Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
al Partitioning by Predicate Abstraction and its Application to Data Warehouse Design Aleksandar Dimovski1 , Goran Velinov2 , and Dragan Sahpaski2 1 Faculty of Information-Communic...
Aleksandar Dimovski, Goran Velinov, Dragan Sahpask...
Background: Chromosomal replication is the central event in the bacterial cell cycle. Identification of replication origins (oriCs) is necessary for almost all newly sequenced bac...
Many categories of objects, such as human faces, can be naturally viewed as a composition of several different layers. For example, a bearded face with glasses can be decomposed i...