Dynamic Mode Decomposition from Koopman Theory to Applications (Prof. Peter J. Schmid) Published 2020-05-29 Download video MP4 360p Recommendations 44:44 Modern Tools for the Stability Analysis of Fluid Flows (Prof. Peter J. Schmid) 27:49 Koopman Spectral Analysis (Overview) 50:05 Koopman Theory + Embeddings 1:28:45 Nathan Kutz - The Dynamic Mode Decomposition - A Data-Driven Algorithm 18:18 Dynamic Mode Decomposition (Overview) 1:08:52 MIT Robotics - Harry Asada - Koopman Lifting Linearization for Global, Unified Representation ... 1:09:56 Data Driven Discovery of Dynamical Systems and PDEs 47:07 Hankel Alternative View of Koopman (HAVOK) Analysis [FULL] 23:06 VKI Lecture Series - Machine Learning for Fluid Mechanics - Opening Speech 16:34 Residual Dynamic Mode Decomposition: A very easy way to get error bounds for your DMD computations 08:15 Dynamic Mode Decomposition (Code) 43:29 Dynamic Mode Decomposition (Theory) 58:02 Steve Brunton - Machine Learning for Scientific Discovery, with Examples in Fluid Mechanics 21:04 Kernel Learning for Robust Dynamic Mode Decomposition Similar videos 30:32 Dynamic Mode Decomposition from Koopman: Theory to Applications (Prof. Peter J. Schmid) - Part 1 22:29 From Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction 23:42 Physics-Informed Dynamic Mode Decomposition (PI-DMD) 25:59 Modern Tools for the Stability Analysis of Fluid Flows (Prof. Peter J. Schmid) – Part 2 59:28 MWS | Dr. Matthew Colbrook | Residual Dynamic Mode Decomposition: Robust and verified Koopmanism... 01:10 On Analytical Construction of Observable Functions in Extended Dynamic Mode Decomposition for Nonlin 00:06 goldfish2 demo 56:23 Data Driven Control using Dynamic Mode Decomposition and its extensions using Koopman operators 00:12 kidney image sequence stabilisation using Dynamic Mode Decomposition More results