Stefan Klus

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 36

Top Topics

Dynamical Model

Spectral Clustering

Top Venues

J. Nonlinear Sci.

Mach. Learn. Sci. Technol.

SIAM J. Appl. Dyn. Syst.

Publications

Liam Llamazares-Elias, Samir Llamazares-Elías, Jonas Latz, Stefan Klus
Data-driven approximation of Koopman operators and generators: Convergence rates and error bounds. CoRR (2024)
Maia Trower, Natasa Djurdjevac Conrad, Stefan Klus
Clustering Time-Evolving Networks Using the Dynamic Graph Laplacian. CoRR (2024)
Stefan Klus, Patrick Gelß
Continuous optimization methods for the graph isomorphism problem. CoRR (2023)
Christof Schütte, Stefan Klus, Carsten Hartmann
Overcoming the timescale barrier in molecular dynamics: Transfer operators, variational principles and machine learning. Acta Numer. 32 (2023)
Stefan Klus, Maia Trower
Transfer operators on graphs: Spectral clustering and beyond. CoRR (2023)
Stefan Klus, Natasa Djurdjevac Conrad
Koopman-Based Spectral Clustering of Directed and Time-Evolving Graphs. J. Nonlinear Sci. 33 (1) (2023)
Moritz Hoffmann, Martin Scherer, Tim Hempel, Andreas Mardt, Brian de Silva, Brooke E. Husic, Stefan Klus, Hao Wu, J. Nathan Kutz, Steven L. Brunton, Frank Noé
Deeptime: a Python library for machine learning dynamical models from time series data. Mach. Learn. Sci. Technol. 3 (1) (2022)
Hongyu Zhu, Stefan Klus, Tuhin Sahai
A Dynamic Mode Decomposition Approach for Decentralized Spectral Clustering of Graphs. CCTA (2022)
Hongyu Zhu, Stefan Klus, Tuhin Sahai
A Dynamic Mode Decomposition Approach for Decentralized Spectral Clustering of Graphs. CoRR (2022)
Mattes Mollenhauer, Stefan Klus, Christof Schütte, Péter Koltai
Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence. J. Mach. Learn. Res. 23 (2022)
Andreas Bittracher, Stefan Klus, Boumediene Hamzi, Péter Koltai, Christof Schütte
Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition Manifolds. J. Nonlinear Sci. 31 (1) (2021)
Patrick Gelß, Stefan Klus, Ingmar Schuster, Christof Schütte
Feature space approximation for kernel-based supervised learning. Knowl. Based Syst. 221 (2021)
Stefan Klus, Patrick Gelß, Feliks Nüske, Frank Noé
Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry. Mach. Learn. Sci. Technol. 2 (4) (2021)
Moritz Hoffmann, Martin Scherer, Tim Hempel, Andreas Mardt, Brian de Silva, Brooke E. Husic, Stefan Klus, Hao Wu, J. Nathan Kutz, Steven L. Brunton, Frank Noé
Deeptime: a Python library for machine learning dynamical models from time series data. CoRR (2021)
Stefan Klus, Ingmar Schuster, Krikamol Muandet
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces. J. Nonlinear Sci. 30 (1) (2020)
Kateryna Melnyk, Stefan Klus, Grégoire Montavon, Tim O. F. Conrad
GraphKKE: Graph Kernel Koopman Embedding for Human Microbiome Analysis. CoRR (2020)
Stefan Klus, Feliks Nüske, Boumediene Hamzi
Kernel-based approximation of the Koopman generator and Schrödinger operator. CoRR (2020)
Ingmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet
Kernel Conditional Density Operators. AISTATS (2020)
Stefan Klus, Feliks Nüske, Boumediene Hamzi
Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator. Entropy 22 (7) (2020)
Patrick Gelß, Stefan Klus, Ingmar Schuster, Christof Schütte
Feature space approximation for kernel-based supervised learning. CoRR (2020)
Kateryna Melnyk, Stefan Klus, Grégoire Montavon, Tim O. F. Conrad
GraphKKE: graph Kernel Koopman embedding for human microbiome analysis. Appl. Netw. Sci. 5 (1) (2020)
Mattes Mollenhauer, Stefan Klus, Christof Schütte, Péter Koltai
Kernel autocovariance operators of stationary processes: Estimation and convergence. CoRR (2020)
Sebastian Peitz, Stefan Klus
Koopman operator-based model reduction for switched-system control of PDEs. Autom. 106 (2019)
Stefan Klus, Patrick Gelß
Tensor-based algorithms for image classification. CoRR (2019)
Stefan Klus, Patrick Gelß
Tensor-Based Algorithms for Image Classification. Algorithms 12 (11) (2019)
Ingmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet
Kernel Conditional Density Operators. CoRR (2019)
Feliks Nüske, Patrick Gelß, Stefan Klus, Cecilia Clementi
Tensor-based EDMD for the Koopman analysis of high-dimensional systems. CoRR (2019)
Wei Zhang, Stefan Klus, Tim O. F. Conrad, Christof Schütte
Learning Chemical Reaction Networks from Trajectory Data. SIAM J. Appl. Dyn. Syst. 18 (4) (2019)
Andreas Bittracher, Péter Koltai, Stefan Klus, Ralf Banisch, Michael Dellnitz, Christof Schütte
Transition Manifolds of Complex Metastable Systems - Theory and Data-Driven Computation of Effective Dynamics. J. Nonlinear Sci. 28 (2) (2018)
Stefan Klus, Sebastian Peitz, Ingmar Schuster
Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions. CoRR (2018)
Stefan Klus, Andreas Bittracher, Ingmar Schuster, Christof Schütte
A kernel-based approach to molecular conformation analysis. CoRR (2018)
Stefan Klus, Feliks Nüske, Péter Koltai, Hao Wu, Ioannis G. Kevrekidis, Christof Schütte, Frank Noé
Data-Driven Model Reduction and Transfer Operator Approximation. J. Nonlinear Sci. 28 (3) (2018)
Michael Dellnitz, Stefan Klus, Adrian Ziessler
A Set-Oriented Numerical Approach for Dynamical Systems with Parameter Uncertainty. SIAM J. Appl. Dyn. Syst. 16 (1) (2017)
Patrick Gelß, Stefan Klus, Sebastian Matera, Christof Schütte
Nearest-neighbor interaction systems in the tensor-train format. J. Comput. Phys. 341 (2017)
Tuhin Sahai, Stefan Klus, Michael Dellnitz
Continuous Relaxations for the Traveling Salesman Problem. CoRR (2017)
Stefan Klus, Ingmar Schuster, Krikamol Muandet
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces. CoRR (2017)
Slaven Peles, Stefan Klus
Sparse Automatic Differentiation for Large-Scale Computations Using Abstract Elementary Algebra. CoRR (2015)
Stefan Klus, Tuhin Sahai
A Spectral Assignment Approach for the Graph Isomorphism Problem. CoRR (2014)
Tuhin Sahai, Stefan Klus, Michael Dellnitz
A Traveling Salesman Learns Bayesian Networks CoRR (2012)
Stefan Klus, Tuhin Sahai, Cong Liu, Michael Dellnitz
An efficient algorithm for the parallel solution of high-dimensional differential equations. J. Comput. Appl. Math. 235 (9) (2011)
Stefan Klus, Tuhin Sahai, Cong Liu, Michael Dellnitz
An efficient algorithm for the parallel solution of high-dimensional differential equations CoRR (2010)