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Number of items: 153. AAcevedo, W. and de Wiljes, J. and Reich, S. (2017) Second-order accurate ensemble transform particle filters. SIAM J. Sci. Comput., 39 (5). A1834-A1850. ISSN 1095-7197 (online) BBreiten, T. and Hartmann, Carsten and Neureither, Lara and Sharma, Upanshu (2021) Stochastic gradient descent and fast relaxation to thermodynamic equilibrium: a stochastic control approach. Journal of Mathematical Physics, 62 (12). pp. 1-19. Bittracher, Andreas and Mollenhauer, Mattes and Koltai, Péter and Schütte, Christof (2021) Variational Characterization and Identification of Reaction Coordinates in Stochastic Systems. arXive . pp. 1-33. (Unpublished) Bouanani, Hafida and Hartmann, Carsten and Kebiri, Omar (2021) Model reduction and uncertainty quantification of multiscale diffusions with parameter uncertainties using nonlinear expectations. arXive . pp. 1-22. (Submitted) Barua, Amlan K. and Chew, Ray and Li, Shuwang and Lowengrub, John and Münch, A. and Wagner, B. (2021) Sharp-interface problem of the Ohta-Kawasaki model 2 for symmetric diblock copolymers. Journal of Computational Physics . pp. 1-34. ISSN 0021-9991 (Submitted) Bittracher, Andreas and Klus, Stefan and Hamzi, Boumediene and Koltai, Péter and Schütte, Christof (2020) Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition Manifolds. Journal of Nonlinear Science, 31 (3). pp. 1-41. ISSN 1432-1467 (online) Bittracher, Andreas and Klus, Stefan and Hamzi, Boumediene and Koltai, Péter and Schütte, Christof (2020) Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition Manifolds. Journal of Nonlinear Science, 31 (3). Becker, Simon and Richter, Lorenz (2020) Model order reduction for (stochastic-) delay equations with error bounds. arXive . pp. 1-23. (Submitted) Banisch, R. and Trstanova, Z. and Bittracher, A. and Klus, S. and Koltai, P. (2020) Diffusion maps tailored to arbitrary non-degenerate Ito processes. Applied and computational harmonic analysis, 48 (1). pp. 242-265. ISSN 1063-5203, 1096-603X Becker, Simon and Hartmann, Carsten and Redmann, Martin and Richter, Lorenz (2019) Feedback control theory & Model order reduction for stochastic equations. ArXive . pp. 1-36. (Submitted) Benacchio, T. and Klein, R. (2019) A semi-implicit compressible model for atmospheric flows with seamless access to soundproof and hydrostatic dynamics. Monthly Weather Review, 147 (11). pp. 4221-4240. ISSN Online: 1520-0493; Print: 0027-0644 Blömker, Dirk and Schillings, Claudia and Wacker, Philipp and Weissmann, Simon (2019) Well posedness and convergence analysis of the ensemble Kalman inversion. Inverse Problems, 35 . pp. 1-33. Banisch, Ralf and Koltai, Péter and Padberg-Gehle, Kathrin (2019) Network measures of mixing. Chaos 29, 29 . pp. 1-15. Banisch, Ralf and Hartmann, C. (2016) A sparse Markov chain approximation of LQ-type stochastic control problems. Math. Control Relat. F., 6 (3). pp. 363-389. ISSN 1064-8275 Bittracher, Andreas and Hartmann, C. and Junge, O. and Koltai, Péter (2015) Pseudo generators for under-resolved molecular dynamics. The European Physical Journal Special Topics, 224 (12). pp. 2463-2490. ISSN 1951-6355 CChew, Ray and Benacchio, T. and Hastermann, G. and Klein, R. (2022) A one-step blended soundproof-compressible model with balanced data assimilation: theory and idealised tests. Monthly Weather Review, 150 (8). ISSN 0027-0644; elSSN: 1520-0493 Coghi, Michele and Nilssen, Torstein and Nüsken, Nikolas and Reich, Sebastian (2022) Rough McKean–Vlasov dynamics for robust ensemble Kalman filtering. arxive . pp. 1-44. (In Press) Chen, Yaoyi and Krämer, Andreas and Charron, Nicholas E. and Husic, Brooke E. and Clementi, Cecilia and Noé, Frank (2021) Machine learning implicit solvation for molecular dynamics. The Journal of Chemical Physics, 155 (084101). pp. 1-15. Coghi, Michele and Nilssen, Torstein and Nüsken, Nikolas (2021) Rough McKean-Vlasov dynamics for robust ensemble Kalman filtering. arXive . pp. 1-41. (Submitted) Chew, R. and