Correctness of Sequential Monte Carlo Inference for Probabilistic Programming Languages.
Daniel LundénJohannes BorgströmDavid BromanPublished in: CoRR (2020)
Keyphrases
- programming language
- sequential monte carlo
- bayesian networks
- belief networks
- object oriented
- general purpose
- inference process
- strongly typed
- particle filter
- software engineering
- visual tracking
- high level
- logic programming
- database languages
- programming environment
- lambda calculus
- denotational semantics
- particle filtering
- probabilistic inference
- specification language
- generative model
- object oriented concepts
- high level programming language
- databases
- posterior distribution
- probabilistic model
- spatio temporal
- image sequences
- conditional probabilities
- xml documents
- artificial intelligence
- database
- programming language constructs