We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Background: Protein interactions support cell organization and mediate its response to any specific stimulus. Recent technological advances have produced large data-sets that aim ...
During the past decade, a number of different studies have identified several peculiar properties of networks that arise from a diverse universe, ranging from social to computer n...
Pedram Pedarsani, Daniel R. Figueiredo, Matthias G...
Reverse-engineering of gene networks using linear models often results in an underdetermined system because of excessive unknown parameters. In addition, the practical utility of ...