GSHAC performs exact HAC on large geographic point sets by building a sparse geodesic graph and proving that connected-component subproblems yield identical results to the dense algorithm for all standard linkages at cut heights below the sparsity threshold.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
GaussianHSI uses Voronoi-guided bilateral 2D Gaussian splatting plus a spectral detail enhancement module to perform arbitrary-scale hyperspectral image super-resolution.
citing papers explorer
-
Scalable Exact Hierarchical Agglomerative Clustering via Sparse Geographic Distance Graphs
GSHAC performs exact HAC on large geographic point sets by building a sparse geodesic graph and proving that connected-component subproblems yield identical results to the dense algorithm for all standard linkages at cut heights below the sparsity threshold.
-
Voronoi-guided Bilateral 2D Gaussian Splatting for Arbitrary-Scale Hyperspectral Image Super-Resolution
GaussianHSI uses Voronoi-guided bilateral 2D Gaussian splatting plus a spectral detail enhancement module to perform arbitrary-scale hyperspectral image super-resolution.