This paper presents a new approach to inference in Bayesian networks. The principal idea is to encode the network by logical sentences and to compile the resulting encoding into an...
Bayesian MLP neural networks are a flexible tool in complex nonlinear problems. The approach is complicated by need to evaluate integrals over high-dimensional probability distri...
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...
This paper makes an intensive investigation of the application of Bayesian network in sentence retrieval and introduces three Bayesian network based sentence retrieval models with...
Keke Cai, Jiajun Bu, Chun Chen, Kangmiao Liu, Wei ...