AI RESEARCH
Learning to Solve PDEs on Neural Shape Representations
arXiv CS.LG
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ArXi:2512.21311v2 Announce Type: replace Solving partial differential equations (PDEs) on shapes underpins many shape analysis and engineering tasks; yet, prevailing PDE solvers operate on polygonal/triangle meshes while modern 3D assets increasingly live as neural representations. This mismatch leaves no suitable method to solve surface PDEs directly within the neural domain, forcing explicit mesh extraction or per-instance residual