Stefan Klus - RankMe

48 papers A 1Journal 46Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Bayesian Transfer Operators in Reproducing Kernel Hilbert Spaces. CoRR Septimus Boshoff, Sebastian Peitz, Stefan Klus
2025	J	`jnl`	Data-driven analysis of fine-scale badger movement in the UK. PLoS Comput. Biol. Jessica R. Furber, Richard J. Delahay, Ruth Cox, Rosie Woodroffe, Maria O'hagan, Naratip Santitissadeekorn, Stefan Klus, Giovanni Lo Iacono, Mark A. Chambers, David J. B. Lloyd
2025	J	`jnl`	Data-driven approximation of transfer operators for mean-field stochastic differential equations. CoRR Eirini Ioannou, Stefan Klus, Gonçalo Dos Reis
2025	J	`jnl`	Data-driven system identification using quadratic embeddings of nonlinear dynamics. CoRR Stefan Klus, Joel-Pascal N'Konzi
2025	J	`jnl`	How deep is your network? Deep vs. shallow learning of transfer operators. CoRR Mohammad Tabish, Benedict J. Leimkuhler, Stefan Klus
2024	J	`jnl`	Clustering Time-Evolving Networks Using the Dynamic Graph Laplacian. CoRR Maia Trower, Natasa Djurdjevac Conrad, Stefan Klus
2024	J	`jnl`	Clustering Time-Snapshots of Temporal Networks: From Synthetic Data to Real-World Applications. CoRR Filip Blaskovic, Tim O. F. Conrad, Stefan Klus, Natasa Djurdjevac Conrad
2024	J	`jnl`	Data-driven approximation of Koopman operators and generators: Convergence rates and error bounds. CoRR Liam Llamazares-Elias, Samir Llamazares-Elías, Jonas Latz, Stefan Klus
2024	J	`jnl`	Learning dynamical systems from data: Gradient-based dictionary optimization. CoRR Mohammad Tabish, Neil K. Chada, Stefan Klus
2023	J	`jnl`	Continuous optimization methods for the graph isomorphism problem. CoRR Stefan Klus, Patrick Gelß
2023	J	`jnl`	Koopman-Based Spectral Clustering of Directed and Time-Evolving Graphs. J. Nonlinear Sci. Stefan Klus, Natasa Djurdjevac Conrad
2023	J	`jnl`	Overcoming the timescale barrier in molecular dynamics: Transfer operators, variational principles and machine learning. Acta Numer. Christof Schütte, Stefan Klus, Carsten Hartmann
2023	J	`jnl`	Transfer operators on graphs: Spectral clustering and beyond. CoRR Stefan Klus, Maia Trower
2022	—	`conf`	A Dynamic Mode Decomposition Approach for Decentralized Spectral Clustering of Graphs. CCTA Hongyu Zhu, Stefan Klus, Tuhin Sahai
2022	J	`jnl`	A Dynamic Mode Decomposition Approach for Decentralized Spectral Clustering of Graphs. CoRR Hongyu Zhu, Stefan Klus, Tuhin Sahai
2022	J	`jnl`	Deeptime: a Python library for machine learning dynamical models from time series data. Mach. Learn. Sci. Technol. 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
2022	J	`jnl`	Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence. J. Mach. Learn. Res. Mattes Mollenhauer, Stefan Klus, Christof Schütte, Péter Koltai
2021	J	`jnl`	Deeptime: a Python library for machine learning dynamical models from time series data. CoRR 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
2021	J	`jnl`	Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition Manifolds. J. Nonlinear Sci. Andreas Bittracher, Stefan Klus, Boumediene Hamzi, Péter Koltai, Christof Schütte
2021	J	`jnl`	Feature space approximation for kernel-based supervised learning. Knowl. Based Syst. Patrick Gelß, Stefan Klus, Ingmar Schuster, Christof Schütte
2021	J	`jnl`	Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry. Mach. Learn. Sci. Technol. Stefan Klus, Patrick Gelß, Feliks Nüske, Frank Noé
2020	J	`jnl`	Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces. J. Nonlinear Sci. Stefan Klus, Ingmar Schuster, Krikamol Muandet
2020	J	`jnl`	Feature space approximation for kernel-based supervised learning. CoRR Patrick Gelß, Stefan Klus, Ingmar Schuster, Christof Schütte
