Feliks Nüske

Lehrstuhl für Angewandte Mathematik
feliks.nueske@uni-paderborn.de
ID
81513

18 Publications

Mark all

[18]
2023 | Conference Paper | LibreCat-ID: 30125 | OA
Schaller, M., Worthmann, K., Philipp, F., Peitz, S., & Nüske, F. (2023). Towards reliable data-based optimal and predictive control using extended DMD. IFAC-PapersOnLine, 56(1), 169–174. https://doi.org/10.1016/j.ifacol.2023.02.029
LibreCat | DOI | Download (ext.) | arXiv
 
[17]
2023 | Journal Article | LibreCat-ID: 23428 | OA
Nüske, F., Peitz, S., Philipp, F., Schaller, M., & Worthmann, K. (2023). Finite-data error bounds for Koopman-based prediction and control. Journal of Nonlinear Science, 33, Article 14. https://doi.org/10.1007/s00332-022-09862-1
LibreCat | DOI | Download (ext.)
 
[16]
2022 | Journal Article | LibreCat-ID: 29673 | OA
Klus, S., Nüske, F., & Peitz, S. (2022). Koopman analysis of quantum systems. Journal of Physics A: Mathematical and Theoretical, 55(31), 314002. https://doi.org/10.1088/1751-8121/ac7d22
LibreCat | DOI | Download (ext.) | arXiv
 
[15]
2021 | Journal Article | LibreCat-ID: 24169
Nüske, F., Gelß, P., Klus, S., & Clementi, C. (2021). Tensor-based computation of metastable and coherent sets. Physica D: Nonlinear Phenomena, Article 133018. https://doi.org/10.1016/j.physd.2021.133018
LibreCat | DOI
 
[14]
2021 | Journal Article | LibreCat-ID: 24170
Klus, S., Gelß, P., Nüske, F., & Noé, F. (2021). Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry. Machine Learning: Science and Technology, Article 045016. https://doi.org/10.1088/2632-2153/ac14ad
LibreCat | DOI
 
[13]
2021 | Journal Article | LibreCat-ID: 21820 | OA
Nüske, F., Koltai, P., Boninsegna, L., & Clementi, C. (2021). Spectral Properties of Effective Dynamics from Conditional Expectations. Entropy. https://doi.org/10.3390/e23020134
LibreCat | DOI | Download (ext.)
 
[12]
2020 | Journal Article | LibreCat-ID: 21819 | OA
Klus, S., Nüske, F., & Hamzi, B. (2020). Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator. Entropy. https://doi.org/10.3390/e22070722
LibreCat | DOI | Download (ext.)
 
[11]
2020 | Journal Article | LibreCat-ID: 16288
Klus, S., Nüske, F., Peitz, S., Niemann, J.-H., Clementi, C., & Schütte, C. (2020). Data-driven approximation of the Koopman generator: Model reduction, system identification, and control. Physica D: Nonlinear Phenomena, 406. https://doi.org/10.1016/j.physd.2020.132416
LibreCat | DOI
 
[10]
2019 | Journal Article | LibreCat-ID: 21944
Nüske, F., Boninsegna, L., & Clementi, C. (2019). Coarse-graining molecular systems by spectral matching. The Journal of Chemical Physics. https://doi.org/10.1063/1.5100131
LibreCat | DOI
 
[9]
2018 | Journal Article | LibreCat-ID: 21940
Litzinger, F., Boninsegna, L., Wu, H., Nüske, F., Patel, R., Baraniuk, R., … Clementi, C. (2018). Rapid Calculation of Molecular Kinetics Using Compressed Sensing. Journal of Chemical Theory and Computation, 2771–2783. https://doi.org/10.1021/acs.jctc.8b00089
LibreCat | DOI
 
[8]
2018 | Journal Article | LibreCat-ID: 21941
Klus, S., Nüske, F., Koltai, P., Wu, H., Kevrekidis, I., Schütte, C., & Noé, F. (2018). Data-Driven Model Reduction and Transfer Operator Approximation. Journal of Nonlinear Science, 985–1010. https://doi.org/10.1007/s00332-017-9437-7
LibreCat | DOI
 
