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ORCIDSergey Oladyshkin
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2020 – today
- 2024
[i5]Cosku Can Horuz, Matthias Karlbauer, Timothy Praditia, Sergey Oladyshkin, Wolfgang Nowak, Sebastian Otte:
Inferring Underwater Topography with FINN. CoRR abs/2408.10649 (2024)- 2023
- [j9]Cosku Can Horuz, Matthias Karlbauer, Timothy Praditia, Martin V. Butz
, Sergey Oladyshkin, Wolfgang Nowak, Sebastian Otte:
Physical Domain Reconstruction with Finite Volume Neural Networks. Appl. Artif. Intell. 37(1) (2023) - [j8]Paul-Christian Bürkner, Ilja Kröker, Sergey Oladyshkin, Wolfgang Nowak:
A fully Bayesian sparse polynomial chaos expansion approach with joint priors on the coefficients and global selection of terms. J. Comput. Phys. 488: 112210 (2023) - [j7]Sergey Oladyshkin, Timothy Praditia, Ilja Kröker, Farid Mohammadi, Wolfgang Nowak, 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 (2023) - [i4]Sergey Oladyshkin, Timothy Praditia, Ilja Kröker, Farid Mohammadi, Wolfgang Nowak, Sebastian Otte:
The Deep Arbitrary Polynomial Chaos Neural Network or how Deep Artificial Neural Networks could benefit from Data-Driven Homogeneous Chaos Theory. CoRR abs/2306.14753 (2023) - 2022
- [j6]Ilja Kröker, Sergey Oladyshkin:
Arbitrary multi-resolution multi-wavelet-based polynomial chaos expansion for data-driven uncertainty quantification. Reliab. Eng. Syst. Saf. 222: 108376 (2022) - [c2]Cosku Can Horuz, Matthias Karlbauer, Timothy Praditia, Martin V. Butz, Sergey Oladyshkin, Wolfgang Nowak, Sebastian Otte:
Infering Boundary Conditions in Finite Volume Neural Networks. ICANN (1) 2022: 538-549 - [c1]Matthias Karlbauer, Timothy Praditia, Sebastian Otte, Sergey Oladyshkin, Wolfgang Nowak, Martin V. Butz:
Composing Partial Differential Equations with Physics-Aware Neural Networks. ICML 2022: 10773-10801 - [d3]Timothy Praditia, Matthias Karlbauer, Sebastian Otte, Sergey Oladyshkin, Martin V. Butz, Wolfgang Nowak:
Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network. DaRUS, 2022
- [d2]Timothy Praditia, Matthias Karlbauer, Sebastian Otte, Sergey Oladyshkin, Martin V. Butz, Wolfang Nowak:
Finite Volume Neural Network. Zenodo, 2022 - [d1]Timothy Praditia, Matthias Karlbauer, Sebastian Otte, Sergey Oladyshkin, Martin V. Butz, Wolfgang Nowak:
Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network. DaRUS, 2022 - 2021
- [i3]Timothy Praditia, Matthias Karlbauer, Sebastian Otte, Sergey Oladyshkin, Martin V. Butz, Wolfgang Nowak:
Finite Volume Neural Network: Modeling Subsurface Contaminant Transport. CoRR abs/2104.06010 (2021) - [i2]Matthias Karlbauer, Timothy Praditia, Sebastian Otte, Sergey Oladyshkin, Wolfgang Nowak, Martin V. Butz:
Composing Partial Differential Equations with Physics-Aware Neural Networks. CoRR abs/2111.11798 (2021) - 2020
- [j5]Sergey Oladyshkin, Farid Mohammadi, Ilja Kröker, Wolfgang Nowak:
Bayesian3 Active Learning for the Gaussian Process Emulator Using Information Theory. Entropy 22(8): 890 (2020) - [j4]Sinan Xiao, Sergey Oladyshkin, Wolfgang Nowak:
Reliability analysis with stratified importance sampling based on adaptive Kriging. Reliab. Eng. Syst. Saf. 197: 106852 (2020)
2010 – 2019
- 2019
- [j3]Sergey Oladyshkin, Wolfgang Nowak:
The Connection between Bayesian Inference and Information Theory for Model Selection, Information Gain and Experimental Design. Entropy 21(11): 1081 (2019) - 2018
- [j2]Sergey Oladyshkin, Wolfgang Nowak:
Incomplete statistical information limits the utility of high-order polynomial chaos expansions. Reliab. Eng. Syst. Saf. 169: 137-148 (2018) - [i1]Markus Köppel, Fabian Franzelin, Ilja Kröker, Sergey Oladyshkin, Gabriele Santin, Dominik Wittwar, Andrea Barth, Bernard Haasdonk, Wolfgang Nowak, Dirk Pflüger, Christian Rohde:
Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario. CoRR abs/1802.03064 (2018) - 2012
- [j1]Sergey Oladyshkin, Wolfgang Nowak:
Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion. Reliab. Eng. Syst. Saf. 106: 179-190 (2012)
Coauthor Index
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