Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons.
Dejan PecevskiLars BuesingWolfgang MaassPublished in: PLoS Comput. Biol. (2011)
Keyphrases
- graphical models
- probabilistic inference
- spiking neurons
- belief propagation
- approximate inference
- probabilistic networks
- random variables
- probabilistic model
- bayesian networks
- probabilistic graphical models
- influence diagrams
- exact inference
- markov networks
- conditional random fields
- bayesian belief networks
- factor graphs
- conditional independence
- probabilistic reasoning
- belief networks
- spiking neural networks
- message passing
- junction tree
- conditional probabilities
- distributed systems
- neural network model
- loopy belief propagation