Benacchio, T. and Hastermann, G. and Klein, R. (2021) Balanced data assimilation with a blended numerical model. Monthly Weather Review . pp. 1-43. (Submitted) Chustagulprom, N. and Reich, S. and Reinhardt, M. (2016) A Hybrid Ensemble Transform Particle Filter for Nonlinear and Spatially Extended Dynamical Systems. SIAM/ASA Journal on Uncertainty Quantification, 4 (1). pp. 592-608. ISSN 2166-2525 DDelle Site, Luigi (2021) Investigation of water-mediated intermolecular interactions with the adaptive resolution simulation technique. Journal of Physics: Condensed Matter, 34 (11). pp. 1-15. Detring, Carola and Müller, Annette and Schielicke, Lisa and Névir, Peter and Rust, Henning W. (2021) Occurrence and transition probabilities of omega and high-over-low blocking in the Euro-Atlantic region. Weather Clim. Dynamics, 2 . pp. 927-952. del Razo, Mauricio J. and Dibak, Manuel and Schütte, Christof and Noé, Frank (2021) Multiscale molecular kinetics by coupling Markov state models and reaction-diffusion dynamics. The Journal of Chemical Physics, 155 (12). Detring, Carola and Müller, Annette and Schielicke, Lisa and Névir, Peter and Rust, Henning W. (2020) Atmospheric blocking types: Frequencies and transitions. European Geosiences Union . pp. 1-33. (Submitted) Duncan, A. and Nüsken, N. and Szpruch, L. (2019) On the geometry of Stein variational gradient descent. SFB 1114 Preprint in arXiv:1912.00894 . (Unpublished) Donati, L. and Heida, M. and Weber, M. and Keller, B. (2018) Estimation of the infinitesimal generator by square-root approximation. Journal of Physics: Condensed Matter, 30 (42). p. 425201. ISSN 0953-8984, ESSN: 1361-648X del Razo, M.J. and Qian, H. and Noé, F. (2018) Grand canonical diffusion-influenced reactions: a stochastic theory with applications to multiscale reaction-diffusion simulations. J. Chem. Phys., 149 (4). 044102. ISSN 0021-9606, ESSN: 1089-7690 Dibak, M. and del Razo, M.J. and De Sancho, D. and Schütte, Ch. and Noé, F. (2018) MSM/RD: Coupling Markov state models of molecular kinetics with reaction-diffusion simulations. Journal of Chemical Physics, 148 (214107). ISSN 0021-9606 Delle Site, L. and Ciccotti, G. and Hartmann, C. (2017) Partitioning a macroscopic system into independent subsystems. Journal of Statistical Mechanics: Theory and Experiment, 2017 . pp. 1-13. FFroyland, Gary and Koltai, Péter (2021) Detecting the birth and death of finite-time coherent sets. arXiv . pp. 1-44. (Submitted) Froyland, Gary and Koltai, Péter and Stahn, Martin (2020) Computation and Optimal Perturbation of Finite-Time Coherent Sets for Aperiodic Flows Without Trajectory Integration. SIAM J. APPLIED DYNAMICAL SYSTEMS, 19 (3). pp. 1659-1700. Fackeldey, K. and Koltai, P. and Névir, P. and Rust, H.W. and Schild, A and Weber, M. (2019) From Metastable to Coherent Sets – time-discretization schemes. Chaos: An Interdisciplinary Journal of Nonlinear Science, 29 (1). 012101. ISSN 1054-1500 (print); 1089-7682 (online) Fischer, M. and Ulbrich, U. and Rust, H.W. (2017) A spatial and seasonal climatology of extreme precipitation return-levels: A case study. Spatial Statistics . pp. 1-25. (In Press) Fischer, M. and Rust, H.W. and Ulbrich, U. (2016) Seasonal Cycle in German Daily Precipitation Extremes. Meteorologische Zeitschrift . pp. 1-11. ISSN 0941-2948 (Submitted) Feireisl, E. and Klein, R. and Novotný, A. and Zatorska, E. (2016) On singular limits arising in the scale analysis of stratified fluid flows. Mathematical Models and Methods in Applied Sciences, World Scientific, 26 (3). pp. 419-443. ISSN Print: 0218-2025 Online: 1793-6314 GGiulietti, P. and Koltai, P. and Vaienti, S. (2021) Targets and holes. Proc. Amer. Math. Soc., 149 . pp. 3293-3306. Garbuno-Inigo, Alfredo and Nüsken, Nikolas and Reich, Sebastian (2020) Affine Invariant Interacting Langevin Dynamics for Bayesian Inference. SIAM J. APPLIED DYNAMICAL SYSTEMS, 19 (3). pp. 1633-1658. Garbuno Inigo, A. and Nüsken, N. and Reich, S. (2019) Affine invariant interacting Langevin dynamics for Bayesian inference. SFB 