Symbolic Exact Inference for Discrete Probabilistic Programs.

Steven Holtzen Todd D. Millstein Guy Van den Broeck

Published in: CoRR (2019)

Keyphrases

exact inference
bayesian networks
belief networks
discrete variables
graphical models
approximate inference
probabilistic inference
probabilistic model

inference in bayesian networks
conditional probabilities
belief propagation
structured prediction
dynamic bayesian networks
posterior probability
parameter estimation
latent variables

conditional random fields
approximation algorithms
probability distribution
conditional independence
random variables
generative model
structure learning
continuous variables

learning algorithm
feature space
lower bound
prior knowledge
gaussian process
message passing
machine learning