AMBER: Adaptive Mesh Generation by Iterative Mesh Resolution Prediction
Published in NeurIPS 2025, 2025
AMBER is a supervised learning approach to mesh adaptation. Starting from a coarse mesh, it iteratively predicts the sizing field and uses this prediction to produce new intermediate meshes, removing the need for task-specific heuristics or manual design by human experts.
Recommended citation: Niklas Freymuth, Tobias Wuerth, Nicolas Schreiber, Balazs Gyenes, Andreas Boltres, Johannes Mitsch, Aleksandar Taranovic, Tai Hoang, Philipp Dahlinger, Philipp Becker, Luise Kaerger, Gerhard Neumann. (2025). "AMBER: Adaptive Mesh Generation by Iterative Mesh Resolution Prediction." Conference on Neural Information Processing Systems (NeurIPS).
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