Probabilistic expert systemsbased on Bayesian networks(BNs)require initial specification both a qualitative graphical structure and quantitative assessmentof conditional probabili...
Many researchers have observed that neurons process information in an imprecise manner - if a logical inference emerges from neural computation, it is inexact at best. Thus, there...
This paper presents an approach for controlling gene networks based on a Markov chain model, where the state of a gene network is represented as a probability distribution, while ...
The Generative Topographic Mapping (GTM) was originally conceived as a probabilistic alternative to the well-known, neural networkinspired, Self-Organizing Maps. The GTM can also ...
We define a class of graphs that summarize in a compact visual way the interaction structure between binary multivariate characteristics. This allows studying the conditional depe...