tf.contrib.bayesflow.stochastic_tensor.MultinomialTensor.dtype

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagPlusVDVTTensor.graph

tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.distribution

tf.contrib.bayesflow.stochastic_tensor.StudentTTensor.graph

tf.contrib.bayesflow.stochastic_tensor.PoissonTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

tf.contrib.bayesflow.stochastic_tensor.LaplaceWithSoftplusScaleTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

tf.contrib.bayesflow.stochastic_tensor.CategoricalTensor.distribution

class tf.contrib.distributions.Multinomial Multinomial distribution. This distribution is parameterized by a vector p of probability parameters for k classes and n, the counts per each class..

tf.contrib.distributions.MultivariateNormalDiag.sigma_det(name='sigma_det') Determinant of covariance matrix.

class tf.contrib.distributions.BetaWithSoftplusAB Beta with softplus transform on a and b.