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Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM

https://doi.org/10.1101/330548
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields
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Renormalization of Collective Modes in Large-Scale Neural Dynamics
inferredcites →https://doi.org/10.1016/j.automatica.2008.05.029openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.crvi.2003.09.011openalex-snapshot
Is there chaos in the brain? II. Experimental evidence and related models
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Introduction to Applied Nonlinear Dynamical Systems and Chaos
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inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-snapshot
Long Short-Term Memory
inferredcites →https://doi.org/10.1186/1471-2105-7-483openalex-snapshot
Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems
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Dynamical Systems in Neuroscience

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s11071-020-05640-4openalex-snapshot
Beautiful chaotic patterns generated using simple untrained recurrent neural networks under harmonic excitation
inferred← citeshttps://doi.org/10.1007/s42967-021-00176-9openalex-snapshot
P-Bifurcation of Stochastic van der Pol Model as a Dynamical System in Neuroscience
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