Manual
manual
manual
User Manual:
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Page Count: 51
- Gaussian Process Training and Prediction
- The gp Function
- Inference Methods
- Exact Inference with Gaussian likelihood
- Laplace's Approximation
- Expectation Propagation
- Kullback Leibler Divergence Minimisation
- Variational Bayes
- Compatibility Between Inference Methods and Covariance Approximations
- Sparse Covariance Approximations
- Grid-Based Covariance Approximations
- State Space Representation of GPs
- Likelihood Functions
- Prediction
- Interface
- Implemented Likelihood Functions
- Usage of Implemented Likelihood Functions
- Compatibility Between Likelihoods and Inference Methods
- Gaussian Likelihood
- Warped Gaussian Likelihood
- Gumbel Likelihood
- Laplace Likelihood
- Student's t Likelihood
- Cumulative Logistic Likelihood
- GLM Likelihoods: Poisson, Negative Binomial, Weibull, Gamma, Exponential, Inverse Gaussian and Beta
- Mean Functions
- Covariance Functions
- Hyperpriors