Bio-PINNs with a near-to-far curriculum and deformation-uncertainty proxy recover cell-induced densified phases and tether morphologies more reliably than standard adaptive PINN baselines in single-cell and multicellular settings.
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Smoothing iterations on finite element solutions in an enriched space produce superconvergent approximations for symmetric positive definite problems.
citing papers explorer
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Cell-induced densification and tether formation in fibrous extracellular matrices with biomimetic physics-informed neural networks
Bio-PINNs with a near-to-far curriculum and deformation-uncertainty proxy recover cell-induced densified phases and tether morphologies more reliably than standard adaptive PINN baselines in single-cell and multicellular settings.
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Superconvergence in finite element method by smoothing
Smoothing iterations on finite element solutions in an enriched space produce superconvergent approximations for symmetric positive definite problems.