Low-rank multi-parametric covariance identification
We propose a differential geometric approach for building families of low-rank covariance matrices, via interpolation on low-rank matrix manifolds. In contrast with standard parametric covariance classes, these families offer significant flexibility for problem-specific tailoring via the choice of “...
Main Authors: | Musolas, A, Massart, EM, Hendrickx, JM, Absil, P-A, Marzouk, Y |
---|---|
Format: | Journal article |
Language: | English |
Published: |
Springer
2021
|
Similar Items
-
Low-rank multi-parametric covariance identification
by: Musolas, Antoni, et al.
Published: (2022) -
Low-rank multi-parametric covariance identification
by: Musolas, Antoni, et al.
Published: (2022) -
Geodesically Parameterized Covariance Estimation
by: Musolas, Antoni, et al.
Published: (2022) -
Covariance estimation on matrix manifolds
by: Musolas Otaño, Antoni M.(Antoni Maria)
Published: (2020) -
Covariant approach to parametrized cosmological perturbations
by: Tattersall, O, et al.
Published: (2017)