Bayesian learning for high-dimensional nonlinear dynamical systems : methodologies, numerics and applications to fluid flows

Bayesian learning for high-dimensional nonlinear dynamical systems : methodologies, numerics and applications to fluid flows

Thesis: Ph. D. in Mechanical Engineering and Computation, Massachusetts Institute of Technology, Department of Mechanical Engineering, September, 2020

Bibliographic Details
Main Author: Lin, Jing, Ph. D. Massachusetts Institute of Technology.
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2021
Subjects:
Mechanical Engineering.
Online Access:https://hdl.handle.net/1721.1/132760

Internet

https://hdl.handle.net/1721.1/132760

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