Browse by Projects
Number of items: 39. 2022Chew, R. 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 (9). pp. 2231-2254. 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) 2021Hittmeir, 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. Coghi, Michele and Nilssen, Torstein and Nüsken, Nikolas (2021) Rough McKean-Vlasov dynamics for robust ensemble Kalman filtering. arXive . pp. 1-41. (Submitted) Leung, 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) 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. 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) 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 (Unpublished) Richter, Lorenz and Sallandt, Leon and Nüsken, Nikolas (2021) Solving high-dimensional parabolic PDEs using the tensor train format.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. 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) Schmidt, F. and Gagarina, E. and Klein, R. and Achatz, U. (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) 2020Richter, 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) 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 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. 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. 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. 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) 2019Duncan, A. and Nüsken, N. and Szpruch, L. (2019) On the geometry of Stein variational gradient descent. SFB 1114 Preprint in arXiv:1912.00894 . (Unpublished) 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) 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 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) 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. 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) 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 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 2018Vater, 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 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) 2017Taghvaei, 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. Acevedo, 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) 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 O'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. 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 2016Chustagulprom, 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 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 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 2015Horenko, I. and Gerber, S. (2015) Improving clustering by imposing network information. Science Advances, 1 (7). ISSN 2375-2548 |