Claudia Schillings

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Christoph SchwabProfessor for Mathematics, ETH ZurichEmail yang diverifikasi di math.ethz.ch
Volker SchulzUniversity of TrierEmail yang diverifikasi di uni-trier.de
Simon WeissmannUniversität MannheimEmail yang diverifikasi di uni-mannheim.de
Philipp WackerUniversity of CanterburyEmail yang diverifikasi di canterbury.ac.nz
Andrew M StuartComputing + Mathematical Sciences, CaltechEmail yang diverifikasi di caltech.edu
Dirk BlömkerUniversität AugsburgEmail yang diverifikasi di math.uni-augsburg.de
Frances Y. KuoUNSW AustraliaEmail yang diverifikasi di unsw.edu.au
Ian SloanProfessor of Mathematics, University of New South Wales (UNSW Australia)Email yang diverifikasi di unsw.edu.au
Neil ChadaCity University of Hong KongEmail yang diverifikasi di cityu.edu.hk
Björn SprungkTU Bergakademie FreibergEmail yang diverifikasi di math.tu-freiberg.de
Ralf HiptmairETH Zurich, Seminar for Applied MathematicsEmail yang diverifikasi di hiptmair.de
Laura ScarabosioRadboud UniversityEmail yang diverifikasi di math.ru.nl
Alfio BorziInst. for Mathematics, Universität Würzburg, GermanyEmail yang diverifikasi di mathematik.uni-wuerzburg.de
Gregory von WinckelSandia National LaboratoriesEmail yang diverifikasi di sandia.gov
Xin T. TongNational University of SingaporeEmail yang diverifikasi di nus.edu.sg
Alexander LitvinenkoChair of Mathematics for Uncertainty Quantification, RWTH AachenEmail yang diverifikasi di uq.rwth-aachen.de
Joerg StellingDepartment of Biosystems Science and Engineering, ETH ZurichEmail yang diverifikasi di inf.ethz.ch
Martin SchlatherUniversität MannheimEmail yang diverifikasi di uni-mannheim.de
Marco OestingUniversity of StuttgartEmail yang diverifikasi di mathematik.uni-stuttgart.de
Michael HintermüllerWeierstrass Institute for Applied Analysis and Stochastics, and Humboldt-Universität zu BerlinEmail yang diverifikasi di math.hu-berlin.de

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Claudia Schillings

Institute of Mathematics, FU Berlin

Tidak ada email yang diverifikasi

applied and computational mathematics inverse problems optimization under uncertainty uncertainty


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Analysis of the ensemble Kalman filter for inverse problems C Schillings, AM Stuart SIAM Journal on Numerical Analysis 55 (3), 1264-1290, 2017	256	2017
Sparse, adaptive Smolyak quadratures for Bayesian inverse problems C Schillings, C Schwab Inverse Problems 29 (6), 065011, 2013	154	2013
Efficient shape optimization for certain and uncertain aerodynamic design C Schillings, S Schmidt, V Schulz Computers & Fluids 46 (1), 78-87, 2011	106	2011
Convergence analysis of ensemble Kalman inversion: the linear, noisy case C Schillings, AM Stuart Applicable Analysis 97 (1), 107-123, 2018	98	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	87	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	78	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	64	2019
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
Sparsity in Bayesian inversion of parametric operator equations C Schillings, C Schwab Inverse Problems 30 (6), 065007, 2014	61	2014
Scaling limits in computational Bayesian inversion C Schillings, C Schwab ESAIM: Mathematical Modelling and Numerical Analysis 50 (6), 1825-1856, 2016	52	2016
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	49	2018
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
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	42	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	33	2015
On the incorporation of box-constraints for ensemble Kalman inversion NK Chada, C Schillings, S Weissmann arXiv preprint arXiv:1908.00696, 2019	31	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	23	2022
Parabolic PDE-constrained optimal control under uncertainty with entropic risk measure using quasi-Monte Carlo integration PA Guth, V Kaarnioja, FY Kuo, C Schillings, IH Sloan Numerische Mathematik 156 (2), 565-608, 2024	21	2024
Optimal aerodynamic design under uncertainty V Schulz, C Schillings Management and Minimisation of Uncertainties and Errors in Numerical …, 2013	18	2013

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