Publications
Moldenhawer, T., Moreno, E., Schindler, D., Flemming, S., Holschneider, M., Huisinga, W., Alonso, S. and Beta, C. (2022). Spontaneous transitions between amoeboid and keratocyte-like modes of migration. Front. Cell Dev. Biol., 10:898351. doi:10.3389/fcell.2022.898351
Schindler, D., Moldenhawer, T., Beta, C., Huisinga, W. and Holschneider, M. (2022). Three-component contour dynamics model to simulate and analyze amoeboid cell motility. arXiv:2210.12978
Yochelis, A., Flemming, S. and Beta, C. (2022). Versatile Patterns in the Actin Cortex of Motile Cells: Self-Organized Pulses Can Coexist with Macropinocytic Ring-Shaped Waves. Phys. Rev. Lett., 129:088101. doi: 10.1103/PhysRevLett.129.088101
Schwetlick, L.; Backhaus, D. & Engbert, R. (2022). A dynamical scan-path model for task-dependence during scene viewing. Psychological Review, American Psychological Association (APA). doi: 10.1037/rev0000379
Vilk, O., Aghion, E., Avgar, T., Beta, C., Nagel, O., Sabri, A., Sarfati, R., Schwartz, D., Weiss, M., Krapf, D., Nathan, R., Metzler, R. and Assaf, M. (2022) Unravelling the origins of anomalous diffusion: From molecules to migrating storks. Phys. Rev. Research, 4:033055. doi: 10.1103/PhysRevResearch.4.033055
Riedel, C., Geßner, H., Seegebrecht, A., Ayon, S. I., Chowdhury, S. H., Engbert, R. and Lucke, U. (2022). Including Data Management in Research Culture Increases the Reproducibility of Scientific Results. In: Demmler, D., Krupka, D. & Federrath, H. (Hrsg.), INFORMATIK 2022. Gesellschaft für Informatik, Bonn. (S. 1341-1352). doi: 10.18420/inf2022_114
Moreno, E., Grossmann, R., Beta, C., and Alonso, S. (2022). From Single to Collective Motion of Social Amoebae: A Computational Study of Interacting Cells. Front. Phys., 9:750187. doi: 10.3389/fphy.2021.750187
Maoutsa, D. and Opper, M. (2022). Deterministic particle flows for constraining stochastic nonlinear systems, Phys. Rev. Res., 4, 043035, doi:10.1103/PhysRevResearch.4.043035
Lie, H. C. and Stahn, M. and Sullivan, T.J. (2022). Randomised one-step time integration methods for deterministic operator differential equations. Calcolo, Volume 59, Number 13, ArXiv 2103.16506, doi: 10.1007/s10092-022-00457-6.
Gaucher, S., Carpentier, A., & Giraud, C. (2022). The price of unfairness in linear bandits with biased feedback. Advances in Neural Information Processing Systems, 35, 18363-18376.
Reich, S. (2022): Data assimilation: A dynamic homotopy-based coupling approach. arXiv 2209.05279
Winkler, L., Ojeda, C., and Opper, M. (2022). A Score-Based Approach for Training Schrödinger Bridges for Data Modelling, Entropy, 25, 316, doi:10.3390/e25020316
Huang, D.Z., Huang, J., Reich, S., and Stuart, A.M. (2023). Efficient derivative-free Bayesian inference for large-scale inverse problems. Inverse Probelms, Vol. 38, 125006. doi: 10.1088/1361-6420/ac99fa, arXiv:2204.04386
Pidstrigach, J. (2022). Score-based generative models detect manifolds. In: Advances in Neural Information Processing Systems, Volume 35. arXiv:2206.01018
Pidstrigach, J. (2022). Convergence of preconditioned Hamiltonian Monte Carlo on Hilbert spaces, IMA Journal of Numerical Analysis. doi: 10.1093/imanum/drac052, arXiv:2011.08578
Reich, S. (2022). Frequentist perspective on robust parameter estimation using the ensemble Kalman filter In: Chapron, B., Crisan, D., Holm, D., Mémin, E., Radomska, A. (eds) Stochastic Transport in Upper Ocean Dynamics. STUOD 2021. Mathematics of Planet Earth, vol 10. Springer, Cham. doi: 10.1007/978-3-031-18988-3_15 arXiv:2201.000611
Calvello, E., Reich, S. and Stuart A.M.(2022): Ensemble Kalman methods: A mean field approach. arXiv 2209.11371
Pfeifer, V., Beier, S., Alirezaeizanjani, Z., and Beta, C. (2022): Role of the two flagellar stators in swimming motility of Pseudomonas putida. Mbio 13(6) e02182-22, doi: 10.1128/mbio.02182-22.
