1. Data assimilation - the collaborative research centre SFB1294
  2. Open Science
  3. Publications

Publications

  • Jirak, M. and Wahl, M. (2018): Perturbation bounds for eigenspaces under a relative gap condition.arXiv: 1803.03868

  • Donner, C. and Opper, M. (2018). Efficient Bayesian Inference of Sigmoidal Gaussian Cox Processes, Journal of Machine Learning Research 19, no 67, 1-34. Open Access

  • Morzfeld, M. and Reich, S. (2018): Data assimilation: mathematics for merging models and data. Snapshots of modern mathematics from Oberwolfach, 11. doi: 10.14760/SNAP-2018-011-EN

  • Makowski, S., Jäger, L., Abdelwahab, A., Landwehr, N. and Scheffer, T. (2018). A discriminative model for identifying readers and assessing text comprehension from eye movements. In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD). doi: 10.1007/978-3-030-10925-7_13, arxiv preprint: https://arxiv.org/pdf/1809.08031.pdf

  • Blanchard, G., Hoffmann, M. and Reiß, M. (2018). Early stopping for statistical inverse problems via truncated SVD estimation. Electron. J. Statist. 12 (2): 3204-3231. arXiv 1710.07278; doi: 10.1214/18-EJS1482

  • Blanchard, G. and Mücke, N. (2018). Parallelizing Spectral Algorithms for Kernel Learning. Journal of Machine Learning Research (30):1-29, 2018. Open Access

  • Alonso, S., Stange, M. and Beta, C. (2018). Modeling random crawling, membrane deformation and intracellular polarity of motile amoeboid cells. PLoS ONE, 13(8): e0201977. doi: 10.1371/journal.pone.0201977

  • Fiedler, B., Hainzl, S., Zöller, G. and Holschneider, M. (2018). Detection of Gutenberg–Richter b-value changes in earthquake time series, Bulletin of the Seismological Society of America, 108(5A), 2778–2787. doi: 10.1785/0120180091

  • Salamat, M., Zöller, G. Zare, M. and Amini, M. (2018). The maximum expected earthquake magnitudes in different future time intervals of six seismotectonic zones of Iran and its surroundings, Journal of Seismology, 22, 1485–1498. doi: 10.1007/s10950-018-9780-7

  • Cherstvy, A. G., Nagel, O., Beta, C. and Metzler, R. (2018). Non-Gaussianity, population heterogeneity, and transient superdiffusion in the spreading dynamics of amoeboid cells. doi: 10.1039/c8cp04254c

  • Locatelli, A., and Carpentier, A. (2018). Adaptivity to Smoothness in X-armed bandits. Proceedings of Machine Learning Research, PMLR, 75, 1463-1492. Open Access

  • Pathiraja, S. and van Leeuwen, P.J. (2018). Model uncertainty estimation in data assimilation for multi-scale systems with partially observed resolved variables, Quarterly Journal of the Royal Meteorological Society, under review, arXiv: 1807.09621

  • Blanchard, G., Hoffmann, M. and Reiß, M. (2018). Optimal adaptation for early stopping in statistical inverse problems. SIAM/ASA Journal on Uncertainty Quantification 6(3): 1043-1075. arXiv 1606.07702; doi:10.1137/17M1154096

  • Zöller, G. (2018): A Statistical Model for Earthquake Recurrence Based on the Assimilation of Paleoseismicity, Historic Seismicity, and Instrumental Seismicity. Journal of Geophysical Research: Solid Earth, 123, 4906-4921. doi: 10.1029/2017JB015099

  • Donner, C. and Opper, M. (2018). Efficient Bayesian Inference for a Gaussian Process Density Model, Proc. in Conference on Uncertainty in Artificial Intelligence, 2018. Open Access

  • Pathiraja, S., Anghileri, D., Burlando, P., Sharma, A., Marshall, L. and Moradkhani, H. (2018). Time varying parameter models for catchments with land use change: The importance of model structure, Hydrology and Earth System Sciences, 22(5), 2903-2919. doi: 10.5194/hess-22-2903-2018

  • Jirak, M. and Wahl, M. (2018): Relative perturbation bounds with applications to empirical covariance operators.arXiv: 1802.02869

  • Fiedler, B., Zöller, G., Holschneider, M. and Hainzl, S. (2018). Multiple Change‐Point Detection in Spatiotemporal Seismicity Data, Bulletin of the Seismological Society of America. 108 (3A): 1147-1159. doi: 10.1785/0120170236

  • Bachoc, F., Blanchard, G. and Neuvial, P. (2018): On the post selection inference constant under restricted isometry properties. Electron. J. Statist. 12(2): 3736-3757. doi: 10.1214/18-EJS1490

  • de Wiljes, J., Reich, S. and Stannat, W. (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. arXiv: 1612.06065; doi: 10.1137/17M1119056

  • Moradkhani, H., Nearing, G., Abbaszadeh, P. and Pathiraja, S. (2018).  Fundamentals of Data Assimilation and Theoretical Advances. In: Duan, Q., Pappenberger, F., Thielen, J., Wood, A., Cloke, H.L. and Schaake, J. C. (eds), Handbook of Hydrometeorological Ensemble Forecasting. Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 1 -26. doi: 10.1007/978-3-642-40457-3_30-1 

  • Silin, I. and Spokoiny, V. (2018): Bayesian inference for spectral projectors of the covariance matrix, Electron. J. Statist. 12(1), 1948-1987. doi:10.1214/18-EJS1451; arXiv:1711.11532

  • Pathiraja, S., Anghileri, D., Burlando, P., Sharma, A., Marshall, L. and Moradkhani, H. (2018): Insights on the impact of systematic model errors on data assimilation performance in changing catchments, Advances in Water Resources, 113 (December 2017), 202-222. doi: 10.1016/j.advwatres.2017.12.006

  • Blanchard, G., Carpentier, A. and Gutzeit, M. (2018): Minimax Euclidean Separation Rates for Testing Convex Hypotheses in Rd. Electron. J. Statist. 12 (2): 3713-3735. doi:10.1214/18-EJS1472

  • Pathiraja, S., Moradkhani, H., Marshall, L., Sharma, A. and Geenens, G. (2018): Data-Driven Model Uncertainty Estimation in Hydrologic Data Assimilation, Water Resources Research, 54(2), 1252-1280. doi: 10.1002/2018WR022627

  • Ni, B., Cao, X., Shprits, Y. Y., Summers, D., Gu, X., Fu, S. and Lou, Y. (2018). Hot Plasma Effects on the Cyclotron-Resonant Pitch-Angle Scattering Rates of Radiation Belt Electrons Due to EMIC Waves. Geophysical Research Letters, 45, 21-30. doi: 10.1002/2017GL07602

  • Locatelli, A., Carpentier, A., and Kpotufe, S. (2018): An Adaptive Strategy for Active Learning with Smooth Decision Boundary. Proceedings of Machine Learning Research (ALT), 83, 547-571. Open Access