Positive definite matrices and the S-divergence

By Suvrit Sra. 2011

136 citations recorded by the source corpus.

Subfields: Applied Mathematics, Computational Mechanics, Numerical Analysis

View Paper: https://www.semanticscholar.org/paper/e4bad5b78fd5b24a2976bcba7074d58b6dbf89ad

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Applied Mathematics

1. Zhiwu Huang
2. Luc Van Gool

In Computational Mechanics

1. Zhiwu Huang
2. Luc Van Gool
3. Radu Timofte
4. Chen Change Loy

In Numerical Analysis

1. Zhiwu Huang
2. Luc Van Gool

Citations in the corpus

• A Riemannian Network for SPD Matrix Learning (2016, methodology): “To address this problem, (Pennec, Fillard, and Ayache 2006; Arsigny et al. 2007; Sra 2011) introduced Riemannian metrics, e.g., Log-Euclidean metric (Arsigny et al. 2007), to encode Riemannian geometry of SPD manifolds properly.”
• Riemannian Approaches in Brain-Computer Interfaces: A Review (2017, unknown): “with some Riemannian distances like the AIRM distance [63] but compatible with others [64], [65].”