Probabilistic Programming with Programmable Variational Inference.
McCoy R. BeckerAlexander K. LewXiaoyan WangMatin GhavamiMathieu HuotMartin C. RinardVikash K. MansinghkaPublished in: CoRR (2024)
Keyphrases
- variational inference
- probabilistic model
- hierarchical bayesian
- bayesian inference
- topic models
- mixture model
- variational methods
- generative model
- factor graphs
- gaussian process
- latent dirichlet allocation
- posterior distribution
- bayesian networks
- graphical models
- probabilistic graphical models
- exact inference
- closed form
- approximate inference
- language model
- posterior probability
- conditional random fields
- message passing
- text mining
- probability distribution
- machine learning