[FactorMethod(typeof(Clone), "VariablePoint<>", new Type[]{}, Default = true)]
[Buffers(new string[]{"buffer0"})]
[Quality(QualityBand.Preview)]
public class VariablePointOp_RpropGamma : VariablePointOpBase

Fields

UseMean

Declaration

public static bool UseMean

Field Value

Type	Description
Boolean

Methods

Buffer0(Gamma, Gamma, Gamma, RpropBufferData)

Declaration

[SkipIfAllUniform]
public static RpropBufferData Buffer0(Gamma use, Gamma def, Gamma to_marginal, RpropBufferData buffer0)

Parameters

Type	Name	Description
Gamma	use
Gamma	def
Gamma	to_marginal
RpropBufferData	buffer0

Returns

Type	Description
RpropBufferData

Buffer0Init()

Declaration

public static RpropBufferData Buffer0Init()

Returns

Type	Description
RpropBufferData

MarginalAverageConditional(Gamma, Gamma, RpropBufferData, Gamma)

EP message to marginal.

Declaration

public static Gamma MarginalAverageConditional(Gamma use, Gamma def, RpropBufferData buffer0, Gamma result)

Parameters

Type	Name	Description
Gamma	use	Incoming message from `use`.
Gamma	def	Incoming message from `def`.
RpropBufferData	buffer0	Buffer `buffer0`.
Gamma	result	Modified to contain the outgoing message.

Returns

Type	Description
Gamma	`result`

Remarks

The outgoing message is a distribution matching the moments of marginal as the random arguments are varied. The formula is proj[p(marginal) sum_(use,def) p(use,def) factor(use,def,marginal)]/p(marginal).