Reduced order modeling for parameterized time-dependent PDEs using spatially and memory aware deep learning NT Mücke, SM Bohté, CW Oosterlee Journal of Computational Science 53, 101408, 2021 | 39 | 2021 |
Reduced Order Modeling for Nonlinear PDE-constrained Optimization using Neural Networks NT Mücke, LH Christiansen, AP Karup-Engsig, JB Jørgensen 2019 IEEE 58th Conference on Decision and Control (CDC), 2019 | 5 | 2019 |
Markov chain generative adversarial neural networks for solving Bayesian inverse problems in physics applications NT Mücke, B Sanderse, SM Bohté, CW Oosterlee Computers & Mathematics with Applications 147, 278-299, 2023 | 4 | 2023 |
A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning NT Mücke, P Pandey, S Jain, SM Bohté, CW Oosterlee Sensors 23 (13), 6179, 2023 | 2 | 2023 |
Reduced Order Modelling for Dispersive and Nonlinear Water Wave Modelling FG Eroglu, NT Mücke, AP Engsig-Karup 37th International Workshop on Water Waves and Floating Bodies, 2022 | 2 | 2022 |
AI enhanced data assimilation and uncertainty quantification applied to Geological Carbon Storage GS Seabra, NT Mücke, VLS Silva, D Voskov, F Vossepoel arXiv preprint arXiv:2402.06110, 2024 | | 2024 |
Reduced Order Modelling for Wave-Structure Modelling FG Eroglu, NT Mücke, J Visbech, AP Engsig-Karup 22nd IACM Computational Fluids Conference, 2022 | | 2022 |