A unified framework for quantitative interdisciplinary flood risk assessment. AGU, 2020. [PUMA: IWSABT:lww IWSAUTHOR:ClassHolger IWSAUTHOR:GuthkeAnneli IWSAUTHOR:HaasJannik IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSAUTHOR:TerheidenKristina IWSAUTHOR:WieprechtSilke IWSETC:N IWSOPENACCESS:N IWSREVIEWED:N IWSSUBTYPE:inproceedings IWSTYPEDE:Konferenzbeiträge IWSTYPEEN:contribution_to_edited_volumes IWSTYPENR:3 IWSYEAR:2020]
Composing Partial Differential Equations with Physics-Aware Neural Networks. Proceedings of the 39th International Conference on Machine Learning, 10773--10801, Baltimore, USA, 17--23 Jul 2022. [PUMA: 2 IWSABT:ls3 IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSAUTHOR:PraditiaTimothy IWSMONTH:12 IWSSUBTYPE:inproceedings IWSTYPEDE:Konferenzbeiträge IWSTYPEEN:contribution_to_edited_volumes IWSTYPENR:3 IWSYEAR:2022]
Finite Volume Neural Networks: a Hybrid Modeling Strategy for Subsurface Contaminant Transport. AGU Fall Meeting 2021, 2021. [PUMA: IWSABT:ls3 IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSAUTHOR:PraditiaTimothy IWSMONTH:12 IWSSUBTYPE:inproceedings IWSTYPEDE:Konferenzbeiträge IWSTYPEEN:contribution_to_edited_volumes IWSTYPENR:3 IWSYEAR:2021 from:timothypraditia]
Mixed covariance function Kriging model for uncertainty quantification. International Journal for Uncertainty Quantification, (12)3:17-30, 2022. [PUMA: 1 IWSABT:ls3 IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSMONTH:12 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2022 from:timothypraditia]
Finite Volume Neural Network: Modeling Subsurface Contaminant Transport. Deep Learning for Simulation ICLR Workshop 2021, 2021. [PUMA: 2 IWSABT:ls3 IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSAUTHOR:PraditiaTimothy IWSMONTH:3 IWSSUBTYPE:inproceedings IWSTYPEDE:Konferenzbeiträge IWSTYPEEN:contribution_to_edited_volumes IWSTYPENR:3 IWSYEAR:2021 from:timothypraditia] URL
Unified Bayesian inference framework for surrogate modelling: connection between existing techniques and their common fundamentals. Reliability Engineering and System Safety, 2021 (submitted). [PUMA: IWSMONTH:12 IWSYEAR:2021 IWSAUTHOR:OladyshkinSergey IWSTYPENR:1 from:timothypraditia IWSSUBTYPE:article IWSAUTHOR:NowakWolfgang IWSAUTHOR:XiaoSinan IWSTYPEDE:Publikationen IWSABT:ls3 IWSTYPEEN:articles]
Prognosis of water levels in a moor groundwater system influenced by hydrology and water extraction using an artificial neural network. online, April 2021. [PUMA: 2 IWSABT:ls3 IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSAUTHOR:PraditiaTimothy IWSMONTH:4 IWSSUBTYPE:inproceedings IWSTYPEDE:Konferenzbeiträge IWSTYPEEN:contribution_to_edited_volumes IWSTYPENR:3 IWSYEAR:2021 from:timothypraditia]
Universal Differential Equation for Diffusion-Sorption Problem in Porous Media Flow. online, April 2021. [PUMA: 2 IWSABT:ls3 IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSAUTHOR:PraditiaTimothy IWSMONTH:4 IWSSUBTYPE:inproceedings IWSTYPEDE:Konferenzbeiträge IWSTYPEEN:contribution_to_edited_volumes IWSTYPENR:3 IWSYEAR:2021 from:timothypraditia]
Physics Informed Neural Network for porous media modelling. Stuttgart, Germany, February 2021. [PUMA: IWSTYPEEN:contribution_to_edited_volumes IWSTYPEDE:Konferenzbeiträge IWSYEAR:2021 IWSAUTHOR:OladyshkinSergey IWSTYPENR:3 IWSMONTH:2 from:timothypraditia 2 IWSAUTHOR:NowakWolfgang IWSSUBTYPE:inproceedings IWSAUTHOR:PraditiaTimothy IWSABT:ls3]
A unified framework for quantitative interdisciplinary flood risk assessment. online, December 2020. [PUMA: IWSMONTH:12 IWSTYPEEN:contribution_to_edited_volumes IWSTYPEDE:Konferenzbeiträge IWSAUTHOR:OladyshkinSergey IWSYEAR:2020 IWSTYPENR:3 from:timothypraditia 2 IWSAUTHOR:NowakWolfgang IWSSUBTYPE:inproceedings 3 IWSAUTHOR:HaasJannik IWSABT:ls3 IWSAUTHOR:GuthkeAnneli]
