Published peer-reviewed Journal Articles
S. K. J. Falkena, J. de Wiljes, A. Weisheimer, T. G. Shepherd (2023). A Bayesian Approach to Atmospheric Circulation Regime Assignment, accepted at Journal of Climate , accepted at Journal of Climate
M. Hamm, M. Grott, H. Senshu, J. Knollenberg, J. de Wiljes, V. E. Hamilton, F. Scholten, K. D. Matz, H. Bates, A. Maturilli, Y. Shimaki, N. Sakatani, W. Neumann, T. Okada, F. Preusker, S. Elgner, J. Helbert, E. Kührt, T.-M. Ho, S. Tanaka, R. Jaumann, S. Sugita (2022). Mid-Infrared Emissivity of Partially Dehydrated Asteroid (162173) Ryugu Shows Strong Signs of Aqueous Alteration Nature Communications, 13 (1), 364
C. Maier, J. de Wiljes, N. Hartung, C. Kloft, W. Huisinga (2022). A continued learning approach for model-informed precision dosing: updating models in clinical practice CPT: Pharmacometrics & Systems Pharmacology, 11 (2), 185-198
S. K. J. Falkena, J. de Wiljes, A. Weisheimer, T. G. Shepherd (2022). Towards a Robust Detection of Interannual Ensemble Forecast Signals over the North Atlantic and Europe using Atmospheric Circulation Regimes Quarterly Journal of Royal Meteorological Society, 148 (742), 434-453
Y. Ba, J. de Wiljes, D. Oliver and S. Reich (2021). Randomised maximum likelihood based posterior sampling. Computational Geosciences https://doi.org/10.1007/s10596- 021-10100-y
A. M. Castillo Tibocha, J. de Wiljes, Y. Shprits, N. A. Aseev (2021). Reconstructing the dynamics of the outer electron radiation belt by means of ensemble Kalman filtering with the VERB-3D Code. Space Weather 19 (10): e2020SW002672.
C. Maier, N. Hartung, C. Kloft, W. Huisinga, J. de Wiljes (2021). Combining reinforcement learning with data assimilation for individualised dosing policies in oncology. CPT: Pharmacometrics & Systems Pharmacology. 10(3): 241-254
S. Ruchi, S. Dubinkina, J. de Wiljes (2021). Fast hybrid tempered ensemble transform filter for Bayesian elliptical problems. Nonlinear Processes in Geophysics. 28(1): 23-41
E. Saggioro, J. de Wiljes, M. Kretschmer, J. Runge (2020). Reconstructing regime- dependent causal relationships from observational time series. Chaos 30, 113115
S. K. J. Falkena, J. de Wiljes, A. Weisheimer, T. G. Shepherd (2020). Revisiting the Identification of Wintertime Atmospheric Circulation Regimes in the Euro-Atlantic Sector. Quarterly Journal of Royal Meteorological Society 146(731): 2801-2814
J. de Wiljes, X. T. Tong (2020). Analysis of a localised nonlinear Ensemble Kalman Bucy Filter with complete and accurate observations. Nonlinearity 33(9): 4752–4782.
J. de Wiljes, S. Pathiraja, S. Reich (2020). Ensemble transform algorithms for nonlinear smoothing problems. SIAM Journal on Scientific Computing 42(1): A87–A114.
C. Maier, N. Hartung, J. de Wiljes, C. Kloft, W. Huisinga (2020). Bayesian data assimilation to support informed decision-making in individualised chemotherapy. CPT: Pharmacometrics & Systems Pharmacology 9(3), 153–164.
M. Hamm, I. Pelivan, M. Grott, J. de Wiljes (2020). Thermophysical modeling and parameter estimation of small solarsystem bodies via data assimilation. Monthly Notices of the Royal Astronomical Society 496(3): 2776-2785.
J. de Wiljes, W. Stannat, S. Reich (2018). Long-time stability and accuracy of the ensemble Kalman-Bucy filter for fully observed processes and small measurement noise. SIAM Journal on Applied Dynamical Systems 17(2): 1152–1181.
A. Taghvaei, J. de Wiljes, P. G. Mehta, S. Reich (2018). Kalman Filter and its Modern Extensions for the Continuous-time Nonlinear Filtering Problem. Journal of Dynamic Systems, Measurements, and Control 140(3): 030904.
W. Acevedo, J. de Wiljes, S. Reich (2017). A second-order accurate ensemble transform particle filter. SIAM Journal on Scientific Computing 39(5): A1834–A1850.
J. de Wiljes, L. Putzig, I. Horenko (2014). Discrete nonhomogeneous and nonstationary logistic and Markov regression models for spatiotemporal data with unresolved external influences. Communications in Applied Mathematics & Computational Science 9(1): 1–46.
J. de Wiljes, A. J. Majda, I. Horenko (2013). An adaptive Markov Chain Monte Carlo approach to time series clustering of processes with regime transitions behavior. SIAM Multiscale Modeling & Simulation 11(2): 415–441.
Published Software
Hamm, M. Grott, H. Senshu, J. Knollenberg, J. de Wiljes, V. E. Hamilton, F. Scholten, K. D. Matz, H. Bates, A. Maturilli, Y. Shimaki, N. Sakatani, W. Neumann, T. Okada, F. Preusker, S. Elgner, J. Helbert, E. Kührt, T.-M. Ho, S. Tanaka, R. Jaumann, S. Sugita (2021). Data Assimilation of MASCOT Radiometer Data, Zenodo, https://doi.org/10.5281/zenodo.567959s
C. Maier, J. de Wiljes, N. Hartung, C. Kloft, W. Huisinga (2021). A continued learning approach for model-informed precision dosing: updating models in clinical practice, Zenodo,
Technical Reports
A. David, J. de Wiljes, S. Reich (2017). Interacting particle filters for simultaneous state and parameter estimation. Technical report, University of Potsdam.
Theses
J. de Wiljes (2015). Data-Driven Discrete Spatio-Temporal Models: Problems, Methods and an Arctic Sea Ice Application. Dissertation. http: // www. diss. fu-berlin. de/ diss/ receive/ FUDISS_ thesis_ 000000098296 .
J. de Wiljes (2010). Adopting a Bayesian framework to multidimensional cluster modeling. Diploma thesis.