Emulators API
The Emulators submodule defines types and methods for emulating expensive SimulatorForwardProblems.
SimulationBasedInference.Emulators.Decorrelated — TypeDecorrelated{bijType} <: DataTransformDecorrelation transform applied to a multivariate output (target) space.
SimulationBasedInference.Emulators.EmulatedObservables — TypeEmulatedObservables{names} <: SciMLBase.AbstractSciMLAlgorithmRepresents an emulated forward solver for observables names in a given forward problem. The dimensionality of the output spaces of the emulators are assumed to match those of the observables exactly.
SimulationBasedInference.Emulators.Emulator — TypeEmulator{TM,TT} <: EmulatorData structure consisting of some training data for a model emulator, appropriate transforms, and a tuple of univariate regressors which are applied to the transformed data.
SimulationBasedInference.Emulators.EmulatorData — TypeEmulatorDataGeneric container for emulator training data matrices X and Y. X should have shape m x N where N is the number of samples and m is the number of covariates. Y should have dimensions N x d where d is the number of ouptut covariates.+
SimulationBasedInference.Emulators.GPRegressor — TypeGPRegressorGeneric implementation of a Gaussian Process regressor for a univariate outputs. This implementation is adapted from MLJGaussianProcesses to be usable without MLJ.
SimulationBasedInference.Emulators.StackedRegressors — TypeStackedRegressors{TM}Simple representation of a set of stacked, univaraite regressors for multi-target regression problems.