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Forecasting Chaotic Systems with Very Low Connectivity Reservoir Computers

1 October 2019

Papers citing "Forecasting Chaotic Systems with Very Low Connectivity Reservoir Computers"

40 / 40 papers shown

Title
Federated Koopman-Reservoir Learning for Large-Scale Multivariate Time-Series Anomaly Detection Long Tan Le Tung Nguyen Han Shu Suranga Seneviratne Choong Seon Hong Nguyen Tran 105 0 0 14 Mar 2025
Reconstructing dynamics from sparse observations with no training on target system Zheng-Meng Zhai Jun-Yin Huang Benjamin D. Stern Y. Lai 78 1 0 28 Oct 2024
Learning to learn ecosystems from limited data -- a meta-learning approach Zheng-Meng Zhai Bryan Glaz Mulugeta Haile Ying-Cheng Lai 73 1 0 02 Oct 2024
Data-driven model discovery with Kolmogorov-Arnold networks Mohammadamin Moradi Shirin Panahi Erik M. Bollt Ying-Cheng Lai 61 3 0 23 Sep 2024
Predicting Chaotic System Behavior using Machine Learning Techniques Huaiyuan Rao Yichen Zhao Qiang Lai 91 0 0 11 Aug 2024
Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features Oliver R. A. Dunbar Nicholas H. Nelsen Maya Mutic 180 7 0 30 Jun 2024
Stochastic parameter reduced-order model based on hybrid machine learning approaches Cheng Fang Jinqiao Duan 71 0 0 24 Mar 2024
Hybridizing Traditional and Next-Generation Reservoir Computing to Accurately and Efficiently Forecast Dynamical Systems Ravi Chepuri Dael Amzalag Thomas Antonsen M. Girvan 73 10 0 04 Mar 2024
Chaotic attractor reconstruction using small reservoirs -- the influence of topology Lina Jaurigue AI4TS 53 9 0 23 Feb 2024
Machine-learning parameter tracking with partial state observation Zheng-Meng Zhai Mohammadamin Moradi Bryan Glaz Mulugeta Haile Ying-Cheng Lai 69 7 0 15 Nov 2023
Digital twins of nonlinear dynamical systems: A perspective Ying-Cheng Lai AI4CE 36 4 0 20 Sep 2023
Reservoir Computing with Error Correction: Long-term Behaviors of Stochastic Dynamical Systems Cheng Fang Yubin Lu Ting Gao Jinqiao Duan 77 4 0 01 May 2023
Temporal Subsampling Diminishes Small Spatial Scales in Recurrent Neural Network Emulators of Geophysical Turbulence T. A. Smith S. Penny Jason A. Platt Tse-Chun Chen 62 5 0 28 Apr 2023
Constraining Chaos: Enforcing dynamical invariants in the training of recurrent neural networks Jason A. Platt S. Penny T. A. Smith Tse-Chun Chen H. Abarbanel AI4TS 89 5 0 24 Apr 2023
Learning unidirectional coupling using echo-state network S. Mandal M. Shrimali 80 7 0 23 Mar 2023
Embedding Theory of Reservoir Computing and Reducing Reservoir Network Using Time Delays Xing-Yue Duan Xiong Ying Siyang Leng Jürgen Kurths Wei Lin Huanfei Ma 67 23 0 16 Mar 2023
Effect of temporal resolution on the reproduction of chaotic dynamics via reservoir computing Kohei Tsuchiyama André Röhm Takatomo Mihana R. Horisaki Makoto Naruse 47 6 0 27 Jan 2023
Emergence of a stochastic resonance in machine learning Zheng-Meng Zhai Ling-Wei Kong Y. Lai 58 3 0 15 Nov 2022
Catch-22s of reservoir computing Yuanzhao Zhang Sean P. Cornelius 104 13 0 18 Oct 2022
Digital twins of nonlinear dynamical systems Ling-Wei Kong Yang Weng Bryan Glaz Mulugeta Haile Y. Lai 35 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 76 40 0 01 Jul 2022
Dimensional criterion for forecasting nonlinear systems by reservoir computing Pauliina Karkkainen R. Linna 112 1 0 09 Feb 2022
A Systematic Exploration of Reservoir Computing for Forecasting Complex Spatiotemporal Dynamics Jason A. Platt S. Penny T. A. Smith Tse-Chun Chen H. Abarbanel AI4TS 96 41 0 21 Jan 2022
`Next Generation' Reservoir Computing: an Empirical Data-Driven Expression of Dynamical Equations in Time-Stepping Form Tse-Chun Chen S. Penny T. A. Smith Jason A. Platt 87 1 0 13 Jan 2022
Integrating Recurrent Neural Networks with Data Assimilation for Scalable Data-Driven State Estimation S. Penny T. A. Smith Tse-Chun Chen Jason A. Platt Hsin-Yi Lin M. Goodliff H. Abarbanel AI4CE 95 43 0 25 Sep 2021
Next Generation Reservoir Computing D. Gauthier Erik Bollt Aaron Griffith W. A. S. Barbosa 119 418 0 14 Jun 2021
Learning Hamiltonian dynamics by reservoir computer Han Zhang Huawei Fan Liang Wang Xingang Wang 25 3 0 24 Apr 2021
Deep Chaos Synchronization M. Mobini Georges Kaddoum 55 8 0 17 Apr 2021
Anticipating synchronization with machine learning Huawei Fan Ling-Wei Kong Y. Lai Xingang Wang 61 55 0 13 Mar 2021
Cluster-based Input Weight Initialization for Echo State Networks Peter Steiner A. Jalalvand P. Birkholz 55 14 0 08 Mar 2021
Reservoir Computing with Superconducting Electronics G. Rowlands M. Nguyen G. Ribeill A. Wagner L. Govia W. A. S. Barbosa D. Gauthier T. Ohki 26 9 0 03 Mar 2021
Adaptable Hamiltonian neural networks Chen-Di Han Bryan Glaz Mulugeta Haile Y. Lai AI4TS 87 26 0 25 Feb 2021
Controlling nonlinear dynamical systems into arbitrary states using machine learning Alexander Haluszczynski Christoph Räth AI4CE 93 14 0 23 Feb 2021
Robust Optimization and Validation of Echo State Networks for learning chaotic dynamics A. Racca Luca Magri OOD AAML 55 65 0 09 Feb 2021
Symmetry-Aware Reservoir Computing W. A. S. Barbosa Aaron Griffith G. Rowlands L. Govia G. Ribeill M. Nguyen T. Ohki D. Gauthier 56 12 0 30 Jan 2021
Machine learning prediction of critical transition and system collapse Ling-Wei Kong Hua-wei Fan C. Grebogi Y. Lai 67 85 0 02 Dec 2020
Transfer learning of chaotic systems Yali Guo Han Zhang Liang Wang Huawei Fan Xingang Wang AI4TS 42 17 0 15 Nov 2020
Model-Free Control of Dynamical Systems with Deep Reservoir Computing D. Canaday Andrew Pomerance D. Gauthier 56 33 0 05 Oct 2020
Breaking Symmetries of the Reservoir Equations in Echo State Networks Joschka Herteux Christoph Räth 23 1 0 21 Sep 2020
Bayesian optimisation of large-scale photonic reservoir computers P. Antonik N. Marsal Daniel Brunner D. Rontani 125 22 0 06 Apr 2020