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Article

Schillings, Claudia and Schwab, Christoph (2016) Scaling limits in computational Bayesian inversion. ESAIM: Mathematical Modelling and Numerical Analysis, 50 (6). pp. 1825-1856. ISSN 2822-7840; eISSN = 2804-7214

Schillings, Claudia and Sunnåker, Mikael and Stelling, Jörg and Schwab, Christoph (2015) Efficient characterization of parametric uncertainty of complex (bio) chemical networks. PLOS Computational Biology .

Schillings, Claudia and Schwab, Christoph (2014) Sparsity in Bayesian inversion of parametric operator equations. Inverse Problems, 30 (6).

Schillings, Claudia and Schwab, Christoph (2013) Sparse, adaptive Smolyak quadratures for Bayesian inverse problems. Inverse Problems, 29 (6).

Schillings, Claudia and Schwab, Christoph (2013) A note on sparse, adaptive Smolyak quadratures for Bayesian inverse problems. SAM Research Report, 06 .

Schwab, Christoph and Schillings, Claudia (2012) Sparse, adaptive Smolyak algorithms for Bayesian inverse problems. Research Report No. 2012-37 .

Book Section

Gantner, Robert N. and Schillings, Claudia and Schwab, Christoph (2016) Binned Multilevel Monte Carlo for Bayesian Inverse Problems with Large Data. In: Domain Decomposition Methods in Science and Engineering XXII. Springer, pp. 511-519. ISBN 978-3-319-18826-3

Hansen, Markus and Schillings, Claudia and Schwab, Christoph (2014) Sparse approximation algorithms for high dimensional parametric initial value problems. In: Modeling, Simulation and Optimization of Complex Processes - HPSC 2012. Proceedings of the Fifth International Conference on High Performance Scientific Computing, March 5-9, 2012, Hanoi, Vietnam . Springer Cham, pp. 63-81. ISBN 978-3-319-09062-7

Conference or Workshop Item

Gantner, Robert N. and Schillings, Claudia and Schwab, Christoph (2014) Multilevel Monte Carlo for Bayesian Inverse Problems. In: Swiss Numerics Day 2014, April 2014, Universität Zürich.

Schwab, Christoph and Schillings, Claudia (2013) Sparse Quadrature Approach to Bayesian Inverse Problems. In: SIAM Conference on Computational Science and Engineering.