Bridging the gap: machine learning to resolve improperly modeled dynamics

DOI10.1016/j.physd.2020.132736zbMath1486.68160arXiv2008.12642OpenAlexW3081881792MaRDI QIDQ2116291

Eric Forgoston, Dhanushka Kularatne, Maan Qraitem, M. Ani Hsieh

Publication date: 16 March 2022

Published in: Physica D (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2008.12642

zbMATH Keywords

neural networksnonlinear dynamical systemsmachine learningdata-driven modelinglong short-term memory (LSTM)

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Learning and adaptive systems in artificial intelligence (68T05) Approximation methods and numerical treatment of dynamical systems (37M99)

Related Items (1)

Bayesian learning of stochastic dynamical models

Uses Software

• Keras
• ImageNet
• Adam
• AntisymmetricRNN
• AlexNet

Cites Work

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