir Computing Tempei Kabayama Motomasa Komuro Yasuo Kuniyoshi Kazuyuki Aihara Kohei Nakajima 75 0 0 17 Apr 2025
How more data can hurt: Instability and regularization in next-generation reservoir computing Yuanzhao Zhang Edmilson Roque dos Santos Sean P. Cornelius 153 2 0 28 Jan 2025
Unsupervised learning for anticipating critical transitions Shirin Panahi Ling-Wei Kong Bryan Glaz Mulugeta Haile Y. Lai 176 1 0 02 Jan 2025
Reconstruction of neuromorphic dynamics from a single scalar time series using variational autoencoder and neural network map P. V. Kuptsov N. Stankevich 70 0 0 11 Nov 2024
Learning to learn ecosystems from limited data -- a meta-learning approach Zheng-Meng Zhai Bryan Glaz Mulugeta Haile Ying-Cheng Lai 63 1 0 02 Oct 2024
Zero-shot forecasting of chaotic systems Yuanzhao Zhang William Gilpin AI4TS 260 8 0 24 Sep 2024
Data-driven model discovery with Kolmogorov-Arnold networks Mohammadamin Moradi Shirin Panahi Erik M. Bollt Ying-Cheng Lai 56 3 0 23 Sep 2024
Deep learning for predicting the occurrence of tipping points Chengzuo Zhuge Jiawei Li Wei Chen BDL AI4TS 45 1 0 26 Jul 2024
Prediction of Unobserved Bifurcation by Unsupervised Extraction of Slowly Time-Varying System Parameter Dynamics from Time Series Using Reservoir Computing Keita Tokuda Yuichi Katori 46 0 0 20 Jun 2024
Adaptive control of recurrent neural networks using conceptors Guillaume Pourcel Mirko Goldmann Ingo Fischer Miguel C. Soriano 64 0 0 12 May 2024
Thermodynamic limit in learning period three Yuichiro Terasaki Kohei Nakajima 146 1 0 12 May 2024
Extrapolating tipping points and simulating non-stationary dynamics of complex systems using efficient machine learning Daniel Köglmayr Christoph Räth 39 6 0 11 Dec 2023
Machine-learning parameter tracking with partial state observation Zheng-Meng Zhai Mohammadamin Moradi Bryan Glaz Mulugeta Haile Ying-Cheng Lai 60 7 0 15 Nov 2023
Tipping Points of Evolving Epidemiological Networks: Machine Learning-Assisted, Data-Driven Effective Modeling N. Evangelou Tianqi Cui J. M. Bello-Rivas Alexei Makeev Ioannis G. Kevrekidis 65 1 0 01 Nov 2023
Model-free tracking control of complex dynamical trajectories with machine learning Zheng-Meng Zhai Mohammadamin Moradi Ling-Wei Kong Bryan Glaz Mulugeta Haile Ying-Cheng Lai 64 38 0 20 Sep 2023
Digital twins of nonlinear dynamical systems: A perspective Ying-Cheng Lai AI4CE 27 4 0 20 Sep 2023
Tipping Point Forecasting in Non-Stationary Dynamics on Function Spaces Miguel Liu-Schiaffini C. Singer Nikola B. Kovachki T. Schneider Kamyar Azizzadenesheli Anima Anandkumar 75 5 0 17 Aug 2023
Controlling dynamical systems to complex target states using machine learning: next-generation vs. classical reservoir computing Alexander Haluszczynski Daniel Köglmayr Christoph Räth 57 4 0 14 Jul 2023
Inferring Attracting Basins of Power System with Machine Learning Yao Du Qing Li Huawei Fan Mengyuan Zhan Jinghua Xiao Xingang Wang 62 6 0 20 May 2023
Predicting discrete-time bifurcations with deep learning T. Bury D. Dylewsky C. Bauch M. Anand L. Glass A. Shrier G. Bub 48 20 0 16 Mar 2023
Emergence of a stochastic resonance in machine learning Zheng-Meng Zhai Ling-Wei Kong Y. Lai 53 3 0 15 Nov 2022
Changes from Classical Statistics to Modern Statistics and Data Science Kai Zhang Shan-Yu Liu M. Xiong 82 0 0 30 Oct 2022
Catch-22s of reservoir computing Yuanzhao Zhang Sean P. Cornelius 89 13 0 18 Oct 2022
Digital twins of nonlinear dynamical systems Ling-Wei Kong Yang Weng Bryan Glaz Mulugeta Haile Y. Lai 24 2 0 05 Oct 2022
Using Machine Learning to Anticipate Tipping Points and Extrapolate to Post-Tipping Dynamics of Non-Stationary Dynamical Systems Dhruvit Patel Edward Ott 61 40 0 01 Jul 2022
Predicting extreme events from data using deep machine learning: when and where Junjie Jiang Zi-Gang Huang C. Grebogi Ying-Cheng Lai AI4Cl AI4CE 26 12 0 31 Mar 2022
Discovering dynamical features of Hodgkin-Huxley-type model of physiological neuron using artificial neural network P. V. Kuptsov N. Stankevich Elmira Bagautdinova 24 4 0 26 Mar 2022
Learn one size to infer all: Exploiting translational symmetries in delay-dynamical and spatio-temporal systems using scalable neural networks Mirko Goldmann C. Mirasso Ingo Fischer Miguel C. Soriano AI4CE 66 7 0 05 Nov 2021
Model-free prediction of emergence of extreme events in a parametrically driven nonlinear dynamical system by Deep Learning J. Meiyazhagan S. Sudharsan M. Senthilvelan AI4TS 112 17 0 14 Jul 2021
Learning Hamiltonian dynamics by reservoir computer Han Zhang Huawei Fan Liang Wang Xingang Wang 15 3 0 24 Apr 2021
Anticipating synchronization with machine learning Huawei Fan Ling-Wei Kong Y. Lai Xingang Wang 53 55 0 13 Mar 2021
Adaptable Hamiltonian neural networks Chen-Di Han Bryan Glaz Mulugeta Haile Y. Lai AI4TS 85 26 0 25 Feb 2021