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Disambiguation of "Oladyshkin, Sergey"

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Mixed covariance function Kriging model for uncertainty quantification

, , , , and . submitted to International Journal for Uncertainty Quantification, (2021)

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Apl. Prof. Dr. Sergey Oladyshkin University of Stuttgart

Sergey Abramov University of Stuttgart

 

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Data-driven surrogate-based Bayesian model calibration for predicting vadose zone temperatures in drinking water supply pipes, , , , and . Geophys. Res. Abstr., 25, EGU2024-7820, EGU General Assembly 2024, (April 2024)Bayesian3 active learning for Gaussian process emulator using information theory, , , and . Entropy, 22 (0890): 1-27 (2020)Reliability Analysis with Stratified Importance Sampling Based on Adaptive Kriging, , and . Reliability Engineering & System Safety, (2020)Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site, , , , and . Scientific reports, (2016)Physics-Informed Machine Learning in Hydrology II Oral, , and . American Geophysical Union, Fall Meeting 2021, page H34F. American Geophysical Union, (2021)Surrogate-based Bayesian comparison of computationally expensive models : application to microbially induced calcite precipitation, , , , , , and . Computational geosciences, 25 (6): 1899-1917 (2021)Finite Volume Neural Network : Modeling Subsurface Contaminant Transport, , , , , and . ICLR 2021 : Ninth International Conference on Learning Representations, Cornell University, (2021)A unified framework for quantitative interdisciplinary flood risk assessment, , , , , , , , , and 7 other author(s). American Geophysical Union, Fall Meeting 2020, page H177-01. Smithsonian Astrophysical Observatory, (2020)Data-driven surrogates for rapid simulation and optimization of WAG injection in fractured carbonate reservoirs, , , and . Petroleum geoscience, 23 (2): 270-283 (2017)Uncertainty quantification using Bayesian arbitrary polynomial chaos for computationally demanding environmental modelling: conventional, sparse and adaptive strategy, , , , , , , , and . Computational Methods in Water Resources 2020, Stanford, CMWR Organizing Committee, (2020)