HilbNets define convolutions via Hilbert bundle connection Laplacians, prove that sampled Hilbert cellular sheaf Laplacians converge to the continuous operator, and show that discretized networks are consistent and transferable across samplings.
High-resolution volumetric computation of offset surfaces with feature preservation
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A finite-element method extends 2D odeco integrability to 3D surfaces to generate shear-free quadrilateral meshes with automatic singularity placement and minimized area or stretch distortion under alignment and sizing constraints.
SotA Lens introduces a network-augmented workflow that turns seed searches into citation graphs with community detection to support exploratory state-of-the-art reviews.
An output-sensitive linear-time algorithm computes the temporal α-shape α_T, a minimal encoding of all α-shapes over every time window, supporting fast interactive exploration of temporal point sets.
Method for generating minimum-weight structurally robust shell objects from 3D models using Laplacian parametrization to ensure intersection-free inner boundaries during stress-based thickness optimization.
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Consistent Geometric Deep Learning via Hilbert Bundles and Cellular Sheaves
HilbNets define convolutions via Hilbert bundle connection Laplacians, prove that sampled Hilbert cellular sheaf Laplacians converge to the continuous operator, and show that discretized networks are consistent and transferable across samplings.