A holistic similarity measure for GMMs by embedding it into the manifold of SPD matrices
In this paper, a new similarity measure for comparing two Gaussian Mixture Models (GMMs) is obtained. This is based on an embedding of the manifold of K-component GMMs into the manifold of the symmetric positive definite matrices (SPD). The GMM manifold with the pullback of the induced metric is sho...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Artigo |
| Language: | Inglês |
| Published: |
Taylor & Francis Group
2026-12-01
|
| Series: | Applied Mathematics in Science and Engineering |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/27690911.2026.2629491 |
| Tags: |
No Tags, Be the first to tag this record!
|