IEEE

Shrinking the Eigenvalues of M-Estimators of Covariance Matrix

Abstract: A highly popular regularized (shrinkage) covariance matrix estimator is the shrinkage sample covariance matrix (SCM) which shares the same set of eigenvectors as the SCM but shrinks its ...
GitHub

ViViT: Curvature access through the generalized Gauss-Newton's low-rank structure

ViViT is a collection of numerical tricks to efficiently access curvature from the generalized Gauss-Newton (GGN) matrix based on its low-rank structure. Provided functionality includes computing ...
GitHub

Machine learning workflow of convolutional autoencoder and random forest to identify seismic facies and predict sandstone thickness distribution.

1.make-dataset.py make seismic data converted to a gray-scale image and the gray-scale image is split into patches by the given patch cell. 2.CAEL1.py make patches split into training and test sets ...
IEEE

Improved Estimation of Eigenvalues and Eigenvectors of Covariance Matrices Using Their Sample Estimates

Abstract: The problem of estimating the eigenvalues and eigenvectors of the covariance matrix associated with a multivariate stochastic process is considered. The focus is on finite sample size ...