Claudia Schillings

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Christoph SchwabProfessor for Mathematics, ETH ZurichVerified email at math.ethz.ch
Volker SchulzUniversity of TrierVerified email at uni-trier.de
Simon WeissmannUniversität MannheimVerified email at uni-mannheim.de
Philipp WackerUniversity of CanterburyVerified email at canterbury.ac.nz
Andrew M StuartComputing + Mathematical Sciences, CaltechVerified email at caltech.edu
Dirk BlömkerUniversität AugsburgVerified email at math.uni-augsburg.de
Frances Y. KuoUNSW AustraliaVerified email at unsw.edu.au
Ian SloanProfessor of Mathematics, University of New South Wales (UNSW Australia)Verified email at unsw.edu.au
Neil ChadaCity University of Hong KongVerified email at cityu.edu.hk
Björn SprungkTU Bergakademie FreibergVerified email at math.tu-freiberg.de
Ralf HiptmairETH Zurich, Seminar for Applied MathematicsVerified email at hiptmair.de
Laura ScarabosioRadboud UniversityVerified email at math.ru.nl
Alfio BorziInst. for Mathematics, Universität Würzburg, GermanyVerified email at mathematik.uni-wuerzburg.de
Gregory von WinckelSandia National LaboratoriesVerified email at sandia.gov
Xin T. TongNational University of SingaporeVerified email at nus.edu.sg
Alexander LitvinenkoChair of Mathematics for Uncertainty Quantification, RWTH AachenVerified email at uq.rwth-aachen.de
Joerg StellingDepartment of Biosystems Science and Engineering, ETH ZurichVerified email at inf.ethz.ch
Martin SchlatherUniversität MannheimVerified email at uni-mannheim.de
Marco OestingUniversity of StuttgartVerified email at mathematik.uni-stuttgart.de
Michael HintermüllerWeierstrass Institute for Applied Analysis and Stochastics, and Humboldt-Universität zu BerlinVerified email at math.hu-berlin.de

Claudia Schillings

Institute of Mathematics, FU Berlin

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applied and computational mathematics inverse problems optimization under uncertainty uncertainty


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Analysis of the ensemble Kalman filter for inverse problems C Schillings, AM Stuart SIAM Journal on Numerical Analysis 55 (3), 1264-1290, 2017	236	2017
Sparse, adaptive Smolyak quadratures for Bayesian inverse problems C Schillings, C Schwab Inverse Problems 29 (6), 065011, 2013	152	2013
Efficient shape optimization for certain and uncertain aerodynamic design C Schillings, S Schmidt, V Schulz Computers & Fluids 46 (1), 78-87, 2011	105	2011
Convergence analysis of ensemble Kalman inversion: the linear, noisy case C Schillings, AM Stuart Applicable Analysis 97 (1), 107-123, 2018	90	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	80	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	74	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	63	2010
Well posedness and convergence analysis of the ensemble Kalman inversion D Blömker, C Schillings, P Wacker, S Weissmann Inverse Problems 35 (8), 085007, 2019	61	2019
Sparsity in Bayesian inversion of parametric operator equations C Schillings, C Schwab Inverse Problems 30 (6), 065007, 2014	59	2014
Scaling limits in computational Bayesian inversion C Schillings, C Schwab ESAIM: Mathematical Modelling and Numerical Analysis 50 (6), 1825-1856, 2016	50	2016
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	47	2017
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	46	2018
Problem formulations and treatment of uncertainties in aerodynamic design V Schulz, C Schillings AIAA journal 47 (3), 646-654, 2009	46	2009
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	40	2021
On the influence of robustness measures on shape optimization with stochastic uncertainties C Schillings, V Schulz Optimization and Engineering 16, 347-386, 2015	38	2015
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	32	2015
On the incorporation of box-constraints for ensemble Kalman inversion NK Chada, C Schillings, S Weissmann arXiv preprint arXiv:1908.00696, 2019	28	2019
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	19	2022
Optimal aerodynamic design under uncertainty V Schulz, C Schillings Management and Minimisation of Uncertainties and Errors in Numerical …, 2013	18	2013
Optimal aerodynamic design under uncertainties C Schillings	18	2011

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