GINOT is a deep learning model that combines transformers with neural operators for accurate forward predictions on arbitrary 2D and 3D geometries. It processes surface point clouds using attention-based encoding with sampling and grouping, ensuring robustness to point density, order invariance, and padding resilience.
☆43Jan 20, 2026Updated 9 months ago
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