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Exploring Neural Network Surrogates for High-Order Mesh-Free Interpolants
arXiv:2503.23230v3 Announce Type: replace Abstract: Mesh-free numerical methods offer flexibility in the discretisation of complex geometries, showing significant potential for problems where mesh-based methods struggle. Although high-order approximations can be obtained through consistency-correction linear systems, such approaches remain prohibitively expensive for Lagrangian formulations, which commonly exhibit low-order convergence. Here we investigate the use of machine learning (ML) to...