Surrogate-based Bayesian Comparison of Computationally Expensive Models: Application to Microbially Induced Calcite Precipitation. Computational Geosciences, (25):1899-1917, 2021. [PUMA: 1 IWSABT:ls3 IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSAUTHOR:ScheurerStefania IWSAUTHOR:Schäfer-Rodrigues-SilvaAline IWSMONTH:12 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2021 from:timothypraditia]
Resampling method for reliability-based design optimization based on thermodynamic integration and parallel tempering. Mechanical Systems and Signal Processing, (156):107630, 2021. [PUMA: IWSABT:ls3 IWSAUTHOR:ChengKai IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSAUTHOR:XiaoSinan IWSMONTH:12 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2020 from:timothypraditia]
Bayesian3 active learning for Gaussian process emulator using information theory. Entropy, (22)0890:1-27, Multidisciplinary Digital Publishing Institute, 2020. [PUMA: IWSABT:ls3 IWSAUTHOR:KroekerIlja IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSMONTH:12 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2020 from:timothypraditia]
Application of computed tomography (CT) in geologic CO_2 storage research: a critical review. Journal of Natural Gas Science and Engineering, 103591, 2020. [PUMA: 1 IWSABT:ls3 IWSAUTHOR:OladyshkinSergey IWSMONTH:12 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2020 from:timothypraditia]
Forward-reverse switch between density-based and regional sensitivity analysis. Applied Mathematical Modelling, (84):377-392, 2020. [PUMA: IWSABT:ls3 IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSAUTHOR:XiaoSinan IWSMONTH:12 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2020 from:timothypraditia]
Global sensitivity analysis of a CaO/Ca(OH)2 thermochemical energy storage model for parametric effect analysis. Applied Energy, (285):116456, 2021. [PUMA: IWSABT:ls3 IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSAUTHOR:PraditiaTimothy IWSAUTHOR:XiaoSinan IWSMONTH:12 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2021 from:timothypraditia] URL
Using physics-based regularization in Artificial Neural Networks to predict thermochemical energy storage systems. Fall Meeting 2019, Abstract: IN32B-15, San Francisco, CA, USA, December 2019. [PUMA: IWSMONTH:12 IWSTYPEEN:contribution_to_edited_volumes IWSTYPEDE:Konferenzbeiträge IWSAUTHOR:OladyshkinSergey IWSTYPENR:3 from:timothypraditia IWSYEAR:2019 IWSAUTHOR:NowakWolfgang IWSSUBTYPE:inproceedings 3 IWSAUTHOR:PraditiaTimothy IWSABT:ls3]
Bayesian Calibration and Validation of a Large-scale and Time-demanding Sediment Transport Model. Water Resources Research, (56)7:e2019WR026966, 2020. [PUMA: IWSABT:ls3 IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSMONTH:12 IWSSUBTYPE:article IWSTYPEDE:Publikationen IWSTYPEEN:articles IWSTYPENR:1 IWSYEAR:2019 from:timothypraditia]
Uncertainty quantification using Bayesian arbitrary polynomial chaos for computationally demanding environmental modelling: conventional, sparse and adaptive strategy. Computational Methods in Water Resources (CMWR), 2020. [PUMA: IWSABT:ls3 IWSAUTHOR:KroekerIlja IWSAUTHOR:NowakWolfgang IWSAUTHOR:OladyshkinSergey IWSMONTH:12 IWSSUBTYPE:inproceedings IWSTYPEDE:Konferenzbeiträge IWSTYPEEN:contribution_to_edited_volumes IWSTYPENR:3 IWSYEAR:2020 from:timothypraditia]
Improving Thermochemical Energy Storage dynamics forecast with Physics-Inspired Neural Network architecture. Energies, (13)15:3873, 2020. [PUMA: IWSMONTH:12 IWSAUTHOR:OladyshkinSergey IWSYEAR:2020 IWSTYPENR:1 from:timothypraditia IWSSUBTYPE:article 1 IWSAUTHOR:NowakWolfgang IWSAUTHOR:PraditiaTimothy IWSTYPEDE:Publikationen IWSABT:ls3 IWSTYPEEN:articles] URL