A Wasserstein-type distance for Gaussian mixtures on vector bundles with applications to shape analysis
From MaRDI portal
Publication:6587652
DOI10.1137/23m1620363zbMATH Open1543.62677MaRDI QIDQ6587652
Chiwoo Park, Michael J. Wilson, Tom Needham, Anuj Srivastava, Suparteek Kundu
Publication date: 14 August 2024
Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)
Statistics on manifolds (62R30) Geometric probability and stochastic geometry (60D05) Applications of differential geometry to data and computer science (53Z50)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- On the geometry of graph spaces
- Functional and shape data analysis
- Energy statistics: a class of statistics based on distances
- Non-Euclidean statistics for covariance matrices, with applications to diffusion tensor imaging
- A class of Wasserstein metrics for probability distributions
- The Frechet distance between multivariate normal distributions
- A convexity principle for interacting gases
- Rate-invariant analysis of covariance trajectories
- The statistical theory of shape
- A linear optimal transportation framework for quantifying and visualizing variations in sets of images
- Statistical shape analysis of brain arterial networks (BAN)
- Framing 3-manifolds with bare hands
- Diffusion \(K\)-means clustering on manifolds: provable exact recovery via semidefinite relaxations
- Random Triangles and Polygons in the Plane
- On the parallelizability of the spheres
- A Wasserstein-Type Distance in the Space of Gaussian Mixture Models
- Shape Manifolds, Procrustean Metrics, and Complex Projective Spaces
- Discriminating Between the Von Mises and Wrapped Normal Distributions
- Characteristic Classes. (AM-76)
- A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data
- On the Identifiability of Finite Mixtures
- On Wasserstein geometry of the space of Gaussian measures
- Optimal Transport
- Shapes and diffeomorphisms
- Elastic Metrics on Spaces of Euclidean Curves: Theory and Algorithms
- Radiologic image-based statistical shape analysis of brain tumours
This page was built for publication: A Wasserstein-type distance for Gaussian mixtures on vector bundles with applications to shape analysis