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

Publications

  • König, J., Pfeffer, M. and Stoll, M. (2023). Efficient training of Gaussian processes with tensor product structure. arXiv 2312.15305.

  • Engbert, R. and Rabe, M. M. (2023). Tutorial on dynamical modeling of eye movements in reading. PsyArXiv

  • Boys, B., Girolami, M., Pidstrigach, J., Reich, S., Mosca, A., and Akyildiz, O.D. (2023). Tweedie Moment Projected Diffusions For Inverse Problems arXiv 2310.06721

  • Reich, S. (2023): A particle-based Algorithm for Stochastic Optimal Control. arXiv 2311.06906

  • Chen, Y, Huang D.Z., Huang J., Reich, S., and Stuart, A.M. (2023). Sampling via gradient flows in the space of probability measures arXiv:2310.03597

  • Pidstrigach, J., Marzouk, Y., Reich, S., and Wang, S. (2023). Infinite-Dimensional Diffusion Models arXiv 2302.10130

  • Liu, S., Reich, S., and Tong, X.T. (2023). Dropout ensemble Kalman inversion for high dimensional inverse problems arXiv:2308.16784

  • Pasemann, G. and Beta, C. and Stannat, W. (2023). Stochastic Reaction-Diffusion Systems in Biophysics: Towards a Toolbox for Quantitative Model Evaluation. arXiv:2307.06655

  • Gaudlitz, S. (2023). Non-parametric estimation of the reaction term in semi-linear SPDEs with spatial ergodicity.arXiv:2307.05457

  • G. Blanchard, A. Carpentier, and O. Zadorozhnyi (2023): Moment inequalities for sums of weakly dependent random fields. In: arXiv preprint arXiv:2306.16403

  • Kim, J. W. and Mehta, P. G. (2023): Variance Decay Property for Filter Stability. arXiv 2305.12850

  • Chen, Y, Huang D.Z., Huang J., Reich, S., and Stuart, A.M. (2023). Gradient flows for sampling: Mean-field models, Gaussian approximations and affine invariance arXiv:2302.11024

  • Cvetkovic, N. and Lie, H. C. and Bansal, H. and Veroy-Grepl, K. (2023). Choosing observation operators to mitigate model error in Bayesian inverse problems. ArXiv 2301.04863

  • Kim, J.W. and Reich, S. (2023): On forward-backward SDE approaches to continuousßtime minimum variance estimation. arXiv 2304.12727

  • Pidstrigach, J., Marzouk, Y., Reich, S., and Wang., S. (2023). Infinite-dimensional diffusion models for function spaces arXiv:2302.10130

  • Irwin, B. and Reich, S. (2023). EnKSGD: A class of preconditioned black box optimization and inversion algorithms. arXiv:2303.16494.

  • Mach, T and Freitag, M.A. (2023). Solving the Parametric Eigenvalue Problem by Taylor Series and Chebyshev Expansion arXiv 230212.03661

  • Schwetlick, L. and Reich S. and Engbert R. (2023). Bayesian Dynamical Modeling of Fixational Eye Movements. arXiv:2303.11941.

  • Rabe, M. M., Paape, D., Mertzen, D., Vasishth, S., & Engbert, R. (2023). SEAM: An integrated activation-coupled model of sentence processing and eye movements in reading. arXiv:2303.05221

  • Janák, J. and Reiß, M. (2023). Parameter estimation for the stochastic heat equation with multiplicative noise from local measurements. arXiv:2303.00074v1

  • Kemeth, F., Alonso, S., Echebarria, B., Moldenhawer, T., Beta, C. and Kevrekidis I. (2022). Black and Gray Box Learning of Amplitude Equations: Application to Phase Field Systems. arXiv: 2207.03954