Foundation Posteriors for Approximate Probabilistic Inference.
Mike WuNoah D. GoodmanPublished in: NeurIPS (2022)
Keyphrases
- probabilistic inference
- graphical models
- bayesian networks
- junction tree
- influence diagrams
- conditional probabilities
- weighted model counting
- context specific independence
- belief networks
- bayesian belief networks
- message passing
- efficient inference
- approximate inference
- elimination algorithm
- bucket elimination
- posterior probability
- belief propagation
- random variables
- markov networks
- domain knowledge
- variable elimination
- image segmentation
- data sets
- small number
- data points
- exact inference
- classification accuracy
- feature vectors
- feature space
- neural network