BVAR-Connect: A Variational Bayes Approach to Multi-Subject Vector Autoregressive Models for Inference on Brain Connectivity Networks.
Jeong Hwan KookKelly A. VaughnDana M. DeMasterLinda Ewing-CobbsMarina VannucciPublished in: Neuroinformatics (2021)
Keyphrases
- machine learning
- variational bayes
- brain connectivity
- autoregressive model
- bayesian inference
- hyperparameters
- latent variables
- gaussian mixture model
- model selection
- free energy
- latent dirichlet allocation
- exponential family
- diffusion tensor imaging
- posterior distribution
- feature vectors
- functional connectivity
- prior information
- closed form
- cross validation
- probabilistic model
- bayesian networks
- mixture model
- log likelihood
- expectation maximization