Feliks Nüske

1.3k total citations
21 papers, 762 citations indexed

About

Feliks Nüske is a scholar working on Statistical and Nonlinear Physics, Molecular Biology and Statistics, Probability and Uncertainty. According to data from OpenAlex, Feliks Nüske has authored 21 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Statistical and Nonlinear Physics, 11 papers in Molecular Biology and 8 papers in Statistics, Probability and Uncertainty. Recurrent topics in Feliks Nüske's work include Model Reduction and Neural Networks (12 papers), Protein Structure and Dynamics (11 papers) and Probabilistic and Robust Engineering Design (8 papers). Feliks Nüske is often cited by papers focused on Model Reduction and Neural Networks (12 papers), Protein Structure and Dynamics (11 papers) and Probabilistic and Robust Engineering Design (8 papers). Feliks Nüske collaborates with scholars based in Germany, United States and United Kingdom. Feliks Nüske's co-authors include Frank Noé, Stefan Klus, Cecilia Clementi, Sebastian Peitz, Antonia S. J. S. Mey, Bettina G. Keller, Guillermo Pérez‐Hernández, Christof Schütte, Hao Wu and Friedrich Philipp and has published in prestigious journals such as The Journal of Chemical Physics, Automatica and Journal of Chemical Theory and Computation.

In The Last Decade

Feliks Nüske

18 papers receiving 732 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Feliks Nüske Germany 12 370 318 142 123 104 21 762
Carsten Hartmann Germany 16 315 0.9× 152 0.5× 70 0.5× 101 0.8× 86 0.8× 57 620
Yan Pan United States 21 86 0.2× 383 1.2× 73 0.5× 30 0.2× 15 0.1× 53 1.1k
Andreas Dechant Japan 20 900 2.4× 104 0.3× 80 0.6× 38 0.3× 100 1.0× 30 1.0k
U. E. Vincent Nigeria 26 1.3k 3.6× 64 0.2× 46 0.3× 14 0.1× 73 0.7× 83 1.6k
Vı́ctor Fairén Spain 15 250 0.7× 128 0.4× 64 0.5× 5 0.0× 23 0.2× 39 670
Pierre Barthelemy Italy 9 174 0.5× 162 0.5× 104 0.7× 6 0.0× 208 2.0× 12 1.0k
Tobias Jahnke Germany 15 180 0.5× 330 1.0× 15 0.1× 28 0.2× 26 0.3× 32 805
Chuang Li China 14 578 1.6× 107 0.3× 47 0.3× 8 0.1× 65 0.6× 33 1.4k
Andre C. Barato Germany 18 1.6k 4.3× 273 0.9× 144 1.0× 50 0.4× 169 1.6× 42 1.8k
Thomas Wellens Germany 17 393 1.1× 124 0.4× 34 0.2× 48 0.4× 300 2.9× 58 1.1k

Countries citing papers authored by Feliks Nüske

Since Specialization
Citations

This map shows the geographic impact of Feliks Nüske's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Feliks Nüske with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feliks Nüske more than expected).

Fields of papers citing papers by Feliks Nüske

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Feliks Nüske. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Feliks Nüske. The network helps show where Feliks Nüske may publish in the future.

