Numerical Issues in Maximum Likelihood Parameter Estimation for Gaussian Process Interpolation.
Subhasish BasakSébastien PetitJulien BectEmmanuel VázquezPublished in: LOD (2021)
Keyphrases
- parameter estimation
- maximum likelihood
- gaussian process
- hyperparameters
- model selection
- likelihood function
- gaussian processes
- approximate inference
- em algorithm
- gaussian process regression
- posterior distribution
- maximum a posteriori
- bayesian framework
- expectation maximization
- maximum likelihood estimation
- statistical models
- regression model
- latent variables
- parameter values
- parameter estimation algorithm
- cross validation
- semi supervised
- random fields
- covariance matrices
- gaussian distribution
- structure learning
- probabilistic model
- generative model
- gaussian mixture model
- markov chain monte carlo
- bayesian networks
- parameter estimates
- variational inference
- graphical models
- exponential family
- feature selection
- machine learning