Sergey Oladyshkin

18 papers A* 1Journal 16Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Surrogate-assisted global sensitivity analysis of a hybrid-dimensional Stokes-Brinkman-Darcy model.
CoRR
Linheng Ruan, Ilja Kröker, Sergey Oladyshkin, Iryna Rybak
2025 J jnl
CODE: A global approach to ODE dynamics learning.
CoRR
Nils Wildt, Daniel M. Tartakovsky, Sergey Oladyshkin, Wolfgang Nowak
2024 J jnl
Inferring Underwater Topography with FINN.
CoRR
Cosku Can Horuz, Matthias Karlbauer, Timothy Praditia, Sergey Oladyshkin, Wolfgang Nowak, Sebastian Otte
2023 J jnl
A fully Bayesian sparse polynomial chaos expansion approach with joint priors on the coefficients and global selection of terms.
J. Comput. Phys.
Paul-Christian Bürkner, Ilja Kröker, Sergey Oladyshkin, Wolfgang Nowak
2023 J jnl
Physical Domain Reconstruction with Finite Volume Neural Networks.
Appl. Artif. Intell.
Cosku Can Horuz, Matthias Karlbauer, Timothy Praditia, Martin V. Butz, Sergey Oladyshkin, Wolfgang Nowak, Sebastian Otte
2023 J jnl
The Deep Arbitrary Polynomial Chaos Neural Network or how Deep Artificial Neural Networks could benefit from Data-Driven Homogeneous Chaos Theory.
CoRR
Sergey Oladyshkin, Timothy Praditia, Ilja Kröker, Farid Mohammadi, Wolfgang Nowak, Sebastian Otte
2023 J jnl
The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory.
Neural Networks
Sergey Oladyshkin, Timothy Praditia, Ilja Kröker, Farid Mohammadi, Wolfgang Nowak, Sebastian Otte
2022 J jnl
Arbitrary multi-resolution multi-wavelet-based polynomial chaos expansion for data-driven uncertainty quantification.
Reliab. Eng. Syst. Saf.
Ilja Kröker, Sergey Oladyshkin
2022 A* conf
Composing Partial Differential Equations with Physics-Aware Neural Networks.
ICML
Matthias Karlbauer, Timothy Praditia, Sebastian Otte, Sergey Oladyshkin, Wolfgang Nowak, Martin V. Butz
2022 — conf
Infering Boundary Conditions in Finite Volume Neural Networks.
ICANN (1)
Cosku Can Horuz, Matthias Karlbauer, Timothy Praditia, Martin V. Butz, Sergey Oladyshkin, Wolfgang Nowak, Sebastian Otte
2021 J jnl
Composing Partial Differential Equations with Physics-Aware Neural Networks.
CoRR
Matthias Karlbauer, Timothy Praditia, Sebastian Otte, Sergey Oladyshkin, Wolfgang Nowak, Martin V. Butz
2021 J jnl
Finite Volume Neural Network: Modeling Subsurface Contaminant Transport.
CoRR
Timothy Praditia, Matthias Karlbauer, Sebastian Otte, Sergey Oladyshkin, Martin V. Butz, Wolfgang Nowak
2020 J jnl
Bayesian3 Active Learning for the Gaussian Process Emulator Using Information Theory.
Entropy
Sergey Oladyshkin, Farid Mohammadi, Ilja Kröker, Wolfgang Nowak
2020 J jnl
Reliability analysis with stratified importance sampling based on adaptive Kriging.
Reliab. Eng. Syst. Saf.
Sinan Xiao, Sergey Oladyshkin, Wolfgang Nowak
2019 J jnl
The Connection between Bayesian Inference and Information Theory for Model Selection, Information Gain and Experimental Design.
Entropy
Sergey Oladyshkin, Wolfgang Nowak
2018 J jnl
Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario.
CoRR
Markus Köppel, Fabian Franzelin, Ilja Kröker, Sergey Oladyshkin, Gabriele Santin, Dominik Wittwar, Andrea Barth, Bernard Haasdonk, Wolfgang Nowak, Dirk Pflüger, Christian Rohde
2018 J jnl
Incomplete statistical information limits the utility of high-order polynomial chaos expansions.
Reliab. Eng. Syst. Saf.
Sergey Oladyshkin, Wolfgang Nowak
2012 J jnl
Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion.
Reliab. Eng. Syst. Saf.
Sergey Oladyshkin, Wolfgang Nowak