Publications

Ilja Kröker, Elisabeth Nißler, Sergey Oladyshkin, Wolfgang Nowak, and Claus Haslauer. Data-driven surrogate-based Bayesian model calibration for predicting vadose zone temperatures in drinking water supply pipes. Geophys. Res. Abstr., (25, EGU2024-7820)April 2024. [PUMA: 2 HaslauerClaus IWSABT:ls3 IWSAUTHOR: IWSAUTHOR:KroekerIlja IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSMONTH:04 IWSSUBTYPE:inproceedings IWSTYPEDE:Konferenzbeiträge IWSTYPEEN:contribution_to_edited_volumes IWSTYPENR:3 IWSYEAR:2024]

Ilja Kröker, Tim Brünnette, Nils Wildt, Maria Fernanda Morales Oreamuno, Rebecca Kohlhaas, Sergey Oladyshkin, and Wolfgang Nowak. Bayesian Active Learning for Regularized Multi-Resolution Arbitrary Polynomial Chaos using Information Theory.. International Journal for Uncertainty Quantification, 2024 (submitted). [PUMA: 1 IWSABT:ls3 IWSAUTHOR:BruennetteTim IWSAUTHOR:KohlhaasRebecca IWSAUTHOR:KroekerIlja IWSAUTHOR:MoralesOreamunoMariaFernanda IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSAUTHOR:WildtNils IWSMONTH:12 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2024]

Sergey Oladyshkin, Timothy Praditia, Ilja Kroeker, Farid Mohammadi, Wolfgang Nowak, and Sebastian Otte. The Deep Arbitrary Polynomial Chaos Neural Network or how Deep Artificial Neural Networks could benefit from Data-Driven Homogeneous Chaos Theory. Neural Networks, (166):85-104, Elsevier, 2023. [PUMA: 1 IWSABT:ls3 IWSAUTHOR:KroekerIlja IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSAUTHOR:PraditiaTimothy IWSMONTH:09 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2023 from:sscheurer peerreviewed pn5]

Ilja Kröker, Sergey Oladyshkin, and Iryna Rybak. Global sensitivity analysis using multi-resolution polynomial chaos expansion for coupled Stokes-Darcy flow problems. Computational Geosciences, 2023. [PUMA: 1 IWSABT:ls3 IWSAUTHOR:KroekerIlja IWSAUTHOR:OladyshkinSergey IWSMONTH:07 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2023 from:timothypraditia] URL

Rebecca Kohlhaas, Ilja Kröker, Sergey Oladyshkin, and Wolfgang Nowak. Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator: concept for bias correction, assessment of surrogate reliability and its application to the carbon dioxide benchmark. Computational Geosciences, (27)3:1-21, 2023. [PUMA: 1 IWSABT:ls3 IWSAUTHOR:KroekerIlja IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSMONTH:04 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2023 from:timothypraditia peerreviewed]

Paul-Christian Bürkner, Ilja Kröker, Sergey Oladyshkin, and Wolfgang Nowak. The sparse Polynomial Chaos expansion: a fully Bayesian approach with joint priors on the coefficients and global selection of terms. Journal of Computational Physics, 112210, 2023. [PUMA: 1 IWSABT:ls3 IWSAUTHOR:KroekerIlja IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSMONTH:05 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2023 from:timothypraditia]

Sergey Oladyshkin, Farid Mohammadi, Ilja Kröker, and Wolfgang Nowak. Bayesian3 active learning for Gaussian process emulator using information theory. Entropy, (22)0890:1-27, Multidisciplinary Digital Publishing Institute, 2020. [PUMA: IWSABT:ls3 IWSAUTHOR:KroekerIlja IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSMONTH:12 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2020 from:timothypraditia]

S. Oladyshkin, F. Beckers, I. Kroeker, F. Mohammadi, A. Heredia, M. Noack, B. Flemisch, S. Wieprecht, and W. Nowak. Uncertainty quantification using Bayesian arbitrary polynomial chaos for computationally demanding environmental modelling: conventional, sparse and adaptive strategy. Computational Methods in Water Resources (CMWR), 2020. [PUMA: IWSABT:ls3 IWSAUTHOR:KroekerIlja IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSMONTH:12 IWSSUBTYPE:inproceedings IWSTYPEDE:Konferenzbeiträge IWSTYPEEN:contribution_to_edited_volumes IWSTYPENR:3 IWSYEAR:2020 from:timothypraditia]

M. Köppel, F. Franzelin, I. Kröker, S. Oladyshkin, G. Santin, D. Wittwar, A. Barth, B. Haasdonk, W. Nowak, D. Pflüger, and C. Rohde. Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario. Computational Geosciences, (23)2:339-354, 2019. [PUMA: 1 IWSABT:ls3 IWSAUTHOR:KroekerIlja IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSMONTH:12 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2019 from:jannikhaas from:timothypraditia]