1114 Preprint in arXiv:1912.02859 . pp. 1-29. (Unpublished) Gräser, C. and Kies, T. (2019) Discretization error estimates for penalty formulations of a linearized Canham-Helfrich-type energy. IMA Journal of Numerical Analysis, 39 (2). pp. 626-649. ISSN 0272-4979 Gerber, S. and Horenko, I. (2017) Toward a direct and scalable identification of reduced models for categorical processes. Proceedings of the National Academy of Sciences, 114 (19). pp. 4863-4868. HHoffmann, Moritz and Scherer, Martin and Hempel, Tim and Mardt, Andreas and de Silva, Brian and Husic, Brooke E. and Klus, Stefan and Wu, Hao and Kutz, Nathan and Brunton, Steven L (2021) Deeptime: a Python library for machine learning dynamical models from time series data. Mach. Learn.: Sci. Technol. 3 (2022), 3 (015009). pp. 1-28. Hartmann, Carsten and Neureither, Lara and Stehlau, Markus (2021) Reachability Analysis of Randomly Perturbed Hamiltonian Systems. IFAC-PapersOnLine, 54 (19). pp. 307-3014. Hittmeir, S. and Klein, R. and Müller, A. and Névir, P. (2021) The Dynamic State Index with Moisture and Phase Changes. J. Math. Phys, 62 (12). pp. 1-12. Hastermann, G. and Reinhardt, M. and Klein, R. and Reich, S. (2021) Balanced data assimilation for highly-oscillatory mechanical systems. Communications in Applied Mathematics & Computational Science, 16 (1). pp. 119-154. Hartmann, C. and Richter, L. (2021) Nonasymptotic bounds for suboptimal importance sampling. arXive . pp. 1-26. (Submitted) Husic, Brooke E. and Charron, Nicholas E. and Lemm, Dominik and Wang, Jiang and Pérez, Adrià and Majewski, Maciej and Krämer, Andreas and Chen, Yaoyi and Olsson, Simon and de Fabritiis, Gianni and Noé, Frank and Clementi, Cecilia (2020) Coarse graining molecular dynamics with graph neural networks. J. Chem. Phys., 153 (194101). pp. 1-17. Helfmann, Luzie and Ribera Borrell, Enric and Schütte, Christof and Koltai, Péter (2020) Extending Transition Path Theory: Periodically Driven and Finite-Time Dynamics. Journal of Nonlinear Science, 30 . pp. 3321-3366. Helfmann, Luzie and Ribera Borrell, Enric and Schütte, Christof and Koltai, Péter (2020) Extending Transition Path Theory: Periodically Driven and Finite-Time Dynamics. Journal of Nonlinear Science . pp. 1-46. ISSN 1432-1467 (online) Hittmeir, S. and Klein, R. and Li, J. and Titi, E. (2020) Global well-posedness for the primitive equations coupled to nonlinear moisture dynamics with phase changes. Nonlinearity, 33 (7). pp. 3206-3236. Hartmann, C. and Neureither, L. and Sharma, U. (2020) Coarse-graining of non-reversible stochastic differential equations: quantitative results and connections to averaging. SIAM Journal on Mathematical Analysis, 52 (3). pp. 2689-2733. Hartmann, Carsten and Neureither, Lara and Sharma, Upanshu (2020) Coarse-graining of non-reversible stochasticdifferential equations: quantitative results and connections to averaging. SIAM Journal on Numerical Analysis, 52 (3). pp. 2689-2733. ISSN 0036-1429 Hittmeir, S. and Klein, R. and Li, J. and Titi, E. (2019) "Global well-posedness for the primitive equations coupled to nonlinear moisture dynamics with phase changes" by Hittmeir, Sabine; Klein, Rupert; Li, Jinkai; Titi, Edriss. Analysis of PDEs . pp. 1-28. ISSN 1907.11199 (Submitted) Hartmann, Carsten and Kebiri, Omar and Neureither, Lara and Richter, Lorenz (2019) Variational approach to rare event simulation using least-squares regression. Chaos, 29 (6). ISSN 1054-1500 (print); 1089-7682 (online) Hartmann, C. and Schütte, Ch. and Zhang, W. (2019) Jarzysnki equality, fluctuation theorems and variance reduction: Mathematical analysis and numerical algorithms. J. Stat. Phys., 175 (6). pp. 1214-1261. ISSN 0022-4715; ESSN: 1572-9613 Hartmann, C. and Schütte, Ch. and Weber, M. and Zhang, W. (2018) Importance sampling in path space for diffusion processes with slow-fast variables. Probab. Theory Rel. Fields, 170 (1-2). pp. 177-228. ISSN 0178-8051 (print) 1432-2064 (online) Hartmann, C. and Richter, L. and Schütte, Ch. and Zhang, W. (2017) Variational characterization