Error-Correcting Neural Networks for Semi-Lagrangian Advection in the Level-Set Method

@article{LariosCrdenas2021ErrorCorrectingNN,
  title={Error-Correcting Neural Networks for Semi-Lagrangian Advection in the Level-Set Method},
  author={Luis {\'A}ngel Larios-C{\'a}rdenas and Fr{\'e}d{\'e}ric Gibou},
  journal={J. Comput. Phys.},
  year={2021},
  volume={471},
  pages={111623}
}

Error-Correcting Neural Networks for Two-Dimensional Curvature Computation in the Level-set Method

An error-neural-modeling-based strategy for approximating two-dimensional curvature in the level-set method and introduces dimensionless parametrization and probabilistic subsampling during data production to improve the accuracy and efficiency of curvature calculations around under-resolved regions.

Machine learning algorithms for three-dimensional mean-curvature computation in the level-set method

This work develops a single pair of neural models in R 3 that can yield more accurate mean-curvature estimations in the L 1 and L ∞ norms than modern particle-based interface reconstruction and level-set schemes around under-resolved regions.

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