A latent variable-based Bayesian regression to address recording replications in Parkinson's Disease.
Carlos J. PérezLizbeth NaranjoJacinto MartínYolanda Campos-RocaPublished in: EUSIPCO (2014)
Keyphrases
- latent variables
- posterior distribution
- gaussian process
- gaussian processes
- probabilistic model
- latent variable models
- regression model
- sparse bayesian learning
- topic models
- random variables
- bayesian networks
- prior knowledge
- real valued
- hierarchical model
- active learning
- databases
- latent structure
- data analysis
- hidden variables
- natural language processing
- model selection
- maximum likelihood
- graphical models
- bayesian inference
- posterior probability
- probability distribution
- structured prediction
- relevance vector machine
- observed variables