of free energy: theory and algorithms. Entropy (Special Issue), 19 (11). pp. 1-27. ISSN 1099-4300 Hittmeir, S. and Klein, R. and Li, J. and Titi, E. (2017) Global well-posedness for passively transported nonlinear moisture dynamics with phase changes. Nonlinearity, 30 (10). pp. 3676-3718. ISSN 0951-7715 Horenko, I. and Gerber, S. and O'Kane, T.J. and Risbey, J.S. and Monselesan, D.P. (2017) On inference and validation of causality relations in climate teleconnections. In: Nonlinear and Stochastic Climate Dynamics. Cambridge University Press, pp. 184-208. ISBN 9781107118140 Hirt, M. and Schielicke, L. and Müller, A. and Névir, P. (2017) Statistical and dynamical analyses of atmospheric blocking with an idealized point vortex model. Tellus A . pp. 1-22. (Submitted) Hartmann, C. and Schütte, Ch. and Zhang, W. (2016) Model reduction algorithms for optimal control and importance sampling of diffusions. Nonlinearity, 29 (8). pp. 2298-2326. ISSN 0951-7715 Horenko, I. and Gerber, S. (2015) Improving clustering by imposing network information. Science Advances, 1 (7). ISSN 2375-2548 Hartmann, C. and Latorre, J.C. and Pavliotis, G. A. and Zhang, W. (2014) Optimal control of multiscale systems using reduced-order models. J. Computational Dynamics, 1 (2). pp. 279-306. ISSN 2158-2505 KKostré, Margarita and Schütte, Christof and Noé, Frank and del Razo, Mauricio J. (2021) Coupling Particle-Based Reaction-Diffusion Simulations with Reservoirs Mediated by Reaction-Diffusion PDEs. Sociaty for Industrial and Applied Mathematics, 19 (4). Klus, Stefan and Gelß, Patrick and Nüske, Feliks and Noé, Frank (2021) Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry. Machine Learning: Science and Technologie, 2 . pp. 1-23. Kies, T. and Gräser, C. (2021) On differentiability of the membrane-mediated mechanical interaction energy of discrete-continuum membrane-particle models. Interfaces and Free Boundaries . pp. 1-22. ISSN 1463-9963 (In Press) Koltai, Péter and von Lindheim, Johannes and Neumayer, Sebastian and Steidl, Gabriele (2021) Transfer Operators from Optimal Transport Plans for Coherent Set Detection. Physica D: Nonlinear Phenomena, 426 . pp. 1-34. Kies, T. and Gräser, C. and Delle Site, L. and Kornhuber, R. (2020) Free energy computation of particles with membrane-mediated interactions via Langevin dynamics. arXiv:2009.14713 . pp. 1-20. (Submitted) Klus, Stefan and Husic, Brooke E. and Mollenhauer, Mattes and Noé, Frank (2019) Kernel methods for detecting coherent structures in dynamical data. Chaos, 29 (12). Koltai, P. and Lie, Han Cheng and Plonka, M. (2019) Fréchet differentiable drift dependence of Perron--Frobenius and Koopman operators for non-deterministic dynamics. Nonlinearity, 32 (11). pp. 4232-4257. ISSN 0951-7715 Klus, S. and Schuster, I. and Muandet, K. (2019) Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces. Journal of Nonlinear Science, 30 . pp. 283-315. Kebiri, Omar and Neureither, Lara and Hartmann, Carsten (2019) Adaptive importance sampling with forward-backward stochastic differential equations. In: Stochastic Dynamics Out of Equilibrium. Springer Proceedings in Mathematics & Statistics, 282 . Springer International Publishing, pp. 265-281. ISBN 978-3-030-15095-2 Kühnlein, C. and Deconinck, W. and Klein, R. and Malardel, S. and Piotrowski, Z. and Smolarkiewicz, P.K. and Szmelter, J. and Wedi, N. (2019) FVM 1.0: a nonhydrostatic finite-volume dynamical core for the IFS. Geosci. Model Dev., 12 (2). pp. 651-676. ISSN 1991-959X, ESSN: 1991-9603 Kies, Tobias (2018) Gradient Methods for Membrane-Mediated Particle Interactions. PhD Thesis . pp. 1-147. Kebiri, O. and Neureither, L. and Hartmann, C. (2018) Singularly perturbed forward-backward stochastic differential equations: application to the optimal control of bilinear systems. Computation, 6 (3). p. 41. ISSN 2079-3197 (online) Koltai, P. and Renger, M. (2018) From Large Deviations to Semidistances of Transport and Mixing: Coherence Analysis for Finite Lagrangian Data. Journal of Nonlinear Science, 