13#include <MachineLearning/FgSparseDeepGPBaseModel.h>
17 namespace MachineLearning
49 template<
typename Scalar>
80 SDGPR(
const af::array& Y,
const af::array& X, std::vector<HiddenLayerDescription> hiddenLayerdescriptions,
Scalar alpha = 1.0, LogLikType lType = LogLikType::Gaussian);
109 friend class boost::serialization::access;
111 template<
class Archive>
112 void serialize(Archive& ar,
unsigned int version)
114 ar& boost::serialization::base_object<SparseDeepGPBaseModel<Scalar>>(*this);
116 ar& BOOST_SERIALIZATION_NVP(dAlpha);
Deep sparse Gaussian process via Approximated Expectation Propagation (AEP).
virtual Scalar Function(const af::array &x, af::array &outGradient) override
Cost function the given x inputs.
SDGPR(const af::array &Y, const af::array &X, HiddenLayerDescription hiddenLayerdescription, Scalar alpha=1.0, LogLikType lType=LogLikType::Gaussian)
Constructor.
SDGPR()
Default constructor.
SDGPR(const af::array &Y, const af::array &X, std::vector< HiddenLayerDescription > hiddenLayerdescriptions, Scalar alpha=1.0, LogLikType lType=LogLikType::Gaussian)
Constructor.
Base class with abstract and basic function definitions. All deep GP models will be derived from this...
Description of the layer.