Discovering mean residence time and escape probability from data of stochastic dynamical systems

DOI10.1063/1.5118788zbMath1423.37049arXiv1909.00901OpenAlexW3099548371WikidataQ90420200 ScholiaQ90420200MaRDI QIDQ5242058

Miaomiao Fu, Dengfeng Wu, Jin-qiao Duan

Publication date: 5 November 2019

Published in: Chaos: An Interdisciplinary Journal of Nonlinear Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1909.00901

zbMATH Keywords

stochastic differential equationsmachine learning

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Learning and adaptive systems in artificial intelligence (68T05) Stochastic learning and adaptive control (93E35) Ordinary differential equations and systems with randomness (34F05) Generation, random and stochastic difference and differential equations (37H10)

Related Items (6)

Detecting stochastic governing laws with observation on stationary distributions ⋮ Identifying stochastic governing equations from data of the most probable transition trajectories ⋮ Discovering transition phenomena from data of stochastic dynamical systems with Lévy noise ⋮ Detecting the maximum likelihood transition path from data of stochastic dynamical systems ⋮ Extracting governing laws from sample path data of non-Gaussian stochastic dynamical systems ⋮ A data-driven approach for discovering stochastic dynamical systems with non-Gaussian Lévy noise

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