Co-authorship network of co-authors of Feliks Nüske

This figure shows the co-authorship network connecting the top 25 collaborators of Feliks Nüske. A scholar is included among the top collaborators of Feliks Nüske based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Feliks Nüske. Feliks Nüske is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Berger, Thomas & Feliks Nüske. (2025). Funnel control for Langevin dynamics. Automatica. 179. 112448–112448. 1 indexed citations
2.
Nüske, Feliks, et al.. (2025). Kinetically Consistent Coarse Graining Using Kernel-Based Extended Dynamic Mode Decomposition. Journal of Chemical Theory and Computation. 21(15). 7236–7248. 2 indexed citations
3.
Chen, Weilong, et al.. (2025). Thermodynamic Interpolation: A Generative Approach to Molecular Thermodynamics and Kinetics. Journal of Chemical Theory and Computation. 21(5). 2535–2545. 6 indexed citations
4.
Cao, Siqin, et al.. (2025). AMUSET-TICA: A Tensor-Based Approach for Identifying Slow Collective Variables in Biomolecular Dynamics. Journal of Chemical Theory and Computation. 21(9). 4855–4866.
5.
Philipp, Friedrich, et al.. (2025). Error Analysis of Kernel EDMD for Prediction and Control in the Koopman Framework. Journal of Nonlinear Science. 35(5). 1 indexed citations
6.
Peitz, Sebastian, H. Harder, Feliks Nüske, et al.. (2024). Equivariance and partial observations in Koopman operator theory for partial differential equations. 12(2). 305–324. 3 indexed citations
7.
Philipp, Friedrich, Manuel Schaller, Karl Worthmann, Sebastian Peitz, & Feliks Nüske. (2024). Error bounds for kernel-based approximations of the Koopman operator. Applied and Computational Harmonic Analysis. 71. 101657–101657. 15 indexed citations
8.
Nüske, Feliks & Stefan Klus. (2023). Efficient approximation of molecular kinetics using random Fourier features. The Journal of Chemical Physics. 159(7). 9 indexed citations
9.
Schaller, Manuel, Karl Worthmann, Friedrich Philipp, Sebastian Peitz, & Feliks Nüske. (2023). Towards reliable data-based optimal and predictive control using extended DMD. IFAC-PapersOnLine. 56(1). 169–174. 19 indexed citations
10.
Nüske, Feliks, et al.. (2023). Slicing and Dicing: Optimal Coarse-Grained Representation to Preserve Molecular Kinetics. ACS Central Science. 9(2). 186–196. 11 indexed citations
11.
Nüske, Feliks, Sebastian Peitz, Friedrich Philipp, Manuel Schaller, & Karl Worthmann. (2022). Finite-Data Error Bounds for Koopman-Based Prediction and Control. Journal of Nonlinear Science. 33(1). 42 indexed citations
12.
Nüske, Feliks, et al.. (2022). tgEDMD: Approximation of the Kolmogorov Operator in Tensor Train Format. Journal of Nonlinear Science. 32(4). 4 indexed citations
13.
Nüske, Feliks. (2021). Spectral Properties of Effective Dynamics from Conditional Expectations. MDPI (MDPI AG). 7 indexed citations
14.
Klus, Stefan, Feliks Nüske, & Boumediene Hamzi. (2020). Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator. Refubium (Universitätsbibliothek der Freien Universität Berlin). 35 indexed citations
15.
Klus, Stefan, et al.. (2020). Data-driven approximation of the Koopman generator: Model reduction, system identification, and control. Physica D Nonlinear Phenomena. 406. 132416–132416. 173 indexed citations
16.
Nüske, Feliks, et al.. (2018). Quantitative comparison of adaptive sampling methods for protein dynamics. The Journal of Chemical Physics. 149(24). 244119–244119. 37 indexed citations
17.
Boninsegna, Lorenzo, Hao Wu, Feliks Nüske, et al.. (2018). Rapid Calculation of Molecular Kinetics Using Compressed Sensing. Journal of Chemical Theory and Computation. 14(5). 2771–2783. 21 indexed citations
18.
Nüske, Feliks, Hao Wu, Jan-Hendrik Prinz, et al.. (2017). Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias. The Journal of Chemical Physics. 146(9). 46 indexed citations
19.
Wu, Hao, Feliks Nüske, Fabian Paul, et al.. (2017). Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations. The Journal of Chemical Physics. 146(15). 154104–154104. 90 indexed citations
20.
Nüske, Feliks, Bettina G. Keller, Guillermo Pérez‐Hernández, Antonia S. J. S. Mey, & Frank Noé. (2014). Variational Approach to Molecular Kinetics. Journal of Chemical Theory and Computation. 10(4). 1739–1752. 205 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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