Kernel methods for detecting coherent structures in dynamical data

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Kernel methods for detecting coherent structures in dynamical data

16 April 2019

Mattes Mollenhauer

Frank Noé

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Papers citing "Kernel methods for detecting coherent structures in dynamical data"

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Title
Dynamical systems and complex networks: A Koopman operator perspective Stefan Klus Natavsa Djurdjevac Conrad 51 3 0 14 May 2024
Transfer operators on graphs: Spectral clustering and beyond Stefan Klus Maia Trower 75 5 0 19 May 2023
Koopman-based spectral clustering of directed and time-evolving graphs Stefan Klus Nataša Djurdjevac Conrad 47 11 0 06 Apr 2022
Deeptime: a Python library for machine learning dynamical models from time series data Moritz Hoffmann Martin K. Scherer Tim Hempel Andreas Mardt Brian M. de Silva ... Stefan Klus Hao Wu N. Kutz Steven L. Brunton Frank Noé AI4CE 101 107 0 28 Oct 2021
Machine Learning Force Fields Oliver T. Unke Stefan Chmiela H. E. Sauceda M. Gastegger I. Poltavsky Kristof T. Schütt A. Tkatchenko K. Müller AI4CE 141 940 0 14 Oct 2020
Spacetime Autoencoders Using Local Causal States Adam T. Rupe James P. Crutchfield CML 140 2 0 12 Oct 2020
The linear conditional expectation in Hilbert space I. Klebanov Björn Sprungk T. Sullivan 80 13 0 27 Aug 2020
Kernel-based approximation of the Koopman generator and Schrödinger operator Stefan Klus Feliks Nuske B. Hamzi 70 59 0 27 May 2020
Tensor-based computation of metastable and coherent sets Feliks Nuske Patrick Gelß Stefan Klus C. Clementi 32 13 0 12 Aug 2019
Singular Value Decomposition of Operators on Reproducing Kernel Hilbert Spaces Mattes Mollenhauer Ingmar Schuster Stefan Klus Christof Schütte 68 19 0 24 Jul 2018