[2607.23437] Neural Representation of Minimal Surfaces
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arXiv:2607.23437 (cs)
[Submitted on 26 Jul 2026]
Title:Neural Representation of Minimal Surfaces
Authors:Jiayin Sun, Albert Chern<br>View a PDF of the paper titled Neural Representation of Minimal Surfaces, by Jiayin Sun and 1 other authors
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Abstract:We propose a neural representation for minimal surfaces. Unlike prior approaches based on discretization or Physics-Informed Neural Networks (PINNs), where meshes or neural fields are optimized to approximate the governing equations, our method builds on an exact representation, similar to the classical Weierstrass--Enneper parameterization, yielding minimal surfaces up to negligible quadrature error in evaluation. We formulate a training objective for the Plateau problem that optimizes over this representation.
Comments:<br>11 pages, 11 figures
Subjects:
Graphics (cs.GR); Machine Learning (cs.LG)
Cite as:<br>arXiv:2607.23437 [cs.GR]
(or<br>arXiv:2607.23437v1 [cs.GR] for this version)
https://doi.org/10.48550/arXiv.2607.23437
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arXiv-issued DOI via DataCite (pending registration)
Submission history<br>From: Jiayin Sun [view email]<br>[v1]<br>Sun, 26 Jul 2026 03:26:42 UTC (34,480 KB)
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