A DeepONet trained on LAMMPS platelet simulations reproduces time-resolved platelet deformation with sub-1% median error and extends with under 8% maximum error to held-out stiffness extremes.
Learning nonlinear operators via deeponet based on the uni- versal approximation theorem of operators.Nature machine intelligence, 3(3):218–229, 2021
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A Neural-Operator Surrogate for Platelet Deformation Across Capillary Numbers
A DeepONet trained on LAMMPS platelet simulations reproduces time-resolved platelet deformation with sub-1% median error and extends with under 8% maximum error to held-out stiffness extremes.