ABS methods are direct iterative methods for solving linear systems of equations, where the i-th iteration satisfies the first i equations. Thus, a system of m equations is solved in at most m ABS iterates. In 2004 and 2007, two-step ABS methods were introduced in at most [((m+1))/2] steps to solve full row rank linear systems of equations. These methods consuming less space, are more compress ...

This paper describes aneural blind source separation (BSS) method based on amortized variational inference (AVI) of a non-linear generative model mixture signals. A classical statistical approach to BSS is fit linear that consists spatial and models representing the inter-channel covariances power spectral densities sources, respectively. Although autoencoder (VAE) has successfully been used as...

We review both full-rank and reduced-rank parameterizations for correlation matrices. In particular, the full-rank parameterizations of Rebonato (1999d) and Schoenmakers and Coffey (2000), the reduced-rank angle parameterization of Rebonato (1999d) and Rebonato and Jäckel (1999), and the well known zeroed-eigenvalues reduced-rank approximation are described in detail. Numerical examples are pro...