16 Publications

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[16]
2021 | Preprint | LibreCat-ID: 23428
F. Nüske, S. Peitz, F. Philipp, M. Schaller, and K. Worthmann, “Finite-data error bounds for Koopman-based prediction and control,” arXiv:2108.07102. 2021.
LibreCat | Download (ext.)
 
[15]
2021 | Journal Article | LibreCat-ID: 24170
S. Klus, P. Gelß, F. Nüske, and F. Noé, “Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry,” Machine Learning: Science and Technology, Art. no. 045016, 2021, doi: 10.1088/2632-2153/ac14ad.
LibreCat | DOI
 
[14]
2021 | Journal Article | LibreCat-ID: 24169
F. Nüske, P. Gelß, S. Klus, and C. Clementi, “Tensor-based computation of metastable and coherent sets,” Physica D: Nonlinear Phenomena, Art. no. 133018, 2021, doi: 10.1016/j.physd.2021.133018.
LibreCat | DOI
 
[13]
2021 | Journal Article | LibreCat-ID: 21820
F. Nüske, P. Koltai, L. Boninsegna, and C. Clementi, “Spectral Properties of Effective Dynamics from Conditional Expectations,” Entropy, 2021.
LibreCat | DOI | Download (ext.)
 
[12]
2020 | Journal Article | LibreCat-ID: 16288
S. Klus, F. Nüske, S. Peitz, J.-H. Niemann, C. Clementi, and C. Schütte, “Data-driven approximation of the Koopman generator: Model reduction, system identification, and control,” Physica D: Nonlinear Phenomena, vol. 406, 2020.
LibreCat | DOI
 
[11]
2020 | Journal Article | LibreCat-ID: 21819
S. Klus, F. Nüske, and B. Hamzi, “Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator,” Entropy, 2020.
LibreCat | DOI | Download (ext.)
 
[10]
2019 | Journal Article | LibreCat-ID: 21944
F. Nüske, L. Boninsegna, and C. Clementi, “Coarse-graining molecular systems by spectral matching,” The Journal of Chemical Physics, 2019.
LibreCat | DOI
 
[9]
2018 | Journal Article | LibreCat-ID: 21941
S. Klus et al., “Data-Driven Model Reduction and Transfer Operator Approximation,” Journal of Nonlinear Science, pp. 985–1010, 2018.
LibreCat | DOI
 
[8]
2018 | Journal Article | LibreCat-ID: 21942
L. Boninsegna, F. Nüske, and C. Clementi, “Sparse learning of stochastic dynamical equations,” The Journal of Chemical Physics, 2018.
LibreCat | DOI
 
[7]
2018 | Journal Article | LibreCat-ID: 21943
E. Hruska, J. R. Abella, F. Nüske, L. E. Kavraki, and C. Clementi, “Quantitative comparison of adaptive sampling methods for protein dynamics,” The Journal of Chemical Physics, 2018.
LibreCat | DOI
 
[6]
2018 | Journal Article | LibreCat-ID: 21940
F. Litzinger et al., “Rapid Calculation of Molecular Kinetics Using Compressed Sensing,” Journal of Chemical Theory and Computation, pp. 2771–2783, 2018.
LibreCat | DOI
 
[5]
2017 | Journal Article | LibreCat-ID: 21939
H. Wu, F. Nüske, F. Paul, S. Klus, P. Koltai, and F. Noé, “Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations,” The Journal of Chemical Physics, 2017.
LibreCat | DOI
 
[4]
2017 | Journal Article | LibreCat-ID: 21938
F. Nüske, H. Wu, J.-H. Prinz, C. Wehmeyer, C. Clementi, and F. Noé, “Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias,” The Journal of Chemical Physics, 2017.
LibreCat | DOI
 
[3]
2016 | Journal Article | LibreCat-ID: 21937
F. Nüske, R. Schneider, F. Vitalini, and F. Noé, “Variational tensor approach for approximating the rare-event kinetics of macromolecular systems,” The Journal of Chemical Physics, 2016.
LibreCat | DOI
 
[2]
2014 | Journal Article | LibreCat-ID: 21936
F. Nüske, B. G. Keller, G. Pérez-Hernández, A. S. J. S. Mey, and F. Noé, “Variational Approach to Molecular Kinetics,” Journal of Chemical Theory and Computation, pp. 1739–1752, 2014.
LibreCat | DOI
 
[1]
2013 | Journal Article | LibreCat-ID: 21935
F. Noé and F. Nüske, “A Variational Approach to Modeling Slow Processes in Stochastic Dynamical Systems,” Multiscale Modeling & Simulation, pp. 635–655, 2013.
LibreCat | DOI
 

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16 Publications

Mark all

[16]
2021 | Preprint | LibreCat-ID: 23428
F. Nüske, S. Peitz, F. Philipp, M. Schaller, and K. Worthmann, “Finite-data error bounds for Koopman-based prediction and control,” arXiv:2108.07102. 2021.
LibreCat | Download (ext.)
 
