24 citations · 25 across the 2 of their papers we have counts for
3 papers
math.NA2021★ 1 cited
A Differentiable Solver Approach to Operator Inference
Dirk Hartmann, Lukas Failer
Model Order Reduction is a key technology for industrial applications in the context of digital twins. Key requirements are non-intrusiveness, physics-awareness, as well as robustn…
math.NA2021
Model Order Reduction based on Runge-Kutta Neural Network
Qinyu Zhuang, Juan Manuel Lorenzi, Hans-Joachim Bungartz +1
Model Order Reduction (MOR) methods enable the generation of real-time-capable digital twins, which can enable various novel value streams in industry. While traditional projection…
cs.LG2021★ 24 cited
Machine Learning-Based Optimal Mesh Generation in Computational Fluid Dynamics
Keefe Huang, Moritz Krügener, Alistair Brown +3
Computational Fluid Dynamics (CFD) is a major sub-field of engineering. Corresponding flow simulations are typically characterized by heavy computational resource requirements. Oft…