57 citations · 113 across the 21 of their papers we have counts for
4 papers · 1 filter
One-shot Learning of Surrogates in PDE-constrained Optimization Under Uncertainty
Philipp A. Guth, Claudia Schillings, Simon Weissmann
We propose a general framework for machine learning based optimization under uncertainty. Our approach replaces the complex forward model by a surrogate, which is learned simultane…
Adaptive Tikhonov strategies for stochastic ensemble Kalman inversion
Simon Weissmann, Neil K. Chada, Claudia Schillings +1
Ensemble Kalman inversion (EKI) is a derivative-free optimizer aimed at solving inverse problems, taking motivation from the celebrated ensemble Kalman filter. The purpose of this…
Continuous time limit of the stochastic ensemble Kalman inversion: Strong convergence analysis
Dirk Blömker, Claudia Schillings, Philipp Wacker +1
The Ensemble Kalman inversion (EKI) method is a method for the estimation of unknown parameters in the context of (Bayesian) inverse problems. The method approximates the underlyin…
Hierarchical surrogate-based Approximate Bayesian Computation for an electric motor test bench
David N. John, Livia Stohrer, Claudia Schillings +2
Inferring parameter distributions of complex industrial systems from noisy time series data requires methods to deal with the uncertainty of the underlying data and the used simula…