Homodyned K-Distribution: Parameter Estimation and Uncertainty Quantification Using Bayesian Neural Networks.
Ali Kafaei Zad TehraniIván M. Rosado-MéndezHassan RivazPublished in: ISBI (2023)
Keyphrases
- parameter estimation
- maximum likelihood
- neural network
- posterior distribution
- bayesian model selection
- least squares
- markov chain monte carlo
- gaussian distribution
- model selection
- statistical models
- decision theory
- maximum likelihood estimates
- markov random field
- approximate inference
- expectation maximization
- em algorithm
- parameter estimation algorithm
- random fields
- parameter values
- parameters estimation
- exponential family
- maximum likelihood estimation
- model fitting
- estimation problems
- experimental data
- probability distribution
- markov fields
- random variables
- gibbs sampling
- variational inference
- metropolis hastings algorithm
- hyperparameters
- bayesian inference
- maximum entropy
- posterior probability
- higher order
- bayesian networks