JSTOR Daily

GRAPH ESTIMATION FOR MATRIX-VARIATE GAUSSIAN DATA

Matrix-variate Gaussian graphical models (GGM) have been widely used for modeling matrix-variate data. Since the support of sparse precision matrix represents the conditional independence graph among ...
JSTOR Daily

GENERALIZED SPARSE PRECISION MATRIX SELECTION FOR FITTING MULTIVARIATE GAUSSIAN RANDOM FIELDS TO LARGE DATA SETS

We present a new method for estimating multivariate, second-order stationary Gaussian Random Field (GRF) models based on the Sparse Precision matrix Selection (SPS) algorithm, proposed by Davanloo ...
TechRepublic

Implementation of Complex Matrix Inversion Using Gauss-Jordan Elimination Method in Verilog

For high data rate wireless communications they use Orthogonal Frequency Division Multiplexing (OFDM) due to its high spectral efficiency and low computational complexity. It gives the architecture of ...
GIGAZINE

A method is developed to dramatically improve the accuracy of '3D Gaussian splitting,' which converts images into 3D

A research team from the University of British Columbia and Google has announced that they have developed a method called '3D Gaussian Splatting as a Markov Chain Monte Carlo Method' that dramatically ...