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ORCIDClaudia Schillings
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2020 – today
- 2024
[j11]Philipp A. Guth, Claudia Schillings, Simon Weissmann:
One-Shot Learning of Surrogates in PDE-Constrained Optimization under Uncertainty. SIAM/ASA J. Uncertain. Quantification 12(2): 614-645 (2024)- [j10]Philipp A. Guth, Vesa Kaarnioja, Frances Y. Kuo, Claudia Schillings, Ian H. Sloan
:
Parabolic PDE-constrained optimal control under uncertainty with entropic risk measure using quasi-Monte Carlo integration. Numerische Mathematik 156(2): 565-608 (2024) - [i14]David Sommer, Robert Gruhlke, Max Kirstein, Martin Eigel, Claudia Schillings:
Generative Modelling with Tensor Train approximations of Hamilton-Jacobi-Bellman equations. CoRR abs/2402.15285 (2024) - [i13]Vesa Kaarnioja, Claudia Schillings:
Quasi-Monte Carlo for Bayesian design of experiment problems governed by parametric PDEs. CoRR abs/2405.03529 (2024) - 2023
- [j9]Claudia Schillings, Claudia Totzeck, Philipp Wacker:
Ensemble-Based Gradient Inference for Particle Methods in Optimization and Sampling. SIAM/ASA J. Uncertain. Quantification 11(3): 757-787 (2023) - [i12]Matei Hanu, Jonas Latz, Claudia Schillings:
Subsampling in ensemble Kalman inversion. CoRR abs/2302.11323 (2023) - [i11]Steffen Jung, Jan Christian Schwedhelm, Claudia Schillings, Margret Keuper:
Happy People - Image Synthesis as Black-Box Optimization Problem in the Discrete Latent Space of Deep Generative Models. CoRR abs/2306.06684 (2023) - [i10]Matei Hanu, Jürgen Hesser, Guido Kanschat, Javier Moviglia, Claudia Schillings, Jan Stallkamp:
Ensemble Kalman Inversion for Image Guided Guide Wire Navigation in Vascular Systems. CoRR abs/2312.06460 (2023) - 2022
- [j8]Dirk Blömker, Claudia Schillings, Philipp Wacker, Simon Weissmann:
Continuous Time Limit of the Stochastic Ensemble Kalman Inversion: Strong Convergence Analysis. SIAM J. Numer. Anal. 60(6): 3181-3215 (2022) - [i9]Philipp A. Guth, Vesa Kaarnioja, Frances Y. Kuo, Claudia Schillings, Ian H. Sloan:
Parabolic PDE-constrained optimal control under uncertainty with entropic risk measure using quasi-Monte Carlo integration. CoRR abs/2208.02767 (2022) - [i8]Claudia Schillings, Claudia Totzeck, Philipp Wacker:
Ensemble-based gradient inference for particle methods in optimization and sampling. CoRR abs/2209.15420 (2022) - 2021
- [j7]Philipp A. Guth, Vesa Kaarnioja, Frances Y. Kuo, Claudia Schillings, Ian H. Sloan:
A Quasi-Monte Carlo Method for Optimal Control Under Uncertainty. SIAM/ASA J. Uncertain. Quantification 9(2): 354-383 (2021) - [i7]Dirk Blömker, Claudia Schillings, Philipp Wacker, Simon Weissmann:
Continuous time limit of the stochastic ensemble Kalman inversion: Strong convergence analysis. CoRR abs/2107.14508 (2021) - [i6]Simon Weissmann, Neil K. Chada, Claudia Schillings, Xin T. Tong:
Adaptive Tikhonov strategies for stochastic ensemble Kalman inversion. CoRR abs/2110.09142 (2021) - [i5]Philipp A. Guth, Claudia Schillings, Simon Weissmann:
A General Framework for Machine Learning based Optimization Under Uncertainty. CoRR abs/2112.11126 (2021) - 2020
- [j6]Claudia Schillings, Björn Sprungk, Philipp Wacker:
On the convergence of the Laplace approximation and noise-level-robustness of Laplace-based Monte Carlo methods for Bayesian inverse problems. Numerische Mathematik 145(4): 915-971 (2020) - [i4]Philipp A. Guth, Claudia Schillings, Simon Weissmann:
Ensemble Kalman filter for neural network based one-shot inversion. CoRR abs/2005.02039 (2020) - [i3]Neil K. Chada, Claudia Schillings, Xin T. Tong, Simon Weissmann:
Consistency analysis of bilevel data-driven learning in inverse problems. CoRR abs/2007.02677 (2020)
2010 – 2019
- 2019
- [i2]Neil K. Chada, Claudia Schillings, Simon Weissmann:
On the Incorporation of Box-Constraints for Ensemble Kalman Inversion. CoRR abs/1908.00696 (2019) - [i1]Philipp A. Guth, Vesa Kaarnioja, Frances Y. Kuo, Claudia Schillings, Ian H. Sloan:
A quasi-Monte Carlo Method for an Optimal Control Problem Under Uncertainty. CoRR abs/1910.10022 (2019) - 2018
- [j5]Ralf Hiptmair, Laura Scarabosio, Claudia Schillings, Christoph Schwab:
Large deformation shape uncertainty quantification in acoustic scattering. Adv. Comput. Math. 44(5): 1475-1518 (2018) - [j4]Dirk Blömker, Claudia Schillings, Philipp Wacker:
A Strongly Convergent Numerical Scheme from Ensemble Kalman Inversion. SIAM J. Numer. Anal. 56(4): 2537-2562 (2018) - 2017
- [j3]Dishi Liu, Alexander Litvinenko, Claudia Schillings, Volker Schulz:
Quantification of Airfoil Geometry-Induced Aerodynamic Uncertainties - Comparison of Approaches. SIAM/ASA J. Uncertain. Quantification 5(1): 334-352 (2017) - [j2]Claudia Schillings, Andrew M. Stuart:
Analysis of the Ensemble Kalman Filter for Inverse Problems. SIAM J. Numer. Anal. 55(3): 1264-1290 (2017) - 2015
- [j1]Claudia Schillings, Mikael Sunnåker, Jörg Stelling, Christoph Schwab:
Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks. PLoS Comput. Biol. 11(8) (2015) - 2012
- [c1]Markus Hansen, Claudia Schillings, Christoph Schwab:
Sparse Approximation Algorithms for High Dimensional Parametric Initial Value Problems. HPSC 2012: 63-81
Coauthor Index
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