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A physics-informed meta-learning framework for the continuous solution of parametric PDEs on arbitrary geometries2026 Computers & Structures article Physics and Astronomy Model Reduction and Neural Networks Open access
Reza Najian Asl, Yusuke Yamazaki, Kianoosh Taghikhani, Mayu Muramatsu, Markus Apel, Shahed Rezaei
4citations -
Applying physics-informed enhanced super-resolution generative adversarial networks to turbulent premixed combustion and engine-like flame kernel direct numerical simulation data2023 Proceedings of the Combustion Institute article Physics and Astronomy Model Reduction and Neural Networks Open access
Mathis Bode, Michael Gauding, Dominik Goeb, Tobias Falkenstein, Heinz G. Pitsch
31citations -
A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary Geometries2025 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access
Reza Najian Asl, Yusuke Yamazaki, Kianoosh Taghikhani, Mayu Muramatsu, Markus Apel, Shahed Rezaei
1citations -
Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Turbulent Premixed Combustion and Engine-like Flame Kernel Direct Numerical Simulation Data2022 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access
Mathis Bode, Michael Gauding, Dominik Goeb, Tobias Falkenstein, Heinz G. Pitsch
0citations
9 results