Catch-22s of reservoir computing

18 October 2022

Papers citing "Catch-22s of reservoir computing"

34 / 34 papers shown

Title
How more data can hurt: Instability and regularization in next-generation reservoir computing Yuanzhao Zhang Edmilson Roque dos Santos Sean P. Cornelius 141 2 0 28 Jan 2025
Modeling Nonlinear Oscillator Networks Using Physics-Informed Hybrid Reservoir Computing Andrew Shannon Conor Houghton David Barton Martin Homer 59 0 0 07 Nov 2024
Zero-shot forecasting of chaotic systems Yuanzhao Zhang William Gilpin AI4TS 225 7 0 24 Sep 2024
Learning unseen coexisting attractors D. Gauthier Ingo Fischer André Röhm 55 24 0 28 Jul 2022
Using Machine Learning to Anticipate Tipping Points and Extrapolate to Post-Tipping Dynamics of Non-Stationary Dynamical Systems Dhruvit Patel Edward Ott 50 40 0 01 Jul 2022
Optimizing Memory in Reservoir Computers T. Carroll 33 33 0 05 Jan 2022
Parallel Machine Learning for Forecasting the Dynamics of Complex Networks Keshav Srinivasan Nolan J. Coble J. Hamlin Thomas Antonsen Edward Ott M. Girvan AI4TS 31 28 0 27 Aug 2021
Learning strange attractors with reservoir systems Lyudmila Grigoryeva Allen G. Hart Juan-Pablo Ortega 50 27 0 11 Aug 2021
Combining machine learning and data assimilation to forecast dynamical systems from noisy partial observations Georg Gottwald Sebastian Reich AI4CE 81 38 0 08 Aug 2021
Model-free inference of unseen attractors: Reconstructing phase space features from a single noisy trajectory using reservoir computing André Röhm D. Gauthier Ingo Fischer 75 40 0 06 Aug 2021
A Framework for Machine Learning of Model Error in Dynamical Systems Matthew E. Levine Andrew M. Stuart 66 69 0 14 Jul 2021
Next Generation Reservoir Computing D. Gauthier Erik Bollt Aaron Griffith W. A. S. Barbosa 73 410 0 14 Jun 2021
Fit without fear: remarkable mathematical phenomena of deep learning through the prism of interpolation M. Belkin 51 187 0 29 May 2021
Anticipating synchronization with machine learning Huawei Fan Ling-Wei Kong Y. Lai Xingang Wang 42 55 0 13 Mar 2021
Modern Koopman Theory for Dynamical Systems Steven L. Brunton M. Budišić E. Kaiser J. Nathan Kutz AI4CE 100 417 0 24 Feb 2021
Symmetry-Aware Reservoir Computing W. A. S. Barbosa Aaron Griffith G. Rowlands L. Govia G. Ribeill M. Nguyen T. Ohki D. Gauthier 36 12 0 30 Jan 2021
Machine learning prediction of critical transition and system collapse Ling-Wei Kong Hua-wei Fan C. Grebogi Y. Lai 43 85 0 02 Dec 2020
Do Reservoir Computers Work Best at the Edge of Chaos? T. Carroll 27 62 0 02 Dec 2020
Machine Learning Link Inference of Noisy Delay-coupled Networks with Opto-Electronic Experimental Tests A. Banerjee Joseph D. Hart R. Roy Edward Ott 51 25 0 29 Oct 2020
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 497 2,414 0 18 Oct 2020
Multifunctionality in a Reservoir Computer Andrew Flynn V. Tsachouridis Andreas Amann 28 29 0 10 Aug 2020
The Random Feature Model for Input-Output Maps between Banach Spaces Nicholas H. Nelsen Andrew M. Stuart 72 143 0 20 May 2020
Echo State Networks trained by Tikhonov least squares are L2(μ) approximators of ergodic dynamical systems Allen G. Hart J. Hook Jonathan H.P Dawes 67 46 0 14 May 2020
A Bayesian machine scientist to aid in the solution of challenging scientific problems Roger Guimerà I. Reichardt Antoni Aguilar-Mogas F. Massucci Manuel Miranda J. Pallarés Marta Sales-Pardo AI4CE 33 116 0 25 Apr 2020
Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems Alexander Wikner Jaideep Pathak Brian Hunt M. Girvan T. Arcomano I. Szunyogh Andrew Pomerance Edward Ott AI4CE 94 71 0 10 Feb 2020
Model-free prediction of spatiotemporal dynamical systems with recurrent neural networks: Role of network spectral radius Junjie Jiang Y. Lai 45 105 0 10 Oct 2019
Backpropagation Algorithms and Reservoir Computing in Recurrent Neural Networks for the Forecasting of Complex Spatiotemporal Dynamics Pantelis R. Vlachas Jaideep Pathak Brian R. Hunt T. Sapsis M. Girvan Edward Ott Petros Koumoutsakos AI4TS 61 391 0 09 Oct 2019
Forecasting Chaotic Systems with Very Low Connectivity Reservoir Computers Aaron Griffith Andrew Pomerance D. Gauthier 41 128 0 01 Oct 2019
Rapid Time Series Prediction with a Hardware-Based Reservoir Computer D. Canaday Aaron Griffith D. Gauthier 32 76 0 19 Jul 2018
Reservoir Computing Universality With Stochastic Inputs Lukas Gonon Juan-Pablo Ortega 38 111 0 07 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 414 5,111 0 19 Jun 2018
Hybrid Forecasting of Chaotic Processes: Using Machine Learning in Conjunction with a Knowledge-Based Model Jaideep Pathak Alexander Wikner Rebeckah K. Fussell Sarthak Chandra Brian Hunt M. Girvan Edward Ott 46 287 0 09 Mar 2018
Using a reservoir computer to learn chaotic attractors, with applications to chaos synchronisation and cryptography P. Antonik Marvyn Gulina J. Pauwels Serge Massar 47 76 0 08 Feb 2018
Visualizing the Loss Landscape of Neural Nets Hao Li Zheng Xu Gavin Taylor Christoph Studer Tom Goldstein 243 1,893 0 28 Dec 2017