Approximate Inference for Neural Probabilistic Logic Programming.
Robin ManhaeveGiuseppe MarraLuc De RaedtPublished in: KR (2021)
Keyphrases
- logic programming
- approximate inference
- bayesian networks
- graphical models
- factor graphs
- logic programs
- probabilistic reasoning
- belief propagation
- probabilistic inference
- probabilistic model
- exact inference
- parameter estimation
- message passing
- latent variables
- gaussian process
- knowledge representation
- logic programming language
- answer set programming
- programming language
- knowledge base
- belief networks
- probabilistic graphical models
- conditional random fields
- stable models
- answer sets
- generative model
- structured prediction
- inductive logic programming
- conditional probabilities
- maximum likelihood
- least squares
- posterior probability
- pairwise
- probabilistic logic
- upper bound
- structure learning
- prior knowledge
- distributed systems
- stereo matching
- lower bound
- graph cuts
- probabilistic relational