24 citations · 25 across the 4 of their papers we have counts for
3 papers · 1 filter
Operator inference with roll outs for learning reduced models from scarce and low-quality data
Wayne Isaac Tan Uy, Dirk Hartmann, Benjamin Peherstorfer
Data-driven modeling has become a key building block in computational science and engineering. However, data that are available in science and engineering are typically scarce, oft…
Active-learning-based non-intrusive Model Order Reduction
Qinyu Zhuang, Dirk Hartmann, Hans Joachim Bungartz +1
The Model Order Reduction (MOR) technique can provide compact numerical models for fast simulation. Different from the intrusive MOR methods, the non-intrusive MOR does not require…
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…