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Model-free inference of unseen attractors: Reconstructing phase space
  features from a single noisy trajectory using reservoir computing
v1v2 (latest)

Model-free inference of unseen attractors: Reconstructing phase space features from a single noisy trajectory using reservoir computing

Chaos (Chaos), 2021
6 August 2021
André Röhm
D. Gauthier
Ingo Fischer
ArXiv (abs)PDFHTMLGithub

Papers citing "Model-free inference of unseen attractors: Reconstructing phase space features from a single noisy trajectory using reservoir computing"

20 / 20 papers shown
Multifunctional physical reservoir computing in soft tensegrity robots
Multifunctional physical reservoir computing in soft tensegrity robotsChaos (Chaos), 2025
Ryo Terajima
Katsuma Inoue
Kohei Nakajima
Yasuo Kuniyoshi
152
7
0
29 Jul 2025
Learning Beyond Experience: Generalizing to Unseen State Space with Reservoir Computing
Learning Beyond Experience: Generalizing to Unseen State Space with Reservoir Computing
Declan A. Norton
Yuanzhao Zhang
M. Girvan
364
5
0
05 Jun 2025
Confabulation dynamics in a reservoir computer: Filling in the gaps with untrained attractors
Confabulation dynamics in a reservoir computer: Filling in the gaps with untrained attractorsChaos (Chaos), 2025
Jack O'Hagan
Andrew Keane
Andrew Flynn
304
8
0
07 May 2025
Denoising and Reconstruction of Nonlinear Dynamics using Truncated Reservoir Computing
Denoising and Reconstruction of Nonlinear Dynamics using Truncated Reservoir ComputingChaos (Chaos), 2025
Omid Sedehi
Manish Yadav
M. Stender
S. Oberst
257
3
0
17 Apr 2025
Unsupervised Learning in Echo State Networks for Input Reconstruction
Unsupervised Learning in Echo State Networks for Input Reconstruction
Taiki Yamada
Yuichi Katori
Kantaro Fujiwara
320
0
0
20 Jan 2025
How more data can hurt: Instability and regularization in next-generation reservoir computing
How more data can hurt: Instability and regularization in next-generation reservoir computing
Yuanzhao Zhang
Edmilson Roque dos Santos
Huixin Zhang
Sean P. Cornelius
592
8
0
11 Jul 2024
Thermodynamic limit in learning period three
Thermodynamic limit in learning period three
Yuichiro Terasaki
Kohei Nakajima
611
4
0
12 May 2024
Chaotic attractor reconstruction using small reservoirs -- the influence
  of topology
Chaotic attractor reconstruction using small reservoirs -- the influence of topology
Lina Jaurigue
AI4TS
228
22
0
23 Feb 2024
Attractor reconstruction with reservoir computers: The effect of the
  reservoir's conditional Lyapunov exponents on faithful attractor
  reconstruction
Attractor reconstruction with reservoir computers: The effect of the reservoir's conditional Lyapunov exponents on faithful attractor reconstruction
J. D. Hart
332
21
0
30 Dec 2023
Inferring Attracting Basins of Power System with Machine Learning
Inferring Attracting Basins of Power System with Machine LearningPhysical Review Research (Phys. Rev. Res.), 2023
Yao Du
Qing Li
Huawei Fan
Mengyuan Zhan
Jinghua Xiao
Xingang Wang
201
12
0
20 May 2023
Learning unidirectional coupling using echo-state network
Learning unidirectional coupling using echo-state networkPhysical Review E (PRE), 2023
S. Mandal
M. Shrimali
188
11
0
23 Mar 2023
Reservoir Computing with Noise
Reservoir Computing with NoiseChaos (Chaos), 2023
Chad Nathe
C. Pappu
N. Mecholsky
Joseph D. Hart
Thomas L. Carroll
F. Sorrentino
215
23
0
28 Feb 2023
Effect of temporal resolution on the reproduction of chaotic dynamics
  via reservoir computing
Effect of temporal resolution on the reproduction of chaotic dynamics via reservoir computingChaos (Chaos), 2023
Kohei Tsuchiyama
André Röhm
Takatomo Mihana
R. Horisaki
Makoto Naruse
279
10
0
27 Jan 2023
Stabilizing Machine Learning Prediction of Dynamics: Noise and
  Noise-inspired Regularization
Stabilizing Machine Learning Prediction of Dynamics: Noise and Noise-inspired Regularization
Alexander Wikner
Joseph Harvey
M. Girvan
Brian R. Hunt
Andrew Pomerance
Thomas Antonsen
Edward Ott
319
7
0
09 Nov 2022
Catch-22s of reservoir computing
Catch-22s of reservoir computingPhysical Review Research (Phys. Rev. Res.), 2022
Yuanzhao Zhang
Sean P. Cornelius
369
19
0
18 Oct 2022
Learning unseen coexisting attractors
Learning unseen coexisting attractorsChaos (Chaos), 2022
D. Gauthier
Ingo Fischer
André Röhm
247
28
0
28 Jul 2022
Continual Learning of Dynamical Systems with Competitive Federated
  Reservoir Computing
Continual Learning of Dynamical Systems with Competitive Federated Reservoir Computing
Leonard Bereska
E. Gavves
248
7
0
27 Jun 2022
Exploring the limits of multifunctionality across different reservoir
  computers
Exploring the limits of multifunctionality across different reservoir computersIEEE International Joint Conference on Neural Network (IJCNN), 2022
Andrew Flynn
O. Heilmann
Daniel Köglmayr
V. Tsachouridis
Christoph Räth
Andreas Amann
211
8
0
23 May 2022
Learn one size to infer all: Exploiting translational symmetries in
  delay-dynamical and spatio-temporal systems using scalable neural networks
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
348
10
0
05 Nov 2021
Master memory function for delay-based reservoir computers with
  single-variable dynamics
Master memory function for delay-based reservoir computers with single-variable dynamicsIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021
F. Köster
S. Yanchuk
K. Lüdge
245
10
0
28 Aug 2021
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