28 (5). pp. 1915-1957. ISSN 1432-1467 (online) Koltai, P. and Wu, H. and Noé, F. and Schütte, Ch. (2018) Optimal data-driven estimation of generalized Markov state models for non-equilibrium dynamics. Computation, 6(1) (22). ISSN 2079-3197 (online) Klus, S. and Nüske, F. and Koltai, P. and Wu, H. and Kevrekidis, I. and Schütte, Ch. and Noé, F. (2018) Data-driven model reduction and transfer operator approximation. Journal of Nonlinear Science, 28 (1). pp. 1-26. Koltai, P. and Schütte, Ch. (2018) A multiscale perturbation expansion approach for Markov state modeling of non-stationary molecular dynamics. Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, 16 (4). pp. 1455-1485. ISSN 1540-3459 Koltai, P. and Ciccotti, G. and Schütte, Ch. (2016) On metastability and Markov state models for non-stationary molecular dynamics. Journal of Chemical Physics, 145 (17). p. 174103. Klein, R. and Benacchio, T. (2016) A doubly blended model for multiscale atmospheric dynamics. Journal of the Atmospheric Sciences, 73 . pp. 1179-1186. ISSN Online: 1520-0469 Print: 0022-4928 LLeung, Tsz Yan and Leutbecher, Martin and Reich, Sebastian and Shepherd, Theodore G. (2021) Forecast verification: relating deterministic and probabilistic metrics. Quarterly Journal of the Royal Meteorological Society . pp. 1-17. ISSN 1477-870X (Submitted) Leung, Tsz Yan and Leutbecher, M. and Reich, S. and Shepherd, Th.G. (2020) Impact of the mesoscale range on error growth and the limits to atmospheric predictability. Journal of the Atmospheric Sciences, 77 (11). pp. 3769-3779. ISSN 1520-0469 Leung, T.Y. and Leutbecher, M. and Reich, S. and Shepherd, Th.G. (2019) Atmospheric Predictability: Revisiting the Inherent Finite-Time Barrier. Journal of the Atmospheric Sciences, 76 (12). pp. 3883-3892. ISSN Online: 1520-0469 Print: 0022-4928 Lie, Han Cheng and Schütte, Ch. and Hartmann, C. (2014) Martingale-based gradient descent algorithm for estimating free energy values of diffusions. SIAM J. Sci. Comput. . ISSN 1064-8275 (Submitted) MMaity, Priyanka and Koltai, Péter and Schumacher, Jörg (2021) Large-scale flow in a cubic Rayleigh-B ́enard cell: Long-term turbulence statistics and Markovianity of macrostate transitions. Philosophical Transaction of the Royal Society . pp. 1-13. (In Press) Müller, Annette and Névir, Peter (2021) On the algebra and groups of incompressible vortex dynamics. Journal of Physics A: Mathematical and Theoretical, 54 . pp. 1-34. Miron, P. and Beron-Vera, F.J. and Helfmann, L. and Koltai, P. (2021) Transition paths of marine debris and the stability of the garbage patches. Chaos, 31 . pp. 1-16. Müller, Annette and Niedrich, Benjamin and Névir, Peter (2020) Three-dimensional potential vorticity structures for extreme precipitation events on the convective scale. Tellus A: Dynamic Meteorology and Oceanography, 72 (1). pp. 1-20. ISSN (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/zela20 Mollenhauer, Mattes and Klus, Stefan and Schütte, Christof and Koltai, Péter (2020) Kernel autocovariance operators of stationary processes: Estimation and convergence. arXive . pp. 1-36. (Unpublished) Mardt, Andreas and Pasquali, Luca and Noé, F. and Wu, Hao (2020) Deep learning Markov and Koopman models with physical constraints. Proceedings of Machine Learning Research, 107 . pp. 451-475. Müller, Annette and Névir, Peter (2019) Using the concept of the Dynamic State Index for a scale-dependent analysis of atmospheric blocking. Meteorologische Zeitschrift, 28 (6). pp. 487-498. Miron, P. and Beron-Vera, F.J. and Olascoaga, M.J. and Koltai, P. (2019) Markov-chain-inspired search for MH370. Chaos: An Interdisciplinary Journal of Nonlinear Science, 29 (4). ISSN 1054-1500 (print); 1089-7682 (online) Müller, A. and Névir, P. and Klein, R. (2018) Scale Dependent Analytical Investigation of the Dynamic State Index Concerning the Quasi-Geostrophic Theory. Mathematics of Climate and Weather Forecasting, 4 (1). pp. 1-22. ISSN 2353-6438 (online) Mazza, E. and Ulbrich, U. and Klein, R. (2017) The Tropical Transition of the October 1996 Medicane in the Western Mediterranean Sea: A Warm Seclusion Event. Monthly Weather Review, 145 . pp. 2575-2595. ISSN Online: 1520-0493 Print: 0027-0644 Mey, A.S.J.S. and Wu, H. and Noé, F. (2014) xTRAM: Estimating equilibrium expectations from time-correlated simulation data at multiple thermodynamic states. Phys. Rev. X, 4 (4). 