Explore the application of machine learning in extracting useful patterns and coherent structures from high-dimensional fluid dynamics data in this 21-minute video lecture. Delve into topics such as autoencoders, robust POD/PCA, robust statistics (RPCA), super resolution, and statistical stationarity. Access the accompanying paper in the Annual Review of Fluid Mechanics for further insights, and stay updated with the presenter's Twitter and website for ongoing developments in this field.
Overview
Syllabus
MACHINE LEARNING FOR FLUID MECHANICS
Autoencoder
ROBUST POD/PCA
ROBUST STATISTICS (RPCA)
SUPER RESOLUTION
STATISTICAL STATIONARITY
Taught by
Steve Brunton
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