Reduced-space Gaussian Process Regression for data-driven probabilistic forecast of chaotic dynamical systems
© 2016 Elsevier B.V. We formulate a reduced-order strategy for efficiently forecasting complex high-dimensional dynamical systems entirely based on data streams. The first step of our method involves reconstructing the dynamics in a reduced-order subspace of choice using Gaussian Process Regression...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier BV
2021
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| Online Access: | https://hdl.handle.net/1721.1/134449 |