| On the convergence of the Laplace approximation and noise-level-robustness of Laplace-based Monte Carlo methods for Bayesian inverse problems C Schillings, B Sprungk, P Wacker Numerische Mathematik 145 (4), 915-971, 2020 | 50 | 2020 |
| A strongly convergent numerical scheme from ensemble Kalman inversion D Blömker, C Schillings, P Wacker SIAM Journal on Numerical Analysis 56 (4), 2537-2562, 2018 | 40 | 2018 |
| Well posedness and convergence analysis of the ensemble Kalman inversion D Blömker, C Schillings, P Wacker, S Weissmann Inverse Problems 35 (8), 085007, 2019 | 38 | 2019 |
| Pattern size in Gaussian fields from spinodal decomposition LA Bianchi, D Blömker, P Wacker SIAM Journal on Applied Mathematics 77 (4), 1292-1319, 2017 | 6 | 2017 |
| Continuous time limit of the stochastic ensemble Kalman inversion: Strong convergence analysis D Blömker, C Schillings, P Wacker, S Weissmann arXiv preprint arXiv:2107.14508, 2021 | 5 | 2021 |
| Nested sampling for physical scientists G Ashton, N Bernstein, J Buchner, X Chen, G Csányi, A Fowlie, F Feroz, ... Nature Reviews Methods Primers 2 (1), 1-22, 2022 | 3 | 2022 |
| The lion in the attic--A resolution of the Borel--Kolmogorov paradox L Bungert, P Wacker arXiv preprint arXiv:2009.04778, 2020 | 2 | 2020 |
| MAP estimators for nonparametric Bayesian inverse problems in Banach spaces P Wacker arXiv preprint arXiv:2007.12760, 2020 | 2 | 2020 |
| Nested sampling and likelihood plateaus D Schittenhelm, P Wacker arXiv preprint arXiv:2005.08602, 2020 | 2 | 2020 |
| Probabilistic estimates of the maximum norm of random Neumann Fourier series D Blömker, P Wacker, T Wanner Communications in Nonlinear Science and Numerical Simulation 47, 348-369, 2017 | 2 | 2017 |
| Laplace’s method in Bayesian inverse problems with Gaussian priors P Wacker arXiv preprint arXiv:1701.07989, 2017 | 2 | 2017 |
| Complete Deterministic Dynamics and Spectral Decomposition of the Ensemble Kalman Inversion L Bungert, P Wacker arXiv preprint arXiv:2104.13281, 2021 | 1 | 2021 |
| Laplace's method in Bayesian inverse problems P Wacker arXiv preprint arXiv:1701.07989, 2017 | 1 | 2017 |
| Bayesian model selection for linear regression M de Benito Delgado, P Wacker arXiv e-prints, arXiv: 1512.04823, 2015 | 1* | 2015 |
| Maximum a posteriori estimators in are well-defined for diagonal Gaussian priors I Klebanov, P Wacker arXiv preprint arXiv:2207.00640, 2022 | | 2022 |
| Deterministic Dynamics of Ensemble Kalman Inversion L Bungert, P Wacker | | 2021 |
| Complete Dynamics and Spectral Decomposition of the Ensemble Kalman Inversion L Bungert, P Wacker | | 2021 |
| Wavelet-based priors accelerate maximum-a-posteriori optimization in Bayesian inverse problems P Wacker, P Knabner Methodology and Computing in Applied Probability 22 (3), 853-879, 2020 | | 2020 |
| Pointwise defined version of conditional expectation with respect to a random variable P Wacker arXiv preprint arXiv:2007.01635, 2020 | | 2020 |
| Pattern size in Gaussian fields from spinodal decomposition L Amedeo Bianchi, D Blömker, P Wacker arXiv e-prints, arXiv: 1510.01967, 2015 | | 2015 |
Dirk BlömkerUniversität AugsburgPotvrđena adresa e-pošte na math.uni-augsburg.de
