Raising the level of abstraction in the development of GMF-based graphical model editors.
Dimitrios S. KolovosLouis M. RoseRichard F. PaigeFiona A. C. PolackPublished in: MiSE@ICSE (2009)
Keyphrases
- graphical models
- belief propagation
- random variables
- probabilistic model
- approximate inference
- probabilistic graphical models
- probabilistic inference
- structure learning
- conditional random fields
- bayesian networks
- exact inference
- markov networks
- conditional independence
- factor graphs
- belief networks
- graph structure
- conditional dependencies
- map inference
- loopy belief propagation
- nonparametric belief propagation
- message passing
- statistical inference
- undirected graphical models
- shape model
- level set
- directed acyclic
- pairwise