Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints.
Stefan HabenschussJohannes BillBernhard NesslerPublished in: NIPS (2012)
Keyphrases
- expectation maximization
- spiking neural networks
- posterior distribution
- posterior probability
- em algorithm
- feed forward
- probabilistic model
- spiking neurons
- biologically inspired
- parameter estimation
- maximum likelihood
- probability density function
- bayesian framework
- bayesian networks
- learning rules
- gaussian mixture model
- spike trains
- latent variables
- generative model
- biologically plausible
- maximum a posteriori
- neuron model
- computer vision
- artificial neural networks
- markov chain monte carlo
- probability distribution
- mixture model
- bayesian methods
- prior distribution
- bio inspired
- constrained optimization
- graphical models
- neural network model