041018. NNüsken, Nikolas and Richter, Lorenz (2021) Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems. ArXive . pp. 1-25. (Submitted) Nüsken, Nikolas and Richter, Lorenz (2021) Solving high-dimensional Hamilton–Jacobi–Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space. Partial Differential Equations and Applications, 2 (48). pp. 1-48. Nüsken, Nikolas and Renger, D.R. Michiel (2021) Stein Variational Gradient Descent:many-particle and long-time asymptotics. arxiv preprint . pp. 1-25. (Submitted) Nüsken, N. and Renger, M. (2021) Stein Variational Gradient Descent: many-particle and long-time asymptotics. arXive . pp. 1-25. (Unpublished) Nüske, Feliks and Koltai, Péter and Boninsegna, Lorenzo and Clementi, Cecilia (2021) Spectral Properties of Effective Dynamics from Conditional Expectations. Entropy, 23 (134). pp. 1-25. Noé, Frank (2020) Machine Learning for Molecular Dynamics on Long Timescales. Machine Learning Meets Quantum Physics . pp. 331-372. Nüsken, N. and Richter, L. (2020) Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space. SFB 1114 Preprint in arXiv . pp. 1-40. (Submitted) Noé, Frank and Tkatchenko, Alexandre and Müller, Klaus-Robert and Clementi, Cecilia (2020) Machine Learning for Molecular Simulation. Annual Review of Physical Chemistry, 71 . pp. 361-390. Noé, F. and Olsson, S. and Köhler, J. and Wu, H. (2019) Boltzmann Generators: Sampling Equilibrium States of Many-Body Systems with Deep Learning. Science, 365 (6457). eaaw1147. Nüsken, N. and Reich, S. (2019) Note on Interacting Langevin Diffusions: Gradient Structure and Ensemble Kalman Sampler by Garbuno-Inigo, Hoffmann, Li and Stuart. arXive . pp. 1-6. (Submitted) Nüske, Feliks and Boninsegna, Lorenzo and Clementi, Cecilia (2019) Coarse-graining molecular systems by spectral matching. J. Chem. Phys., 151 . pp. 1-10. ISSN 0021-9606, ESSN: 1089-7690 Neureither, L. and Hartmann, C. (2019) Time scales and exponential trends to equilibrium: Gaussian model problems. In: Stochastic Dynamics Out of Equilibrium. IHPStochDyn 2017. Springer Proceedings in Mathematics & Statistics, 282 . Springer, pp. 391-410. ISBN 978-3-030-15095-2 Nüsken, N. and Reich, S. and Rozdeba, P.J. (2019) State and parameter estimation from observed signal increments. Entropy, 21 (5). -505. ISSN 1099-4300 Nissen, K.M. and Ulbrich, U. (2017) Increasing frequencies and changing characteristics of heavy precipitation events threatening infrastructure in Europe under climate change. Nat. Hazards Earth Syst. Sci., 17 . pp. 1177-1190. Nüske, F. and Wu, H. and Wehmeyer, C. and Clementi, C. and Noé, F. (2017) Markov State Models from short non-Equilibrium Simulations - Analysis and Correction of Estimation Bias. J. Chem. Phys., 146 . 094104. Nüske, F. and Schneider, R. and Vitalini, F. and Noé, F. (2016) Variational Tensor Approach for Approximating the Rare-Event Kinetics of Macromolecular Systems. J. Chem. Phys., 144 (5). 054105. OO'Kane, T.J. and Monselesan, D.P. and Risbey, J.S. and Horenko, I. and Franzke, Ch.L.E. (2017) On memory, dimension, and atmospheric teleconnection patterns. Math. Clim. Weather Forecast, 3 (1). pp. 1-27. Olsson, Simon and Wu, H. and Paul, F. and Clementi, C. and Noé, F. (2017) Combining experimental and simulation data of molecular processes via augmented Markov models. Proc. Natl. Acad. Sci. USA, 114 . pp. 8265-8270. O’Kane, T.J. and Risbey, J.S. and Monselesan, D.P. and Horenko, I. and Franzke, Ch.L.E. (2015) On the dynamics of persistent states and their secular trends in the waveguides of the Southern Hemisphere troposphere. Climate Dynamics . ISSN Print: 0930-7575, Online: 1432-0894 PPolzin, Robert and Müller, Annette and