The dynamics of a high-dimensional metastable molecular system can often...
Numerical models are used widely for parameter reconstructions in the fi...
We present a numerical method to model dynamical systems from data. We u...
Governing equations are essential to the study of nonlinear dynamics, of...
The dynamical behavior of social systems can be described by agent-based...
We propose a method for the approximation of high- or even
infinite-dime...
We consider autocovariance operators of a stationary stochastic process ...
We derive a data-driven method for the approximation of the Koopman gene...
We present a novel kernel-based machine learning algorithm for identifyi...
We present a novel machine learning approach to understanding conformati...
Reproducing kernel Hilbert spaces (RKHSs) play an important role in many...
Background: High-throughput proteomics techniques, such as mass spectrom...