Discovery of slow variables in a class of multiscale stochastic systems via neural networks
Przemyslaw Zielinski,
Jan S. Hesthaven
Abstract:Finding a reduction of complex, high-dimensional dynamics to its essential, low-dimensional "heart" remains a challenging yet necessary prerequisite for designing efficient numerical approaches. Machine learning methods have the potential to provide a general framework to automatically discover such representations. In this paper, we consider multiscale stochastic systems with local slow-fast time scale separation and propose a new method to encode in an artificial neural network a map that extracts the slow r… Show more
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