Guaranteed bounds for posterior inference in universal probabilistic programming.

Raven Beutner C.-H. Luke Ong Fabian Zaiser

Published in: PLDI (2022)

Keyphrases

posterior probability
bayesian networks
probabilistic model
belief networks
inference process
probabilistic reasoning
lower bound
upper bound
markov chain monte carlo methods

bayesian inference
probability distribution
programming language
logical inference
probabilistic networks
markov chain monte carlo
variable elimination
bayes nets
lower and upper bounds

programming environment
factor graphs
upper and lower bounds
bayesian model
probabilistic logic
probabilistic inference
inference mechanism
probabilistic modeling
generative model

object oriented
independence assumption
posterior distribution
first order logic
marginal probabilities
graphical models
bayesian reasoning
optimal solution