Feedforward Likelihoods

BayesFlux.FeedforwardNormalType
FeedforwardNormal(nc::NetConstructor{T, F}, prior_σ::D) where {T, F, D<:Distribution}

Use a Gaussian/Normal likelihood for a Feedforward architecture with a single output.

Assumes is a single output. Thus, the last layer must have output size one.

Arguments

  • nc: obtained using destruct
  • prior_σ: a prior distribution for the standard deviation
BayesFlux.FeedforwardTDistType
FeedforwardTDist(nc::NetConstructor{T, F}, prior_σ::D, ν::T) where {T, F, D}

Use a Student-T likelihood for a Feedforward architecture with a single output and known degress of freedom.

Assumes is a single output. Thus, the last layer must have output size one.

Arguments

  • nc: obtained using destruct
  • prior_σ: a prior distribution for the standard deviation
  • ν: degrees of freedom