This paper investigates the use of the Bayesian inference for devising an unsupervised sketch rendering procedure. As likelihood model of this inference, we exploit the recent sta...
Abstract. This paper studies the properties and performance of models for estimating local probability distributions which are used as components of larger probabilistic systems ā...
Kristina Toutanova, Mark Mitchell, Christopher D. ...
ā The protein structure prediction (PSP) problem is one of the most important problems in computational biology. This paper proposes a novel Estimation of Distribution Algorithms...
It is well-known that, in unidentiļ¬able models, the Bayes estimation provides much better generalization performance than the maximum likelihood (ML) estimation. However, its ac...
The coding of information by neural populations depends critically on the statistical dependencies between neuronal responses. However, there is no simple model that can simultane...