[7]
2018 | Journal Article | LibreCat-ID: 21942
Boninsegna, L., Nüske, F., & Clementi, C. (2018). Sparse learning of stochastic dynamical equations. The Journal of Chemical Physics. https://doi.org/10.1063/1.5018409
LibreCat | DOI
 
[6]
2018 | Journal Article | LibreCat-ID: 21943
Hruska, E., Abella, J. R., Nüske, F., Kavraki, L. E., & Clementi, C. (2018). Quantitative comparison of adaptive sampling methods for protein dynamics. The Journal of Chemical Physics. https://doi.org/10.1063/1.5053582
LibreCat | DOI
 
[5]
2017 | Journal Article | LibreCat-ID: 21938
Nüske, F., Wu, H., Prinz, J.-H., Wehmeyer, C., Clementi, C., & Noé, F. (2017). Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias. The Journal of Chemical Physics. https://doi.org/10.1063/1.4976518
LibreCat | DOI
 
[4]
2017 | Journal Article | LibreCat-ID: 21939
Wu, H., Nüske, F., Paul, F., Klus, S., Koltai, P., & Noé, F. (2017). Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations. The Journal of Chemical Physics. https://doi.org/10.1063/1.4979344
LibreCat | DOI
 
[3]
2016 | Journal Article | LibreCat-ID: 21937
Nüske, F., Schneider, R., Vitalini, F., & Noé, F. (2016). Variational tensor approach for approximating the rare-event kinetics of macromolecular systems. The Journal of Chemical Physics. https://doi.org/10.1063/1.4940774
LibreCat | DOI
 
[2]
2014 | Journal Article | LibreCat-ID: 21936
Nüske, F., Keller, B. G., Pérez-Hernández, G., Mey, A. S. J. S., & Noé, F. (2014). Variational Approach to Molecular Kinetics. Journal of Chemical Theory and Computation, 1739–1752. https://doi.org/10.1021/ct4009156
LibreCat | DOI
 
[1]
2013 | Journal Article | LibreCat-ID: 21935
Noé, F., & Nüske, F. (2013). A Variational Approach to Modeling Slow Processes in Stochastic Dynamical Systems. Multiscale Modeling & Simulation, 635–655. https://doi.org/10.1137/110858616
LibreCat | DOI
 
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18 Publications

Mark all

[18]
2023 | Conference Paper | LibreCat-ID: 30125 | OA
Schaller, M., Worthmann, K., Philipp, F., Peitz, S., & Nüske, F. (2023). Towards reliable data-based optimal and predictive control using extended DMD. IFAC-PapersOnLine, 56(1), 169–174. https://doi.org/10.1016/j.ifacol.2023.02.029
LibreCat | DOI | Download (ext.) | arXiv
 
[17]
2023 | Journal Article | LibreCat-ID: 23428 | OA
Nüske, F., Peitz, S., Philipp, F., Schaller, M., & Worthmann, K. (2023). Finite-data error bounds for Koopman-based prediction and control. Journal of Nonlinear Science, 33, Article 14. https://doi.org/10.1007/s00332-022-09862-1
LibreCat | DOI | Download (ext.)
 
[16]
2022 | Journal Article | LibreCat-ID: 29673 | OA
Klus, S., Nüske, F., & Peitz, S. (2022). Koopman analysis of quantum systems. Journal of Physics A: Mathematical and Theoretical, 55(31), 314002. https://doi.org/10.1088/1751-8121/ac7d22
LibreCat | DOI | Download (ext.) | arXiv
 
[15]
2021 | Journal Article | LibreCat-ID: 24169
Nüske, F., Gelß, P., Klus, S., & Clementi, C. (2021). Tensor-based computation of metastable and coherent sets. Physica D: Nonlinear Phenomena, Article 133018. https://doi.org/10.1016/j.physd.2021.133018
LibreCat | DOI
 
[14]
2021 | Journal Article | LibreCat-ID: 24170
Klus, S., Gelß, P., Nüske, F., & Noé, F. (2021). Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry. Machine Learning: Science and Technology, Article 045016. https://doi.org/10.1088/2632-2153/ac14ad
LibreCat | DOI
 
[13]
2021 | Journal Article | LibreCat-ID: 21820 | OA
Nüske, F., Koltai, P., Boninsegna, L., & Clementi, C. (2021). Spectral Properties of Effective Dynamics from Conditional Expectations. Entropy. https://doi.org/10.3390/e23020134
LibreCat | DOI | Download (ext.)
 
