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ORCIDNikolaj Takata Mücke
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2020 – today
- 2024
[b1]Nikolaj Takata Mücke:
Deep Learning for Real-Time Inverse Problems and Data Assimilation with Uncertainty Quantification for Digital Twins. Utrecht University, Netherlands, 2024- [i3]Nikolaj Takata Mücke, Sander M. Bohté, Cornelis W. Oosterlee:
The Deep Latent Space Particle Filter for Real-Time Data Assimilation with Uncertainty Quantification. CoRR abs/2406.02204 (2024) - 2023
- [j3]Nikolaj Takata Mücke
, Benjamin Sanderse, Sander M. Bohté, Cornelis W. Oosterlee:
Markov chain generative adversarial neural networks for solving Bayesian inverse problems in physics applications. Comput. Math. Appl. 147: 278-299 (2023) - [j2]Nikolaj Takata Mücke, Prerna Pandey, Shashi Jain, Sander M. Bohté, Cornelis W. Oosterlee:
A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning. Sensors 23(13): 6179 (2023) - 2021
- [j1]Nikolaj Takata Mücke, Sander M. Bohté, Cornelis W. Oosterlee:
Reduced order modeling for parameterized time-dependent PDEs using spatially and memory aware deep learning. J. Comput. Sci. 53: 101408 (2021) - [i2]Nikolaj Takata Mücke, Benjamin Sanderse, Sander M. Bohté, Cornelis W. Oosterlee:
Markov Chain Generative Adversarial Neural Networks for Solving Bayesian Inverse Problems in Physics Applications. CoRR abs/2111.12408 (2021) - 2020
- [i1]Nikolaj Takata Mücke, Sander M. Bohté, Cornelis W. Oosterlee:
Reduced Order Modeling for Parameterized Time-Dependent PDEs using Spatially and Memory Aware Deep Learning. CoRR abs/2011.11327 (2020)
2010 – 2019
- 2019
- [c1]Nikolaj Takata Mücke, Lasse Hjuler Christiansen, Allan Peter Engsig-Karup, John Bagterp Jørgensen:
Reduced Order Modeling for Nonlinear PDE-constrained Optimization using Neural Networks. CDC 2019: 4267-4272
Coauthor Index
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