Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition Manifolds

18 Apr 2019Andreas BittracherStefan KlusBoumediene HamziPéter KoltaiChristof Schütte

We present a novel kernel-based machine learning algorithm for identifying the low-dimensional geometry of the effective dynamics of high-dimensional multiscale stochastic systems. Recently, the authors developed a mathematical framework for the computation of optimal reaction coordinates of such systems that is based on learning a parametrization of a low-dimensional transition manifold in a certain function space... (read more)

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