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20072023
most citedA Data-Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition

1.9k citations · 5.7k across the 37 of their papers we have counts for

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Showing 2017 · math.DSShow all

2 papers · 2 filters

math.DS2017

Linearly-Recurrent Autoencoder Networks for Learning Dynamics

Samuel E. Otto, Clarence W. Rowley

This paper describes a method for learning low-dimensional approximations of nonlinear dynamical systems, based on neural-network approximations of the underlying Koopman operator.…

math.DS2017★ 4 cited

Evaluating the accuracy of the dynamic mode decomposition

Hao Zhang, Scott T. M. Dawson, Clarence W. Rowley +2

Dynamic mode decomposition (DMD) gives a practical means of extracting dynamic information from data, in the form of spatial modes and their associated frequencies and growth/decay…