• 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 problemsarXiv:2204.04386.

  • Yadav, H., Smith, G., Reich, S., and Vasishth, S. (2022). Number feature distortion modulates cue-based retrieval in reading. doi:10.31234/osf.io/s4c9t.

  • 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.

  • Gaudlitz, S. and Reiß, M. (2022). Estimation for the reaction term in semi-linear SPDEs under small diffusivity. arXiv:2203.10527

  • Pathiraja, S., & van Leeuwen, P. J. (2022). Multiplicative non-Gaussian model error estimation in data assimilation. Journal of Advances in Modeling Earth Systems, 14, e2021MS002564. https://doi.org/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 [1]

  • Reich, S. (2022). Frequentist perspective on robust parameter estimation using the ensemble Kalman filter arXiv:2201.000611