Autoencoder networks extract latent variables and encode these variables in their connectomes.
Matthew FarrellStefano RecanatesiR. Clay ReidStefan MihalasEric Shea-BrownPublished in: Neural Networks (2021)
Keyphrases
- latent variables
- random variables
- observed variables
- hidden variables
- factor graphs
- probabilistic model
- causal relationships
- posterior distribution
- structural model
- hierarchical model
- real valued
- latent variable models
- prior knowledge
- gaussian process
- topic models
- variational bayes
- observational data
- structural svms
- social networks
- causal models
- probability distribution
- bayesian networks
- approximate inference
- latent factors
- information retrieval
- probabilistic graphical models
- hidden layer
- conditional probability distributions
- structured prediction
- exact inference
- training data
- image segmentation