arXiv Machine Learning By Lawrence Fulton, Christopher Fulton, Arvind Sharma, Aleksandar Tomic

Retrospective Orthogonal Design: Response-Surface Reconstruction from Observational Data

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arXiv:2607. 26219v1 Announce Type: cross Abstract: Regression estimates from observational data can depend on specification under multicollinearity, while sequential sums of squares (SS) depend on term order.

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arXiv Computer Vision
6d ago

Hierarchical Incremental Beta Splatting for Online Reconstruction

Hierarchical Incremental Beta Splatting (HIBS) introduces beta kernels into online 3D Gaussian splatting, allowing the shape parameter to interpolate between soft Gaussian-like primitives and flat-topped, near-opaque surfels. This confidence-aware spawning uses geometric observability and multi-view depth agreement to initialize opacity and shape, producing solid primitives where geometry is verifiable and soft, correctable primitives elsewhere. HIBS also employs error-driven relocation for densification, bounded beta kernel support for efficient culling and rasterization, and a shape-preserving merging formulation to create a level-of-detail hierarchy, achieving up to 0.8 dB PSNR improvement and 40 % faster optimization on the Mip-NeRF 360 dataset.

By Linus Franke