Approximate Inference in Probabilistic Answer Set Programming for Statistical Probabilities.
Damiano AzzoliniElena BellodiFabrizio RiguzziPublished in: AI*IA (2022)
Keyphrases
- answer set programming
- approximate inference
- graphical models
- belief networks
- probabilistic inference
- bayesian networks
- factor graphs
- conditional probabilities
- belief propagation
- exact inference
- logic programs
- logic programming
- probabilistic model
- answer sets
- message passing
- parameter estimation
- probabilistic graphical models
- latent variables
- gaussian process
- loopy belief propagation
- answer set programs
- conditional random fields
- probability distribution
- dynamic bayesian networks
- random variables
- free energy
- expectation propagation
- posterior probability
- generative model
- graph cuts
- structured prediction
- information retrieval
- machine learning
- noise level
- markov random field
- knowledge representation
- prior knowledge
- pairwise