Stefan Klus

According to our database, Stefan Klus authored at least 33 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Clustering Time-Snapshots of Temporal Networks: From Synthetic Data to Real-World Applications.

Filip Blaskovic, Tim O. F. Conrad, Stefan Klus, Natasa Djurdjevac Conrad

CoRR, 2024

Learning dynamical systems from data: Gradient-based dictionary optimization.

Mohammad Tabish, Neil K. Chada, Stefan Klus

CoRR, 2024

Clustering Time-Evolving Networks Using the Dynamic Graph Laplacian.

Maia Trower, Natasa Djurdjevac Conrad, Stefan Klus

CoRR, 2024

Data-driven approximation of Koopman operators and generators: Convergence rates and error bounds.

Liam Llamazares-Elias, Samir Llamazares-Elías, Jonas Latz, Stefan Klus

CoRR, 2024

2023

Overcoming the timescale barrier in molecular dynamics: Transfer operators, variational principles and machine learning.

Christof Schütte, Stefan Klus, Carsten Hartmann

Acta Numer., May, 2023

Koopman-Based Spectral Clustering of Directed and Time-Evolving Graphs.

Stefan Klus, Natasa Djurdjevac Conrad

J. Nonlinear Sci., 2023

Continuous optimization methods for the graph isomorphism problem.

Stefan Klus, Patrick Gelß

CoRR, 2023

Transfer operators on graphs: Spectral clustering and beyond.

Stefan Klus, Maia Trower

CoRR, 2023

2022

Deeptime: a Python library for machine learning dynamical models from time series data.

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

Mach. Learn. Sci. Technol., 2022

Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence.

Mattes Mollenhauer, Stefan Klus, Christof Schütte, Péter Koltai

J. Mach. Learn. Res., 2022

A Dynamic Mode Decomposition Approach for Decentralized Spectral Clustering of Graphs.

Hongyu Zhu, Stefan Klus, Tuhin Sahai

Proceedings of the IEEE Conference on Control Technology and Applications, 2022

2021

Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry.

Stefan Klus, Patrick Gelß, Feliks Nüske, Frank Noé

Mach. Learn. Sci. Technol., 2021

Feature space approximation for kernel-based supervised learning.

Patrick Gelß, Stefan Klus, Ingmar Schuster, Christof Schütte

Knowl. Based Syst., 2021

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

Andreas Bittracher, Stefan Klus, Boumediene Hamzi, Péter Koltai, Christof Schütte

J. Nonlinear Sci., 2021

2020

Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces.

Stefan Klus, Ingmar Schuster, Krikamol Muandet

J. Nonlinear Sci., 2020

Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator.

Stefan Klus, Feliks Nüske, Boumediene Hamzi

Entropy, 2020

GraphKKE: graph Kernel Koopman embedding for human microbiome analysis.

Kateryna Melnyk, Stefan Klus, Grégoire Montavon, Tim O. F. Conrad

Appl. Netw. Sci., 2020

Kernel Conditional Density Operators.

Ingmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Learning Chemical Reaction Networks from Trajectory Data.

Wei Zhang, Stefan Klus, Tim O. F. Conrad, Christof Schütte

SIAM J. Appl. Dyn. Syst., 2019

Tensor-based EDMD for the Koopman analysis of high-dimensional systems.

Feliks Nüske, Patrick Gelß, Stefan Klus, Cecilia Clementi

CoRR, 2019

Koopman operator-based model reduction for switched-system control of PDEs.

Sebastian Peitz, Stefan Klus

Autom., 2019

Tensor-Based Algorithms for Image Classification.

Stefan Klus, Patrick Gelß

Algorithms, 2019

2018

Data-Driven Model Reduction and Transfer Operator Approximation.

Stefan Klus, Feliks Nüske, Péter Koltai, Hao Wu, Ioannis G. Kevrekidis, Christof Schütte, Frank Noé

J. Nonlinear Sci., 2018

Transition Manifolds of Complex Metastable Systems - Theory and Data-Driven Computation of Effective Dynamics.

Andreas Bittracher, Péter Koltai, Stefan Klus, Ralf Banisch, Michael Dellnitz, Christof Schütte

J. Nonlinear Sci., 2018

A kernel-based approach to molecular conformation analysis.

Stefan Klus, Andreas Bittracher, Ingmar Schuster, Christof Schütte

CoRR, 2018

Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions.

Stefan Klus, Sebastian Peitz, Ingmar Schuster

CoRR, 2018

2017

A Set-Oriented Numerical Approach for Dynamical Systems with Parameter Uncertainty.

Michael Dellnitz, Stefan Klus, Adrian Ziessler

SIAM J. Appl. Dyn. Syst., 2017

Nearest-neighbor interaction systems in the tensor-train format.

Patrick Gelß, Stefan Klus, Sebastian Matera, Christof Schütte

J. Comput. Phys., 2017

Continuous Relaxations for the Traveling Salesman Problem.

Tuhin Sahai, Stefan Klus, Michael Dellnitz

CoRR, 2017

2015

Sparse Automatic Differentiation for Large-Scale Computations Using Abstract Elementary Algebra.

Slaven Peles, Stefan Klus

CoRR, 2015

2014

A Spectral Assignment Approach for the Graph Isomorphism Problem.

Stefan Klus, Tuhin Sahai

CoRR, 2014

2012

A Traveling Salesman Learns Bayesian Networks

Tuhin Sahai, Stefan Klus, Michael Dellnitz

CoRR, 2012

2011

An efficient algorithm for the parallel solution of high-dimensional differential equations.

Stefan Klus, Tuhin Sahai, Cong Liu, Michael Dellnitz

J. Comput. Appl. Math., 2011