[12]
2020 | Journal Article | LibreCat-ID: 21819 | OA
Klus, S., Nüske, F., & Hamzi, B. (2020). Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator. Entropy. https://doi.org/10.3390/e22070722
LibreCat | DOI | Download (ext.)
 
[11]
2020 | Journal Article | LibreCat-ID: 16288
Klus, S., Nüske, F., Peitz, S., Niemann, J.-H., Clementi, C., & Schütte, C. (2020). Data-driven approximation of the Koopman generator: Model reduction, system identification, and control. Physica D: Nonlinear Phenomena, 406. https://doi.org/10.1016/j.physd.2020.132416
LibreCat | DOI
 
[10]
2019 | Journal Article | LibreCat-ID: 21944
Nüske, F., Boninsegna, L., & Clementi, C. (2019). Coarse-graining molecular systems by spectral matching. The Journal of Chemical Physics. https://doi.org/10.1063/1.5100131
LibreCat | DOI
 
[9]
2018 | Journal Article | LibreCat-ID: 21940
Litzinger, F., Boninsegna, L., Wu, H., Nüske, F., Patel, R., Baraniuk, R., … Clementi, C. (2018). Rapid Calculation of Molecular Kinetics Using Compressed Sensing. Journal of Chemical Theory and Computation, 2771–2783. https://doi.org/10.1021/acs.jctc.8b00089
LibreCat | DOI
 
[8]
2018 | Journal Article | LibreCat-ID: 21941
Klus, S., Nüske, F., Koltai, P., Wu, H., Kevrekidis, I., Schütte, C., & Noé, F. (2018). Data-Driven Model Reduction and Transfer Operator Approximation. Journal of Nonlinear Science, 985–1010. https://doi.org/10.1007/s00332-017-9437-7
LibreCat | DOI
 
[7]
2018 | Journal Article | LibreCat-ID: 21942
Boninsegna, L., Nüske, F., & Clementi, C. (2018). Sparse learning of stochastic dynamical equations. The Journal of Chemical Physics. https://doi.org/10.1063/1.5018409
LibreCat | DOI
 
[6]
2018 | Journal Article | LibreCat-ID: 21943
Hruska, E., Abella, J. R., Nüske, F., Kavraki, L. E., & Clementi, C. (2018). Quantitative comparison of adaptive sampling methods for protein dynamics. The Journal of Chemical Physics. https://doi.org/10.1063/1.5053582
LibreCat | DOI
 
[5]
2017 | Journal Article | LibreCat-ID: 21938
Nüske, F., Wu, H., Prinz, J.-H., Wehmeyer, C., Clementi, C., & Noé, F. (2017). Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias. The Journal of Chemical Physics. https://doi.org/10.1063/1.4976518
LibreCat | DOI
 
[4]
2017 | Journal Article | LibreCat-ID: 21939
Wu, H., Nüske, F., Paul, F., Klus, S., Koltai, P., & Noé, F. (2017). Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations. The Journal of Chemical Physics. https://doi.org/10.1063/1.4979344
LibreCat | DOI
 
[3]
2016 | Journal Article | LibreCat-ID: 21937
Nüske, F., Schneider, R., Vitalini, F., & Noé, F. (2016). Variational tensor approach for approximating the rare-event kinetics of macromolecular systems. The Journal of Chemical Physics. https://doi.org/10.1063/1.4940774
LibreCat | DOI
 
[2]
2014 | Journal Article | LibreCat-ID: 21936
Nüske, F., Keller, B. G., Pérez-Hernández, G., Mey, A. S. J. S., & Noé, F. (2014). Variational Approach to Molecular Kinetics. Journal of Chemical Theory and Computation, 1739–1752. https://doi.org/10.1021/ct4009156
LibreCat | DOI
 
[1]
2013 | Journal Article | LibreCat-ID: 21935
Noé, F., & Nüske, F. (2013). A Variational Approach to Modeling Slow Processes in Stochastic Dynamical Systems. Multiscale Modeling & Simulation, 635–655. https://doi.org/10.1137/110858616
LibreCat | DOI
 
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Search

Filter Publications

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Citation Style: APA

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