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Controlling nonlinear dynamical systems into arbitrary states using
  machine learning
v1v2 (latest)

Controlling nonlinear dynamical systems into arbitrary states using machine learning

Scientific Reports (Sci Rep), 2021
23 February 2021
Alexander Haluszczynski
Christoph Räth
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Controlling nonlinear dynamical systems into arbitrary states using machine learning"

4 / 4 papers shown
Controlling dynamical systems to complex target states using machine
  learning: next-generation vs. classical reservoir computing
Controlling dynamical systems to complex target states using machine learning: next-generation vs. classical reservoir computingIEEE International Joint Conference on Neural Network (IJCNN), 2023
Alexander Haluszczynski
Daniel Köglmayr
Christoph Räth
178
7
0
14 Jul 2023
Controlling Chaotic Maps using Next-Generation Reservoir Computing
Controlling Chaotic Maps using Next-Generation Reservoir ComputingChaos (Chaos), 2023
Robert M Kent
W. A. S. Barbosa
D. Gauthier
331
21
0
07 Jul 2023
Phase2vec: Dynamical systems embedding with a physics-informed
  convolutional network
Phase2vec: Dynamical systems embedding with a physics-informed convolutional networkInternational Conference on Learning Representations (ICLR), 2022
Matthew Ricci
Noa Moriel
Zoe Piran
Mor Nitzan
AI4CE
334
6
0
07 Dec 2022
Digital twins of nonlinear dynamical systems
Digital twins of nonlinear dynamical systems
Ling-Wei Kong
Yang Weng
Bryan Glaz
Mulugeta Haile
Y. Lai
213
2
0
05 Oct 2022
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