| AbstractModel() | shark::AbstractModel< RealVector, RealVector > | inline |
| BatchInputType typedef | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | |
| BatchOutputType typedef | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | |
| BOOST_SERIALIZATION_SPLIT_MEMBER() | shark::ISerializable | |
| ConvolutionalRBM(RngType &rng) | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| createState() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inlinevirtual |
| energy() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| EnergyType typedef | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | |
| eval(BatchInputType const &patterns, BatchOutputType &outputs) const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inlinevirtual |
| eval(BatchInputType const &patterns, BatchOutputType &outputs, State &state) const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inlinevirtual |
| AbstractModel< RealVector, RealVector >::eval(InputType const &pattern, OutputType &output) const | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| evaluationType(bool forward, bool evalMean) | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| Feature enum name | shark::AbstractModel< RealVector, RealVector > | |
| FeatureNotAvailableException typedef | shark::AbstractModel< RealVector, RealVector > | |
| Features typedef | shark::AbstractModel< RealVector, RealVector > | |
| features() const | shark::AbstractModel< RealVector, RealVector > | inline |
| filters() | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| filterSize1() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| filterSize2() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| GradientType typedef | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | |
| HAS_FIRST_INPUT_DERIVATIVE enum value | shark::AbstractModel< RealVector, RealVector > | |
| HAS_FIRST_PARAMETER_DERIVATIVE enum value | shark::AbstractModel< RealVector, RealVector > | |
| HAS_SECOND_INPUT_DERIVATIVE enum value | shark::AbstractModel< RealVector, RealVector > | |
| HAS_SECOND_PARAMETER_DERIVATIVE enum value | shark::AbstractModel< RealVector, RealVector > | |
| hasFirstInputDerivative() const | shark::AbstractModel< RealVector, RealVector > | inline |
| hasFirstParameterDerivative() const | shark::AbstractModel< RealVector, RealVector > | inline |
| hasSecondInputDerivative() const | shark::AbstractModel< RealVector, RealVector > | inline |
| hasSecondParameterDerivative() const | shark::AbstractModel< RealVector, RealVector > | inline |
| hiddenNeurons() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| hiddenNeurons() | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| HiddenType typedef | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | |
| inputHidden(RealMatrix &inputs, RealMatrix const &visibleStates) const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| inputSize1() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| inputSize2() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| InputType typedef | shark::AbstractModel< RealVector, RealVector > | |
| inputVisible(RealMatrix &inputs, RealMatrix const &hiddenStates) const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| IS_SEQUENTIAL enum value | shark::AbstractModel< RealVector, RealVector > | |
| isSequential() const | shark::AbstractModel< RealVector, RealVector > | inline |
| load(InArchive &archive, unsigned int version) | shark::ISerializable | inline |
| m_features | shark::AbstractModel< RealVector, RealVector > | protected |
| name() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inlinevirtual |
| numberOfHN() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| numberOfParameters() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inlinevirtual |
| numberOfVN() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| numFilters() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| operator()(Data< InputType > const &patterns) const | shark::AbstractModel< RealVector, RealVector > | inline |
| operator()(InputType const &pattern) const | shark::AbstractModel< RealVector, RealVector > | inline |
| operator()(BatchInputType const &patterns) const | shark::AbstractModel< RealVector, RealVector > | inline |
| OutputType typedef | shark::AbstractModel< RealVector, RealVector > | |
| parameterVector() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inlinevirtual |
| read(InArchive &archive) | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inlinevirtual |
| responseSize1() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| responseSize2() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| rng() | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| RngType typedef | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | |
| save(OutArchive &archive, unsigned int version) const | shark::ISerializable | inline |
| setParameterVector(const RealVector &newParameters) | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inlinevirtual |
| setStructure(std::size_t newInputSize1, std::size_t newInputSize2, std::size_t newNumFilters, std::size_t filterSize) | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| updateFeatures() | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| visibleNeurons() | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| visibleNeurons() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| VisibleType typedef | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | |
| weightedDerivatives(BatchInputType const &patterns, BatchOutputType const &coefficients, State const &state, RealVector ¶meterDerivative, BatchInputType &inputDerivative) const | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| weightedInputDerivative(BatchInputType const &pattern, BatchOutputType const &coefficients, State const &state, BatchInputType &derivative) const | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| weightedInputDerivative(BatchInputType const &pattern, BatchOutputType const &coefficients, typename Batch< RealMatrix >::type const &errorHessian, State const &state, RealMatrix &derivative, Batch< RealMatrix >::type &hessian) const | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| weightedParameterDerivative(BatchInputType const &pattern, BatchOutputType const &coefficients, State const &state, RealVector &derivative) const | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| weightedParameterDerivative(BatchInputType const &pattern, BatchOutputType const &coefficients, Batch< RealMatrix >::type const &errorHessian, State const &state, RealVector &derivative, RealMatrix &hessian) const | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| weightMatrix() const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inline |
| write(OutArchive &archive) const | shark::ConvolutionalRBM< VisibleLayerT, HiddenLayerT, RngT > | inlinevirtual |
| ~AbstractModel() | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| ~INameable() | shark::INameable | inlinevirtual |
| ~IParameterizable() | shark::IParameterizable | inlinevirtual |
| ~ISerializable() | shark::ISerializable | inlinevirtual |