Encoding Probabilistic Graphical Models into Stochastic Boolean Satisfiability.
Cheng-Han HsiehJie-Hong R. JiangPublished in: IJCAI (2022)
Keyphrases
- probabilistic graphical models
- boolean satisfiability
- graphical models
- sat solvers
- probabilistic planning
- integer linear programming
- sat problem
- markov networks
- randomly generated
- branch and bound algorithm
- symmetry breaking
- exact inference
- belief propagation
- first order logic
- latent variables
- phase transition
- max sat
- approximate inference
- probabilistic inference
- orders of magnitude
- constraint satisfaction problems
- conditional random fields
- sat instances
- belief functions
- combinatorial problems
- parameter learning
- global constraints
- structure learning
- inductive logic programming
- fuzzy measures
- constraint programming
- graph cuts
- maximum likelihood