Claudia Schillings
Claudia Schillings
Institute of Mathematics, FU Berlin
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Analysis of the ensemble Kalman filter for inverse problems
C Schillings, AM Stuart
SIAM Journal on Numerical Analysis 55 (3), 1264-1290, 2017
Sparse, adaptive Smolyak quadratures for Bayesian inverse problems
C Schillings, C Schwab
Inverse Problems 29 (6), 065011, 2013
Efficient shape optimization for certain and uncertain aerodynamic design
C Schillings, S Schmidt, V Schulz
Computers & Fluids 46 (1), 78-87, 2011
Convergence analysis of ensemble Kalman inversion: the linear, noisy case
C Schillings, AM Stuart
Applicable Analysis 97 (1), 107-123, 2018
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, 915-971, 2020
Large deformation shape uncertainty quantification in acoustic scattering
R Hiptmair, L Scarabosio, C Schillings, C Schwab
Advances in Computational Mathematics 44, 1475-1518, 2018
On the treatment of distributed uncertainties in PDE‐constrained optimization
A Borzì, V Schulz, C Schillings, G von Winckel
GAMM‐Mitteilungen 33 (2), 230-246, 2010
Sparsity in Bayesian inversion of parametric operator equations
C Schillings, C Schwab
Inverse Problems 30 (6), 065007, 2014
Well posedness and convergence analysis of the ensemble Kalman inversion
D Blömker, C Schillings, P Wacker, S Weissmann
Inverse Problems 35 (8), 085007, 2019
A strongly convergent numerical scheme from ensemble Kalman inversion
D Blomker, C Schillings, P Wacker
SIAM Journal on Numerical Analysis 56 (4), 2537-2562, 2018
Scaling limits in computational Bayesian inversion
C Schillings, C Schwab
ESAIM: Mathematical Modelling and Numerical Analysis 50 (6), 1825-1856, 2016
Problem formulations and treatment of uncertainties in aerodynamic design
V Schulz, C Schillings
AIAA journal 47 (3), 646-654, 2009
Quantification of airfoil geometry-induced aerodynamic uncertainties---comparison of approaches
D Liu, A Litvinenko, C Schillings, V Schulz
SIAM/ASA Journal on Uncertainty Quantification 5 (1), 334-352, 2017
On the influence of robustness measures on shape optimization with stochastic uncertainties
C Schillings, V Schulz
Optimization and Engineering 16, 347-386, 2015
A quasi-Monte Carlo method for optimal control under uncertainty
PA Guth, V Kaarnioja, FY Kuo, C Schillings, IH Sloan
SIAM/ASA Journal on Uncertainty Quantification 9 (2), 354-383, 2021
Efficient characterization of parametric uncertainty of complex (bio) chemical networks
C Schillings, M Sunnåker, J Stelling, C Schwab
PLOS Computational Biology 11 (8), e1004457, 2015
On the incorporation of box-constraints for ensemble Kalman inversion
NK Chada, C Schillings, S Weissmann
arXiv preprint arXiv:1908.00696, 2019
Optimal aerodynamic design under uncertainty
V Schulz, C Schillings
Management and Minimisation of Uncertainties and Errors in Numerical …, 2013
Optimal aerodynamic design under uncertainties
C Schillings
14 Ensemble Kalman filter for neural network-based one-shot inversion
PA Guth, C Schillings, S Weissmann
Optimization and Control for Partial Differential Equations: Uncertainty …, 2022
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