Rust, Henning W. and Névir, Peter and Koltai, Péter (2022) Direct Bayesian model reduction of smaller scale convective activity conditioned on large-scale dynamics. Nonlinear Processes in Geophysics, 29 (1). pp. 37-52. Paul, F. and Noé, F. and Weikl, T. (2018) Identifying Conformational-Selection and Induced-Fit Aspects in the Binding-Induced Folding of PMI from Markov State Modeling of Atomistic Simulations. J. Phys. Chem. B . Paul, F. and Wehmeyer, C. and Abualrous, E. T. and Wu, H. and Crabtree, M. D. and Schöneberg, J. and Clarke, J. and Freund, C. and Weikl, T. and Noé, F. (2017) Protein-peptide association kinetics beyond the seconds timescale from atomistic simulations. Nat. Comm., 8 (1095). Paul, F. and Weikl, T. (2016) How to Distinguish Conformational Selection and Induced Fit Based on Chemical Relaxation Rates. PLOS Computational Biology . QQuer, J. and Lie, H. (2017) Some connections between importance sampling and enhanced sampling methods in molecular dynamics. Journal of Chemical Physics . pp. 1-19. ISSN 0021-9606 Quer, J. and Donati, L. and Keller, B.G. and Weber, M. (2017) An automatic adaptive importance sampling algorithm for molecular dynamics in reaction coordinates. SIAM J. Sci. Comput. . pp. 1-19. ISSN 1064-8275 (print) (In Press) Quer, J. and Weber, M. (2016) Estimating exit rate for rare event dynamical systems by extrapolation. ZIB-Report . pp. 1-19. ISSN 2192-7782 (online) RReible, Benedikt and Hartmann, Carsten and Delle Site, Luigi (2021) Two-sided Bogoliubov inequality for quantum systems. arXiv . pp. 1-15. Richter, Lorenz and Sallandt, Leon and Nüsken, Nikolas (2021) Solving high-dimensional parabolic PDEs using the tensor train format. Proceedings of the 38th International Conferenceon Machine Learning, 139 . pp. 8998-9009. Richter, Lorenz and Boustati, Ayman and Nüsken, Nikolas and Ruiz, Francisco J. R. and Akyildiz, Ömer Deniz (2020) VarGrad: A Low-Variance Gradient Estimator for Variational Inference. Advances in Neural Information Processing Systems 2020 . pp. 1-25. (Submitted) Ray, Sourav and Sunkara, Vikram and Schütte, Christof and Weber, Marcus (2020) How to calculate pH-dependent binding rates for receptor–ligand systems based on thermodynamic simulations with different binding motifs. Molecular Simulation, 46 (18). pp. 1443-1452. Ritschel, C. and Rust, H.W. and Ulbrich, U. (2017) Precipitation extremes on multiple time scales -- Bartlett-Lewis Rectangular Pulse Model and Intensity-Duration-Frequency curves. Hydrol. Earth Syst. Sci. . pp. 1-20. (Submitted) SSikorski, Alexander and Weber, Marcus and Schütte, Christof (2021) The augmented jump chain – a sparse representationof time-dependent Markov jump processes. Advanced Theory and Simulations, 4(4):2000274, 2021, 4 (4). Schmid, Fabienne and Gagarina, Elena and Klein, R. and Achatz, Ulrich (2021) Towards a numerical laboratory for investigations of gravity-wave 2 mean-ow interactions in the atmosphere. Monthly Weather Review MWR-D-21-0126 . pp. 1-75. (Submitted) Sechi, Renata and Sikorski, Alexander and Weber, Marcus (2021) Estimation of the Koopman generator by Newton’s extrapolation. SIAM Multiscale Modeling & Simulation, 19 (2). pp. 758-774. ISSN print: 1540-3459; online: 1540-3467 Schillings, Claudia and Sprungk, Björn and Wacker, Philipp (2020) On the convergence of the Laplace approximation and noise-level-robustness of Laplace-based Monte Carlo methods for Bayesian inverse problems. Numerische Mathematik, 145 . pp. 915-971. Schulz, R. and von Hansen, Y. and Daldrop, J.O. and Kappler, J. and Noé, F. and Netz, R.R. (2018) Collective hydrogen-bond rearrangement dynamics in liquid water. J. Chem. Phys., 149 (24). -244504. ISSN 0021-9606, ESSN: 1089-7690 Scherer, M. K. and Husic, B.E. and Hoffmann, M. and Paul, F. and Wu, H. and Noé, F. (2018) Variational Selection of Features for Molecular Kinetics. SFB 1114 Preprint in arXiv:1811.11714 . pp. 1-12. (Unpublished) Swenson, D.W.H. and Prinz, J.-H. and Noé, F. and Chodera, J. D. and Bolhuis, P.G. (2018) OpenPathSampling: A Python Framework for Path Sampling Simulations. 