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07/28/2023
Partial observations, coarse graining and equivariance in Koopman operator theory for large-scale dynamical systems
The Koopman operator has become an essential tool for data-driven analys...
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03/31/2021
Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry
We derive symmetric and antisymmetric kernels by symmetrizing and antisy...
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05/27/2020
Kernel-based approximation of the Koopman generator and Schrödinger operator
Many dimensionality and model reduction techniques rely on estimating do...
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09/23/2019
Data-driven approximation of the Koopman generator: Model reduction, system identification, and control
We derive a data-driven method for the approximation of the Koopman gene...
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08/12/2019
Tensor-based EDMD for the Koopman analysis of high-dimensional systems
Recent years have seen rapid advances in the data-driven analysis of dyn...
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12/06/2017
Sparse learning of stochastic dynamic equations
With the rapid increase of available data for complex systems, there is ...
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10/20/2016
