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Next Generation Reservoir Computing

14 June 2021

Papers citing "Next Generation Reservoir Computing"

21 / 21 papers shown

Title
Panda: A pretrained forecast model for universal representation of chaotic dynamics Jeffrey Lai Anthony Bao William Gilpin AI4TS AI4CE 93 0 0 19 May 2025
Reservoir Network with Structural Plasticity for Human Activity Recognition Abdullah M. Zyarah Alaa M. Abdul-Hadi Dhireesha Kudithipudi 164 3 0 01 Mar 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
Modeling Nonlinear Oscillator Networks Using Physics-Informed Hybrid Reservoir Computing Andrew Shannon Conor Houghton David Barton Martin Homer 70 0 0 07 Nov 2024
Zero-shot forecasting of chaotic systems Yuanzhao Zhang William Gilpin AI4TS 245 8 0 24 Sep 2024
Machine Learning for Predicting Chaotic Systems Christof Schötz Alistair J R White Maximilian Gelbrecht Niklas Boers AI4CE 66 4 0 29 Jul 2024
Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features Oliver R. A. Dunbar Nicholas H. Nelsen Maya Mutic 131 7 0 30 Jun 2024
Recurrent Stochastic Configuration Networks for Temporal Data Analytics Dianhui Wang Gang Dang 60 6 0 21 Jun 2024
Using Data Assimilation to Train a Hybrid Forecast System that Combines Machine-Learning and Knowledge-Based Components Alexander Wikner Jaideep Pathak Brian R. Hunt I. Szunyogh M. Girvan Edward Ott 66 37 0 15 Feb 2021
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 514 2,456 0 18 Oct 2020
Model-Free Control of Dynamical Systems with Deep Reservoir Computing D. Canaday Andrew Pomerance D. Gauthier 45 33 0 05 Oct 2020
Accuracy of neural networks for the simulation of chaotic dynamics: precision of training data vs precision of the algorithm S. Bompas B. Georgeot D. Guéry-Odelin 33 26 0 08 Jul 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
Bayesian optimisation of large-scale photonic reservoir computers P. Antonik N. Marsal Daniel Brunner D. Rontani 113 22 0 06 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 102 71 0 10 Feb 2020
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 63 398 0 09 Oct 2019
Forecasting Chaotic Systems with Very Low Connectivity Reservoir Computers Aaron Griffith Andrew Pomerance D. Gauthier 61 129 0 01 Oct 2019
Reservoir Computing Universality With Stochastic Inputs Lukas Gonon Juan-Pablo Ortega 55 111 0 07 Jul 2018
Bayesian optimization of hyper-parameters in reservoir computing J. Yperman Thijs Becker TPM 56 32 0 16 Nov 2016
Determination of the edge of criticality in echo state networks through Fisher information maximization L. Livi F. Bianchi Cesare Alippi 62 64 0 11 Mar 2016
Advances in Optimizing Recurrent Networks Yoshua Bengio Nicolas Boulanger-Lewandowski Razvan Pascanu ODL 109 523 0 04 Dec 2012