2020	J	`jnl`	GraphKKE: Graph Kernel Koopman Embedding for Human Microbiome Analysis. CoRR Kateryna Melnyk, Stefan Klus, Grégoire Montavon, Tim O. F. Conrad
2020	J	`jnl`	GraphKKE: graph Kernel Koopman embedding for human microbiome analysis. Appl. Netw. Sci. Kateryna Melnyk, Stefan Klus, Grégoire Montavon, Tim O. F. Conrad
2020	A	`conf`	Kernel Conditional Density Operators. AISTATS Ingmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet
2020	J	`jnl`	Kernel autocovariance operators of stationary processes: Estimation and convergence. CoRR Mattes Mollenhauer, Stefan Klus, Christof Schütte, Péter Koltai
2020	J	`jnl`	Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator. Entropy Stefan Klus, Feliks Nüske, Boumediene Hamzi
2020	J	`jnl`	Kernel-based approximation of the Koopman generator and Schrödinger operator. CoRR Stefan Klus, Feliks Nüske, Boumediene Hamzi
2019	J	`jnl`	Kernel Conditional Density Operators. CoRR Ingmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet
2019	J	`jnl`	Koopman operator-based model reduction for switched-system control of PDEs. Autom. Sebastian Peitz, Stefan Klus
2019	J	`jnl`	Learning Chemical Reaction Networks from Trajectory Data. SIAM J. Appl. Dyn. Syst. Wei Zhang, Stefan Klus, Tim O. F. Conrad, Christof Schütte
2019	J	`jnl`	Tensor-Based Algorithms for Image Classification. Algorithms Stefan Klus, Patrick Gelß
2019	J	`jnl`	Tensor-based EDMD for the Koopman analysis of high-dimensional systems. CoRR Feliks Nüske, Patrick Gelß, Stefan Klus, Cecilia Clementi
2019	J	`jnl`	Tensor-based algorithms for image classification. CoRR Stefan Klus, Patrick Gelß
2018	J	`jnl`	A kernel-based approach to molecular conformation analysis. CoRR Stefan Klus, Andreas Bittracher, Ingmar Schuster, Christof Schütte
2018	J	`jnl`	Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions. CoRR Stefan Klus, Sebastian Peitz, Ingmar Schuster
2018	J	`jnl`	Data-Driven Model Reduction and Transfer Operator Approximation. J. Nonlinear Sci. Stefan Klus, Feliks Nüske, Péter Koltai, Hao Wu, Ioannis G. Kevrekidis, Christof Schütte, Frank Noé
2018	J	`jnl`	Transition Manifolds of Complex Metastable Systems - Theory and Data-Driven Computation of Effective Dynamics. J. Nonlinear Sci. Andreas Bittracher, Péter Koltai, Stefan Klus, Ralf Banisch, Michael Dellnitz, Christof Schütte
2017	J	`jnl`	A Set-Oriented Numerical Approach for Dynamical Systems with Parameter Uncertainty. SIAM J. Appl. Dyn. Syst. Michael Dellnitz, Stefan Klus, Adrian Ziessler
2017	J	`jnl`	Continuous Relaxations for the Traveling Salesman Problem. CoRR Tuhin Sahai, Stefan Klus, Michael Dellnitz
2017	J	`jnl`	Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces. CoRR Stefan Klus, Ingmar Schuster, Krikamol Muandet
2017	J	`jnl`	Nearest-neighbor interaction systems in the tensor-train format. J. Comput. Phys. Patrick Gelß, Stefan Klus, Sebastian Matera, Christof Schütte
2015	J	`jnl`	Sparse Automatic Differentiation for Large-Scale Computations Using Abstract Elementary Algebra. CoRR Slaven Peles, Stefan Klus
2014	J	`jnl`	A Spectral Assignment Approach for the Graph Isomorphism Problem. CoRR Stefan Klus, Tuhin Sahai
2012	J	`jnl`	A Traveling Salesman Learns Bayesian Networks CoRR Tuhin Sahai, Stefan Klus, Michael Dellnitz
2011	J	`jnl`	An efficient algorithm for the parallel solution of high-dimensional differential equations. J. Comput. Appl. Math. Stefan Klus, Tuhin Sahai, Cong Liu, Michael Dellnitz
2010	J	`jnl`	An efficient algorithm for the parallel solution of high-dimensional differential equations CoRR Stefan Klus, Tuhin Sahai, Cong Liu, Michael Dellnitz