A bayesian recurrent neural network for unsupervised pattern recognition in large incomplete data sets.
Roland OrreAndrew BateG. Niklas NorénErik SwahnStefan ArnborgI. Ralph EdwardsPublished in: Int. J. Neural Syst. (2005)
Keyphrases
- recurrent neural networks
- pattern recognition
- incomplete data sets
- neural network
- incomplete data
- missing values
- data driven
- data sets
- feed forward
- bayesian networks
- feedforward neural networks
- complex valued
- unsupervised learning
- echo state networks
- neural model
- missing data
- maximum likelihood
- recurrent networks
- hidden layer
- artificial neural networks
- reservoir computing
- image processing
- signal processing
- computer vision
- supervised learning
- machine learning
- semi supervised
- long short term memory
- bayesian inference
- back propagation
- fuzzy sets
- feature extraction
- dimensionality reduction
- neural network structure
- decision making
- em algorithm
- fuzzy logic
- nonlinear dynamic systems
- artificial intelligence