Ilja Kröker

Orcid: 0000-0003-0360-5307

According to our database1, Ilja Kröker authored at least 7 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2023
The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory.
Neural Networks, September, 2023

A fully Bayesian sparse polynomial chaos expansion approach with joint priors on the coefficients and global selection of terms.
J. Comput. Phys., September, 2023

2022
Arbitrary multi-resolution multi-wavelet-based polynomial chaos expansion for data-driven uncertainty quantification.
Reliab. Eng. Syst. Saf., 2022

2020
Bayesian3 Active Learning for the Gaussian Process Emulator Using Information Theory.
Entropy, 2020

2019
Computational uncertainty quantification for some strongly degenerate parabolic convection-diffusion equations.
J. Comput. Appl. Math., 2019

2018
Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario.
CoRR, 2018

2016
Computational uncertainty quantification for a clarifier-thickener model with several random perturbations: A hybrid stochastic Galerkin approach.
Comput. Chem. Eng., 2016


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