Accounting for Input Noise in Gaussian Process Parameter Retrieval.
Juan Emmanuel JohnsonValero LaparraGustau Camps-VallsPublished in: IEEE Geosci. Remote. Sens. Lett. (2020)
Keyphrases
- gaussian process
- gaussian processes
- hyperparameters
- noise level
- regression model
- approximate inference
- model selection
- gaussian process regression
- bayesian framework
- input data
- semi supervised
- gaussian process classification
- expectation propagation
- information retrieval
- latent variables
- noise reduction
- noise model
- covariance function
- marginal likelihood
- gaussian process models
- sparse approximations
- signal to noise ratio
- missing data
- noisy images
- closed form
- maximum likelihood
- support vector
- machine learning
- bayesian inference
- data sets
- prior information
- cross validation
- error rate
- higher order
- upper bound
- training data