32 search results - page 2 / 7 » The Representational Power of Discrete Bayesian Networks |
NECO
2008
13 years 5 months ago
2008
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
GCB
2004
Springer
13 years 10 months ago
2004
Springer
: The prediction of transcription factor binding sites is an important problem, since it reveals information about the transcriptional regulation of genes. A commonly used represen...
JMLR
2010
13 years 3 days ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
BMCBI
2008
13 years 5 months ago
2008
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
AAAI
2008
13 years 7 months ago
2008
Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...