On the relationship between deterministic and probabilistic directed Graphical models: From Bayesian networks to recursive neural networks.
Pierre BaldiMichal Rosen-ZviPublished in: Neural Networks (2005)
Keyphrases
- bayesian networks
- directed graphical models
- recursive neural networks
- graphical models
- machine learning
- neural network
- probabilistic model
- posterior probability
- structure learning
- conditional random fields
- gesture recognition
- conditional probabilities
- probabilistic inference
- probability distribution
- undirected graphical models
- dynamic bayesian networks
- belief propagation
- random variables
- hidden variables
- approximate inference
- conditional independence
- parameter learning
- probabilistic graphical models
- support vector machine
- belief networks
- markov networks
- higher order
- feature space