Who knows more about soccer? Us ‘experts’, you the subscribers, a child, a dog or an algorithm? Come join us to predict each ...

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

Abstract: This paper introduces an expectation-maximization (EM) algorithm for image restoration (deconvolution) based on a penalized likelihood formulated in the wavelet domain. Regularization is ...

Creating a highly accurate geological model at a large scale presents a considerable challenge, primarily due to constraints imposed by sparse data availability. A promising strategy to mitigate these ...

y_i -- the (n_i x 1) vector of responses for cluster i. These are given at at training. X_i -- the (n_i x p) fixed effects covariates that are associated with the y_i. These are given at training. Z_i ...

Division of Intramural Research, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, United States ...

Below we have compiled a full list of Google algorithm launches, updates, and refreshes that have rolled out over the years, as well as links to resources for SEO professionals who want to understand ...

In this study, we present a novel and robust methodology for the automatic detection of influenza A virus ribonucleoproteins (RNPs) in single-particle cryo-electron microscopy (cryo-EM) images.

ABSTRACT: This paper is concerned about studying modeling-based methods in cluster analysis to classify data elements into clusters and thus dealing with time series in view of this classification to ...