Corpus ID: 3613313

Geodesic Convolutional Shape Optimization

@article{Baqu2018GeodesicCS,
  title={Geodesic Convolutional Shape Optimization},
  author={P. Baqu{\'e} and Edoardo Remelli and F. Fleuret and P. Fua},
  journal={ArXiv},
  year={2018},
  volume={abs/1802.04016}
}
  • P. Baqué, Edoardo Remelli, +1 author P. Fua
  • Published 2018
  • Computer Science, Mathematics
  • ArXiv
  • Aerodynamic shape optimization has many industrial applications. [...] Key Method The key to making this approach practical is remeshing the original shape using a polycube map, which makes it possible to perform the computations on GPUs instead of CPUs. The neural net is then used to formulate an objective function that is differentiable with respect to the shape parameters, which can then be optimized using a gradient-based technique. This outperforms state- of-the-art methods by 5 to 20% for standard…Expand Abstract
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