Quantifying the Uncertainty in Model Parameters Using Gaussian Process-Based Markov Chain Monte Carlo: An Application to Cardiac Electrophysiological Models.
Jwala DhamalaJohn L. SappB. Milan HorácekLinwei WangPublished in: CoRR (2020)
Keyphrases
- gaussian process
- markov chain monte carlo
- approximate inference
- fully bayesian
- gaussian processes
- expectation propagation
- bayesian framework
- model selection
- parameter estimation
- regression model
- posterior distribution
- generative model
- hyperparameters
- posterior probability
- markov chain
- maximum likelihood
- probabilistic model
- image reconstruction
- machine learning
- noise reduction
- semi supervised
- prior knowledge