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07/01/2023
Understanding recent deep-learning techniques for identifying collective variables of molecular dynamics
The dynamics of a high-dimensional metastable molecular system can often...
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05/04/2023
Impact Study of Numerical Discretization Accuracy on Parameter Reconstructions and Model Parameter Distributions
Numerical models are used widely for parameter reconstructions in the fi...
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12/13/2021
Data-driven modelling of nonlinear dynamics by polytope projections and memory
We present a numerical method to model dynamical systems from data. We u...
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01/07/2021
CINDy: Conditional gradient-based Identification of Non-linear Dynamics – Noise-robust recovery
Governing equations are essential to the study of nonlinear dynamics, of...
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12/14/2020
Data-driven model reduction of agent-based systems using the Koopman generator
The dynamical behavior of social systems can be described by agent-based...
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11/25/2020
Feature space approximation for kernel-based supervised learning
We propose a method for the approximation of high- or even infinite-dime...
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04/02/2020
Kernel autocovariance operators of stationary processes: Estimation and convergence
We consider autocovariance operators of a stationary stochastic process ...
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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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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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09/28/2018
A kernel-based approach to molecular conformation analysis
We present a novel machine learning approach to understanding conformati...
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07/24/2018
Singular Value Decomposition of Operators on Reproducing Kernel Hilbert Spaces
Reproducing kernel Hilbert spaces (RKHSs) play an important role in many...
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06/11/2015
