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Number of items at this level: 9. 2022Chada, Neil and Schillings, Claudia and Tong, Xin and Weissmann, Simon (2022) Consistency analysis of bilevel data-driven learning in inverse problems. Communications in Mathematical Sciences, 20 (1). pp. 123-164. Weissmann, Simon and Chada, Neil and Schillings, Claudia and Tong, Xin (2022) Adaptive Tikhonov strategies for stochastic ensemble Kalman inversion. . . (Submitted) 2021Blömker, Dirk and Schillings, Claudia and Wacker, Philipp and Weissmann, Simon (2021) Continuous time limit of the stochastic ensemble Kalman inversion: Strong convergence analysis. . . (Submitted) Guth, Philipp A. and Kaarnioja, Vesa and Kuo, Frances Y. and Schillings, Claudia and Sloan, Ian H. (2021) A Quasi-Monte Carlo Method for Optimal Control Under Uncertainty. SIAM/ASA Journal on Uncertainty Quantification, 9 (2). John, David N. and Stohrer, Livia and Schillings, Claudia and Schick, Michael and Heuveline, Vincent (2021) Hierarchical surrogate-based Approximate Bayesian Computation for an electric motor test bench. . . (Submitted) Schillings, Claudia and Guth, Philipp A. and Weissmann, Simon (2021) A General Framework for Machine Learning based Optimization Under Uncertainty. . . (Submitted) 2020Schillings, Claudia and Sprungk, Björn and Wacker, Philipp (2020) On the convergence of the Laplace approximation and noise-level-robustness of Laplace-based Monte Carlo methods for Bayesian inverse problems. Numerische Mathematik, 145 . pp. 915-971. Schillings, Claudia and Sprungk, Björn and Wacker, Philipp (2020) On the convergence of the Laplace approximation and noise-level-robustness of Laplace-based Monte Carlo methods for Bayesian inverse problems. Numerische Mathematik, 145 (1). pp. 915-971. 2010Borzì, Alfio and Schulz, Volker H. and Schillings, Claudia and von Winckel, Gregory (2010) On the treatment of distributed uncertainties in PDE‐constrained optimization. GAMM-Mitteilungen, 33 (2). pp. 230-246. |