2024/11/09 by Xinran Liu, Yikun Bai, Liu, Xinran +13 · 2 citations
Computer Science · #Computational Geometry and Mesh Generation #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Metric Geometry (math.MG)
paper · doi:10.48550/arxiv.2411.06055
openalex publication_date 2024/11/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
spaces while preserving their intrinsic geometry, offering a computationally efficient metric for spherical probability measures. We establish the metricity of LSSOT and demonstrate its superior computational efficiency in applications such as cortical surface registration, 3D point cloud interpolation via gradient flow, and shape embedding. Our results demonstrate the significant computational benefits and high accuracy of LSSOT in these applications.