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Kröker, Ilja
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1

Gaussian active learning on multi-resolution arbitrary poly..:

Kohlhaas, Rebecca ; Kröker, Ilja ; Oladyshkin, Sergey.
Computational Geosciences.  27 (2023)  3 - p. 369-389 , 2023
Link: https://doi.org/10.1007/..
 
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2

A computational approach to identifiability analysis for a ..:

Bürger, Raimund ; Chowell, Gerardo ; Kröker, Ilja.
Journal of Biological Dynamics.  17 (2023)  1 - p. , 2023
Link: https://doi.org/10.1080/..
 
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3

Global sensitivity analysis using multi-resolution polynomi..:

Kröker, Ilja ; Oladyshkin, Sergey ; Rybak, Iryna
Computational Geosciences.  27 (2023)  5 - p. 805-827 , 2023
Link: https://doi.org/10.1007/..
 
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4

A fully Bayesian sparse polynomial chaos expansion approach..:

Bürkner, Paul-Christian ; Kröker, Ilja ; Oladyshkin, Sergey.
Journal of Computational Physics.  488 (2023)  - p. 112210 , 2023
Link: https://doi.org/10.1016/..
 
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5

Optimal Exposure Time in Gamma-Ray Attenuation Experiments ..:

Gonzalez-Nicolas, Ana ; Bilgic, Deborah ; Kröker, Ilja...
Transport in Porous Media.  143 (2022)  2 - p. 463-496 , 2022
Link: https://doi.org/10.1007/..
 
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6

Arbitrary multi-resolution multi-wavelet-based polynomial c..:

Kröker, Ilja ; Oladyshkin, Sergey
Reliability Engineering & System Safety.  222 (2022)  - p. 108376 , 2022
Link: https://doi.org/10.1016/..
 
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7

Computational uncertainty quantification for some strongly ..:

Bürger, Raimund ; Kröker, Ilja
Journal of Computational and Applied Mathematics.  348 (2019)  - p. 490-508 , 2019
Link: https://doi.org/10.1016/..
 
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8

Comparison of data-driven uncertainty quantification method..:

Köppel, Markus ; Franzelin, Fabian ; Kröker, Ilja...
Computational Geosciences.  23 (2018)  2 - p. 339-354 , 2018
Link: https://doi.org/10.1007/..
 
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9

Computational uncertainty quantification for a clarifier-th..:

Barth, Andrea ; Bürger, Raimund ; Kröker, Ilja.
Computers & Chemical Engineering.  89 (2016)  - p. 11-26 , 2016
Link: https://doi.org/10.1016/..
 
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10

A stochastically and spatially adaptive parallel scheme for..:

Kröker, Ilja ; Nowak, Wolfgang ; Rohde, Christian
Computational Geosciences.  19 (2015)  2 - p. 269-284 , 2015
Link: https://doi.org/10.1007/..
 
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11

The Deep Arbitrary Polynomial Chaos Neural Network or how D..:

Oladyshkin, Sergey ; Praditia, Timothy ; Kröker, Ilja...
http://arxiv.org/abs/2306.14753.  , 2023
Link: http://arxiv.org/abs/230..
 
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12

Optimal Exposure Time in Gamma-Ray Attenuation Experiments ..:

Gonzalez-Nicolas, Ana ; Bilgic, Deborah ; Kröker, Ilja...
info:eu-repo/semantics/altIdentifier/wos/000788432000002.  , 2022
Link: https://publikationen.bi..
 
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13

A fully Bayesian sparse polynomial chaos expansion approach..:

Bürkner, Paul-Christian ; Kröker, Ilja ; Oladyshkin, Sergey.
http://arxiv.org/abs/2204.06043.  , 2022
Link: http://arxiv.org/abs/220..
 
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14

Comparison of data-driven uncertainty quantification method..:

Köppel, Markus ; Franzelin, Fabian ; Kröker, Ilja...
http://arxiv.org/abs/1802.03064.  , 2018
Link: http://arxiv.org/abs/180..
 
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15

Datasets and executables of data-driven uncertainty quantif..:

Köppel, Markus ; Franzelin, Fabian ; Kröker, Ilja...
doi:10.5281/zenodo.933826.  , 2017
Link: https://zenodo.org/recor..
 
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