In this paper we show that generative models are competitive with and sometimes superior to discriminative models, when both kinds of models are allowed to learn structures that a...
This work present the use of a neural structure to augment the quality of noisy images of liquid bridges to obtain a clear representation of its border in order to determine the ac...
We investigate the use of an unsupervised artificial neural network to form a sparse representation of the underlying causes in a data set. By using fixed lateral connections that...
In this paper, we propose a novel method for generating engaging multi-modal content automatically from text. Rhetorical Structure Theory (RST) is used to decompose text into disc...
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...