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: | , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
Elsevier BV,
2022-06-24T19:39:10Z.
|
Subjects: | |
Online Access: | Get fulltext |