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Physics-informed neural networks for dynamic process operations with limited physical knowledge and data2024 Computers & Chemical Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access
Mehmet Velioglu, Song Zhai, Sophia Rupprecht, Alexander Mitsos, Andreas Jupke, Manuel Dahmen
54citations -
Physics-Informed Neural Networks for Dynamic Process Operations with Limited Physical Knowledge and Data2024 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access
Mehmet Velioglu, Sophia Rupprecht, Alexander Mitsos, Andreas Jupke, Manuel Dahmen
2citations -
Using physics-informed enhanced super-resolution generative adversarial networks for subfilter modeling in turbulent reactive flows2021 Proceedings of the Combustion Institute article Physics and Astronomy Model Reduction and Neural Networks Open access
Mathis Bode, Michael Gauding, Zeyu Lian, Dominik Denker, Marco Davidovic, Konstantin Kleinheinz, +2 more
150citations -
Euclid Preparation TBD. Characterization of convolutional neural networks for the identification of galaxy-galaxy strong lensing events2023 Zurich Open Repository and Archive (University of Zurich) article Physics and Astronomy Galaxies: Formation, Evolution, Phenomena Open access
Euclid Collaboration, Massimo Meneghetti, G. Angora, R. B. Metcalf, Lauro Moscardini, P. Rosati, +89 more
0citations -
Estimating Dense-Packed Zone Height in Liquid-Liquid Separation: A Physics-Informed Neural Network Approach2026 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access
Mehmet Velioglu, Song Zhai, Alexander Mitsos, Adel Mhamdi, Andreas Jupke, Manuel Dahmen
0citations