Efficient computation of the maximum a posteriori path and parameter estimation in integrate-and-fire and more general state-space models.
Shinsuke KoyamaLiam PaninskiPublished in: J. Comput. Neurosci. (2010)
Keyphrases
- parameter estimation
- markov random field
- maximum a posteriori
- maximum likelihood
- efficient computation
- em algorithm
- expectation maximization
- posterior distribution
- random fields
- state space
- model selection
- map estimation
- least squares
- hyperparameters
- bayesian framework
- energy function
- probabilistic model
- higher order
- parameter estimation algorithm
- belief propagation
- graph cuts
- pairwise
- markov chain monte carlo
- parameter estimates
- image segmentation
- approximate inference
- image reconstruction
- mrf model
- image restoration
- reinforcement learning
- prior model
- computational efficiency
- conditional random fields
- generative model
- feature space