[15]
2021 | Journal Article | LibreCat-ID: 24170
S. Klus, P. Gelß, F. Nüske, and F. Noé, “Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry,” Machine Learning: Science and Technology, Art. no. 045016, 2021, doi: 10.1088/2632-2153/ac14ad.
LibreCat | DOI
 
[14]
2021 | Journal Article | LibreCat-ID: 24169
F. Nüske, P. Gelß, S. Klus, and C. Clementi, “Tensor-based computation of metastable and coherent sets,” Physica D: Nonlinear Phenomena, Art. no. 133018, 2021, doi: 10.1016/j.physd.2021.133018.
LibreCat | DOI
 
[13]
2021 | Journal Article | LibreCat-ID: 21820
F. Nüske, P. Koltai, L. Boninsegna, and C. Clementi, “Spectral Properties of Effective Dynamics from Conditional Expectations,” Entropy, 2021.
LibreCat | DOI | Download (ext.)
 
[12]
2020 | Journal Article | LibreCat-ID: 16288
S. Klus, F. Nüske, S. Peitz, J.-H. Niemann, C. Clementi, and C. Schütte, “Data-driven approximation of the Koopman generator: Model reduction, system identification, and control,” Physica D: Nonlinear Phenomena, vol. 406, 2020.
LibreCat | DOI
 
[11]
2020 | Journal Article | LibreCat-ID: 21819
S. Klus, F. Nüske, and B. Hamzi, “Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator,” Entropy, 2020.
LibreCat | DOI | Download (ext.)
 
[10]
2019 | Journal Article | LibreCat-ID: 21944
F. Nüske, L. Boninsegna, and C. Clementi, “Coarse-graining molecular systems by spectral matching,” The Journal of Chemical Physics, 2019.
LibreCat | DOI
 
[9]
2018 | Journal Article | LibreCat-ID: 21941
S. Klus et al., “Data-Driven Model Reduction and Transfer Operator Approximation,” Journal of Nonlinear Science, pp. 985–1010, 2018.
LibreCat | DOI
 
[8]
2018 | Journal Article | LibreCat-ID: 21942
L. Boninsegna, F. Nüske, and C. Clementi, “Sparse learning of stochastic dynamical equations,” The Journal of Chemical Physics, 2018.
LibreCat | DOI
 
[7]
2018 | Journal Article | LibreCat-ID: 21943
E. Hruska, J. R. Abella, F. Nüske, L. E. Kavraki, and C. Clementi, “Quantitative comparison of adaptive sampling methods for protein dynamics,” The Journal of Chemical Physics, 2018.
LibreCat | DOI
 
[6]
2018 | Journal Article | LibreCat-ID: 21940
F. Litzinger et al., “Rapid Calculation of Molecular Kinetics Using Compressed Sensing,” Journal of Chemical Theory and Computation, pp. 2771–2783, 2018.
LibreCat | DOI
 
[5]
2017 | Journal Article | LibreCat-ID: 21939
H. Wu, F. Nüske, F. Paul, S. Klus, P. Koltai, and F. Noé, “Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations,” The Journal of Chemical Physics, 2017.
LibreCat | DOI
 
[4]
2017 | Journal Article | LibreCat-ID: 21938
F. Nüske, H. Wu, J.-H. Prinz, C. Wehmeyer, C. Clementi, and F. Noé, “Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias,” The Journal of Chemical Physics, 2017.
LibreCat | DOI
 
[3]
2016 | Journal Article | LibreCat-ID: 21937
F. Nüske, R. Schneider, F. Vitalini, and F. Noé, “Variational tensor approach for approximating the rare-event kinetics of macromolecular systems,” The Journal of Chemical Physics, 2016.
LibreCat | DOI
 
[2]
2014 | Journal Article | LibreCat-ID: 21936
F. Nüske, B. G. Keller, G. Pérez-Hernández, A. S. J. S. Mey, and F. Noé, “Variational Approach to Molecular Kinetics,” Journal of Chemical Theory and Computation, pp. 1739–1752, 2014.
LibreCat | DOI
 
[1]
2013 | Journal Article | LibreCat-ID: 21935
F. Noé and F. Nüske, “A Variational Approach to Modeling Slow Processes in Stochastic Dynamical Systems,” Multiscale Modeling & Simulation, pp. 635–655, 2013.
LibreCat | DOI
 

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Display / Sort

Citation Style: IEEE

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