Implicit Variational Inference for High-Dimensional Posteriors.
Anshuk UppalKristoffer Stensbo-SmidtWouter BoomsmaJes FrellsenPublished in: NeurIPS (2023)
Keyphrases
- variational inference
- bayesian inference
- high dimensional
- posterior distribution
- probabilistic model
- probability distribution
- hyperparameters
- latent variables
- markov networks
- probabilistic graphical models
- dimensionality reduction
- topic models
- posterior probability
- parameter space
- hidden variables
- bayesian framework
- mixture model
- gaussian process
- gaussian distribution
- variational methods
- maximum a posteriori
- high dimensional data
- parameter estimation
- low dimensional
- prior information
- latent dirichlet allocation
- feature space
- exponential family
- prior knowledge
- markov chain monte carlo
- particle filter
- metric space
- bayesian networks
- least squares
- information extraction
- maximum likelihood
- factor graphs
- regression model