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. doi: 10.31234/osf.io/dsvmt

Lopopolo, A. and Rabovsky, M. (2023). Tracking lexical and semantic prediction error underlying the N400 using artificial neural network models of sentence processing. doi: 10.1101/2022.11.14.516396

Bhandari, D., Pidstrigach, J., and Reich, S. (2023). Affine Invariant Ensemble Transform Methods to Improve Predictive Uncertainty in ReLU Networks. arXiv:2309.04742 

Spokoiny, V. (2023). Deviation bounds for the norm of a random vector under exponential moment conditions with applications, arXiv:2309.02302

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

Spokoiny, V. (2023). Sharp deviation bounds and concentration phenomenon for the squared norm of a sub-Gaussian vector, arXiv:2305.07885v1

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

Spokoiny, V. (2023). Nonlinear regression: finite sample guarantees, arXiv:2305.08193

Spokoiny, V. (2023). Mixed Laplace approximation for marginal posterior and Bayesian inference in error-in-operator model, arXiv:2305.09336

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

Reiß, M., Strauch, C., and Trottner, L. (2023): Change point estimation for a stochastic heat equation. arXiv:2307.10960

Pasemann, G., 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

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., Lie, H. C., 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., and 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