Defined in edward/models/__init__.py
.
class Autoregressive
: Autoregressive distributions.
class Bernoulli
: Bernoulli distribution.
class BernoulliWithSigmoidProbs
: Bernoulli with probs = nn.sigmoid(logits)
.
class Beta
: Beta distribution.
class BetaWithSoftplusConcentration
: Beta with softplus transform of concentration1
and concentration0
.
class Binomial
: Binomial distribution.
class Categorical
: Categorical distribution.
class Cauchy
: The Cauchy distribution with location loc
and scale scale
.
class Chi2
: Chi2 distribution.
class Chi2WithAbsDf
: Chi2 with parameter transform df = floor(abs(df))
.
class ConditionalDistribution
: Distribution that supports intrinsic parameters (local latents).
class ConditionalTransformedDistribution
: A TransformedDistribution that allows intrinsic conditioning.
class Deterministic
: Scalar Deterministic
distribution on the real line.
class Dirichlet
: Dirichlet distribution.
class DirichletMultinomial
: Dirichlet-Multinomial compound distribution.
class DirichletProcess
: Dirichlet process \(\mathcal{DP}(\alpha, H)\).
class Empirical
: Empirical random variable.
class ExpRelaxedOneHotCategorical
: ExpRelaxedOneHotCategorical distribution with temperature and logits.
class Exponential
: Exponential distribution.
class ExponentialWithSoftplusRate
: Exponential with softplus transform on rate
.
class Gamma
: Gamma distribution.
class GammaWithSoftplusConcentrationRate
: Gamma
with softplus of concentration
and rate
.
class Geometric
: Geometric distribution.
class HalfNormal
: The Half Normal distribution with scale scale
.
class Independent
: Independent distribution from batch of distributions.
class InverseGamma
: InverseGamma distribution.
class InverseGammaWithSoftplusConcentrationRate
: InverseGamma
with softplus of concentration
and rate
.
class Laplace
: The Laplace distribution with location loc
and scale
parameters.
class LaplaceWithSoftplusScale
: Laplace with softplus applied to scale
.
class Logistic
: The Logistic distribution with location loc
and scale
parameters.
class Mixture
: Mixture distribution.
class MixtureSameFamily
: Mixture (same-family) distribution.
class Multinomial
: Multinomial distribution.
class MultivariateNormalDiag
: The multivariate normal distribution on R^k
.
class MultivariateNormalDiagPlusLowRank
: The multivariate normal distribution on R^k
.
class MultivariateNormalDiagWithSoftplusScale
: MultivariateNormalDiag with diag_stddev = softplus(diag_stddev)
.
class MultivariateNormalFullCovariance
: The multivariate normal distribution on R^k
.
class MultivariateNormalTriL
: The multivariate normal distribution on R^k
.
class NegativeBinomial
: NegativeBinomial distribution.
class Normal
: The Normal distribution with location loc
and scale
parameters.
class NormalWithSoftplusScale
: Normal with softplus applied to scale
.
class OneHotCategorical
: OneHotCategorical distribution.
class ParamMixture
: A mixture distribution where all components are of the same family.
class PointMass
: PointMass random variable.
class Poisson
: Poisson distribution.
class PoissonLogNormalQuadratureCompound
: PoissonLogNormalQuadratureCompound
distribution.
class QuantizedDistribution
: Distribution representing the quantization Y = ceiling(X)
.
class RandomVariable
: Base class for random variables.
class RelaxedBernoulli
: RelaxedBernoulli distribution with temperature and logits parameters.
class RelaxedOneHotCategorical
: RelaxedOneHotCategorical distribution with temperature and logits.
class SinhArcsinh
: The SinhArcsinh transformation of a distribution on (-inf, inf)
.
class StudentT
: Student’s t-distribution.
class StudentTWithAbsDfSoftplusScale
: StudentT with df = floor(abs(df))
and scale = softplus(scale)
.
class TransformedDistribution
: A Transformed Distribution.
class Uniform
: Uniform distribution with low
and high
parameters.
class VectorDeterministic
: Vector Deterministic
distribution on R^k
.
class VectorDiffeomixture
: VectorDiffeomixture distribution.
class VectorExponentialDiag
: The vectorization of the Exponential distribution on R^k
.
class VectorLaplaceDiag
: The vectorization of the Laplace distribution on R^k
.
class VectorSinhArcsinhDiag
: The (diagonal) SinhArcsinh transformation of a distribution on R^k
.
class WishartCholesky
: The matrix Wishart distribution on positive definite matrices.
class WishartFull
: The matrix Wishart distribution on positive definite matrices.