A residual-based a posteriori estimator is used as a differentiable loss to train a neural network that relocates IGA knots, with a density output that works at any refinement level.
A posteriori error estimation of residual type for anisotropic diffusion-convection-reaction problems
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Parametric Neural r-Adaptivity for Isogeometric Analysis via Residual Minimization
A residual-based a posteriori estimator is used as a differentiable loss to train a neural network that relocates IGA knots, with a density output that works at any refinement level.