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A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains2024 Engineering With Computers article Physics and Astronomy Model Reduction and Neural Networks Open access
Yusuke Yamazaki, Mayu Muramatsu, Alexandre Viardin, Markus Apel, Tim Brepols, Stefanie Reese, +1 more
47citations -
Recurrent and convolutional neural networks in structural dynamics: a modified attention steered encoder–decoder architecture versus LSTM versus GRU versus TCN topologies to predict the response of shock wave-loaded plates31citations
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Influence of adversarial training on super-resolution turbulence reconstruction2024 Physical Review Fluids article Physics and Astronomy Model Reduction and Neural Networks Open access
Ludovico Nista, Heinz G. Pitsch, Christoph Schumann, Mathis Bode, Temistocle Grenga, Jonathan F. MacArt, +1 more
26citations -
Prediction of Acoustic Fields Using a Lattice-Boltzmann Method and Deep Learning2020 Lecture notes in computer science conference-paper Physics and Astronomy Model Reduction and Neural Networks Open access
Mario Rüttgers, Seong Ryong Koh, Jenia Jitsev, Wolfgang Schröder, Andreas Lintermann
7citations -
Influence of adversarial training on super-resolution turbulence reconstruction2023 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access
Ludovico Nista, Christoph Schumann, Mathis Bode, Temistocle Grenga, Jonathan F. MacArt, Antonio Attili, +1 more
0citations