Alqahtani, A., Mach, T., and Reichel, L. (2023). Solution of Ill-posed Problems with Chebfun. Numerical Algorithms (2023). doi:10.1007/s11075-022-01390-z, arXiv 2007.16137
Zöller, G. (2022): A note on the estimation of the maximum possible earthquake magnitude based on extreme value theory for the Groningen gas field. Bulletin of the Seismological Society of America, Vol. 112(4), 1825-1831. doi:10.1785/0120210307
Boether, M., Kißig, O., Taraz, M., Cohen, S., Seidel, K., and Friedrich, T. (2022). Whats Wrong with Deep Learning in Tree Search for Combinatorial Optimization. In: International Conference on Learning Representations. arXiv:2201.10494
Altmeyer, R., Bretschneider, T., Janák, J. and Reiß, M. (2022): Parameter Estimation in an SPDE Model for Cell Repolarisation. SIAM/ASA Journal on Uncertainty Quantification 10(1), 179-199. doi:10.1137/20M1373347
Pidstrigach, J. and Reich, S. (2022). Affine-invariant ensemble transform methods for logistic regression. Foundation of Computational Mathematics, 22. doi:10.10007/s10208-022-09550-2.
Molkenthin, C., Donner, C., Reich, S., Zöller, G., Hainzl, S., Holschneider, M. and Opper, M. (2022): GP-ETAS: Semiparametric Bayesian inference for the spatio-temporal Epidemic Type Aftershock Sequence model. Statistics and Computation, Vol. 32, 29. doi:10.1007/s11222-022-10085-3.
Huang, D.Z., Huang, J., Reich, S., and Stuart, A.M. (2022). Efficient derivative-free Bayesian inference for large-scale inverse problems. arXiv:2204.04386.
Engbert, R., Rabe, M. M., Schwetlick, L., Seelig, S. A., Reich, S., Vasishth, S. (2022). Data assimilation in dynamical cognitive science. Trends in Cognitive Sciences, 26(2), 99-102. doi:10.1016/j.tics.2021.11.006.
Malem-Shinitski, N., Ojeda, C., and Opper, M. (2022). Variational Bayesian Inference for Nonlinear Hawkes Process with Gaussian Process Self-Effects. Entropy, 24(3), 356. doi: 10.3390/e24030356.
Mach, T., Reichel, L., and Van Barel, M. (2023). Adaptive cross approximation for Tikhonov regularization in general form. Numerical Algorithms. doi:10.1007/s11075-022-01395-8, arXiv 2204.05740
Gaudlitz, S. and Reiß, M. (2022): Estimation for the reaction term in semi-linear SPDEs under small diffusivity. arXiv:2203.10527
Pathiraja, S., and van Leeuwen, P. J. (2022): Multiplicative non-Gaussian model error estimation in data assimilation. Journal of Advances in Modeling Earth Systems, 14, e2021MS002564. doi: 10.1029/2021MS002564
Ruchi, S., Dubinkina, S. and de Wiljes, J. (2021): Fast hybrid tempered ensemble transform filter for Bayesian elliptical problems via Sinkhorn approximation. Nonlinear Processes in Geophysics, 28(1): 23-41. doi: 10.5194/npg-28-23-2021