Stochastic Back-propagation and Variational Inference in Deep Latent Gaussian Models.
Danilo Jimenez RezendeShakir MohamedDaan WierstraPublished in: CoRR (2014)
Keyphrases
- back propagation
- gaussian model
- factor graphs
- mixture model
- artificial neural networks
- neural network
- latent variables
- learning algorithm
- fuzzy logic
- expectation maximization
- probabilistic model
- image intensity
- multilayer perceptron
- conditional independence
- gaussian mixture model
- exact inference
- gaussian process
- bayesian inference
- gaussian distribution
- approximate inference
- graphical models
- closed form
- belief propagation
- topic models
- feature extraction
- skin color
- computer vision
- probabilistic graphical models
- artificial intelligence