To define a likelihood we have to specify the form of distribution of the observations, but to define a quasi-likelihood function we need only specify a relation between the mean and variance of the ...

In this work, we describe the development of a new algorithm for the computation of Coulomb-type matrices using the well-known resolution of the identity (RI) or density fitting (DF) approximation.

This paper proposes a method based on the separability and semigroup properties of the Gaussian function, combined with linear texture filtering, to extract and process texture information, which can ...

Abstract: Artificial neural networks (ANNs) rely significantly on activation functions for optimal performance. Traditional activation functions such as ReLU and Sigmoid are commonly used. However, ...

A simple matrix formula is given for the observed information matrix when the EM algorithm is applied to categorical data with missing values. The formula requires only the design matrices, a matrix ...