Open AccessDomain-driven models yield better predictions at lower cost than reservoir computers in Lorenz systems
Author(s) -
Ryan Pyle,
Nikola Jovanović,
Devika Subramanian,
Krishna V. Palem,
Ankit Patel
Publication year - 2021
Publication title -
philosophical transactions of the royal society a mathematical physical and engineering sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.074
H-Index - 169
eISSN - 1471-2962
pISSN - 1364-503X
DOI - 10.1098/rsta.2020.0246
Subject(s) - lorenz system , reservoir computing , computer science , hyperparameter , algorithm , generalization , artificial intelligence , mathematics , theoretical computer science , machine learning , artificial neural network , recurrent neural network , mathematical analysis , chaotic
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