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09/24/2022
One-Shot Learning of Stochastic Differential Equations with Computational Graph Completion
We consider the problem of learning Stochastic Differential Equations of...
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11/25/2021
Learning dynamical systems from data: A simple cross-validation perspective, part III: Irregularly-Sampled Time Series
A simple and interpretable way to learn a dynamical system from data is ...
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12/01/2020
Kernel methods for center manifold approximation and a data-based version of the Center Manifold Theorem
For dynamical systems with a non hyperbolic equilibrium, it is possible ...
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07/09/2020
Learning dynamical systems from data: a simple cross-validation perspective
Regressing the vector field of a dynamical system from a finite number o...
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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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04/18/2019
A kernel-based method for coarse graining complex dynamical systems
We present a novel kernel-based machine learning algorithm for identifyi...
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04/25/2018
A Note on Kernel Methods for Multiscale Systems with Critical Transitions
We study the maximum mean discrepancy (MMD) in the context of critical t...
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04/03/2012
Kernel Methods for the Approximation of Some Key Quantities of Nonlinear Systems
We introduce a data-based approach to estimating key quantities which ar...
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08/14/2011
Kernel Methods for the Approximation of Nonlinear Systems
We introduce a data-driven order reduction method for nonlinear control ...
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11/12/2010