GANO unifies shape encoding with auto-decoders, denoising-stabilized latent optimization, and geometry-injected surrogates into an end-to-end differentiable pipeline for PDE-governed shape optimization and inversion.
arXiv preprint arXiv:2602.03582 , year=
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Geometry-Aware Neural Optimizer for Shape Optimization and Inversion
GANO unifies shape encoding with auto-decoders, denoising-stabilized latent optimization, and geometry-injected surrogates into an end-to-end differentiable pipeline for PDE-governed shape optimization and inversion.