Improved Node and Arc Multiplicity Estimation in De Bruijn Graphs Using Approximate Inference in Conditional Random Fields.
Aranka SteyaertPieter AudenaertJan FostierPublished in: IEEE ACM Trans. Comput. Biol. Bioinform. (2023)
Keyphrases
- free energy
- approximate inference
- conditional random fields
- graph structure
- graphical models
- belief propagation
- importance sampling
- loopy belief propagation
- probabilistic model
- exact inference
- probabilistic inference
- efficient inference
- probabilistic graphical models
- factor graphs
- markov random field
- fully connected
- directed graph
- random fields
- random variables
- structured prediction
- parameter learning
- higher order
- dynamic bayesian networks
- undirected graphical models
- structure learning
- markov networks
- parameter estimation
- information extraction
- hidden markov models
- belief networks
- pairwise
- undirected graph
- markov chain monte carlo
- gaussian process
- generative model
- partition function
- bayesian networks
- bayesian framework
- labeled data
- computer vision