8 papers
Cluster-Aware Matching via Laplacian Optimal Transport
Gabriel Samberg, YoonHaeng Hur, Yuehaw Khoo +1
In many applications of matching, the point clouds to be matched are not merely unstructured sets of points but rather samples from distributions with an intrinsic cluster structur…
Subdivision Schemes in Metric Spaces
Nira Dyn, Nir Sharon
We develop a unified framework for nonlinear subdivision schemes on complete metric spaces (CMS). We begin with CMS preliminaries and formalize refinement in CMS, retaining key str…
Anchor-Based Function Extrapolation with Proven Bounds and Projection Guarantees
Guy Hay, Nir Sharon
Classical approximation and learning methods are typically optimized for interpolation over a sampled domain Ω, with no guarantees on their behavior in an extrapolation region Î,…
Provable orbit recovery over SO(3) from the non-uniform second moment
Tamir Bendory, Dan Edidin, Josh Katz +2
We study the recovery of an unknown three-dimensional band-limited signal from multiple noisy observations that are randomly rotated by latent elements of SO(3), where the rotation…
SO(3)-invariant PCA with application to molecular data
Michael Fraiman, Paulina Hoyos, Tamir Bendory +4
Principal component analysis (PCA) is a fundamental technique for dimensionality reduction and denoising; however, its application to three-dimensional data with arbitrary orientat…
Multiscale analysis via pseudo-reversing and applications to manifold-valued sequences
Wael Mattar, Nir Sharon
Modeling data using manifold values is a powerful concept with numerous advantages, particularly in addressing nonlinear phenomena. This approach captures the intrinsic geometric s…