1. Basics. Journal of Chemical Theory and Computation, Article ASAP . ISSN 1549-9618, ESSN: 15-49-9626 Swenson, D.W.H. and Prinz, J.-H. and Noé, F. and Chodera, J. D. and Bolhuis, P.G. (2018) OpenPathSampling: A Python Framework for Path Sampling Simulations. 2. Building and Customizing Path Ensembles and Sample Schemes. Journal of Chemical Theory and Computation, Article ASAP . ISSN 1549-9618, ESSN: 15-49-9626 Schuster, I. and Constantine, P.G. and Sullivan, T.J. (2017) Exact active subspace Metropolis-Hastings, with applications to the Lorenz-96 system. SFB 1114 Preprint in arXiv:1712.02749 . pp. 1-10. (Unpublished) Scherer, M. K. and Trendelkamp-Schroer, B. and Paul, F. and Pérez-Hernández, G. and Hoffmann, M. and Plattner, N. and Wehmeyer, C. and Prinz, J.-H. and Noé, F. (2015) PyEMMA 2: A Software Package for Estimation, Validation, and Analysis of Markov Models. J. Chem. Theory Comput., 11 (11). pp. 5525-5542. TTaghvaei, A. and de Wiljes, J. and Mehta, P.G. and Reich, S. (2017) Kalman Filter and Its Modern Extensions for the Continuous-Time Nonlinear Filtering Problem. J. Dyn. Sys., Meas., Control, 140 (3). 030904. Trendelkamp-Schroer, B. and Wu, H. and Paul, F. and Noé, F. (2015) Estimation and uncertainty of reversible Markov models. J. Chem. Phys., 143 (17). p. 174101. Vvon Lindheim, Johannes and Harikrishnan, Abhishek P. and Dörffel, Tom and Ernst, Natalia and Klein, R. and Koltai, Péter and Müller, Annette and Pacey, George and Polzin, Robert and Vercauteren, Nikki (2021) Definition, detection and tracking of persistent structures in atmospheric flows. preprint. arXiv . pp. 1-64. (In Press) Vater, S. and Klein, R. (2018) A Semi-Implicit Multiscale Scheme for Shallow Water Flows at Low Froude Number. Communications in Applied Mathematics & Computational Science, 13 (2). pp. 303-336. ISSN 1559-3940 Vitalini, F. and Noé, F. and Keller, B. (2016) Molecular dynamics simulations data of the twenty encoded amino acids in different force fields. Data in Brief, 7 . pp. 582-590. WWu, Ho and Noé, Frank (2019) Variational approach for learning Markov processes from time series data. Journal of Nonlinear Science, 30 . pp. 23-66. ISSN 1432-1467 (online) Wang, J. and Olsson, S. and Wehmeyer, C. and Perez, A. and Charron, N.E. and de Fabritiis, G. and Noé, F. and Clementi, C. (2019) Machine Learning of coarse-grained Molecular Dynamics Force Fields. ACS Cent. Sci., 5 (5). pp. 755-767. ISSN 2374-7943, ESSN: 2374-7951 Wehmeyer, C. and Scherer, M. K. and Hempel, T. and Husic, B.E. and Olsson, S. and Noé, F. (2018) Introduction to Markov state modeling with the PyEMMA software — v1.0. LiveCoMS, 1 (1). pp. 1-12. ISSN E-ISSN: 2575-6524 Weber, M. (2018) Implications of PCCA+ in Molecular Simulation. Computation, 6 (1). ISSN 2079-3197 (online) Weber, M. and Fackeldey, K. and Schütte, Ch. (2017) Set-free Markov state model building. Journal of Chemical Physics, 146 (12). p. 124133. Wu, H. and Paul, F. and Wehmeyer, C. and Noé, F. (2016) Multiensemble Markov models of molecular thermodynamics and kinetics. Proceedings of the National Academy of Sciences, 113 (23). E3221-E3230 . ISSN 0027-8424 Wu, H. and Prinz, J.-H. and Noé, F. (2015) Projected Metastable Markov Processes and Their Estimation with Observable Operator Models. J. Chem. Phys., 143 (14). p. 144101. Wu, H. and Noé, F. (2015) Gaussian Markov transition models of molecular kinetics. J. Chem. Phys., 142 (8). 084104. Wu, H. and Mey, A.S.J.S. and Rosta, E. and Noé, F. (2014) Statistically optimal analysis of state-discretized trajectory data from multiple thermodynamic states. J. Chem. Phys., 141 (21). p. 214106. ZZendehroud, Sina and Loche, Philip and Kornhuber, Ralf and Netz, Roland R. (2022) Boundary Conditions on Conical Hydrophobic Inclusions in Lipid Membranes. Preprint . (Unpublished) Zhang, W. and Hartmann, C. and Schütte, Ch. (2016) Effective dynamics along given reaction coordinates, and reaction rate theory. Faraday discussions, 195 . pp. 365-394. ISSN 1359-6640 |