tf.contrib.bayesflow.stochastic_tensor.NormalTensor.graph

tf.contrib.bayesflow.stochastic_tensor.ObservedStochasticTensor.dtype

tf.contrib.bayesflow.stochastic_tensor.ObservedStochasticTensor.clone(name=None, **dist_args)

tf.contrib.bayesflow.stochastic_tensor.BetaWithSoftplusABTensor.input_dict

tf.contrib.distributions.LaplaceWithSoftplusScale.log_survival_function(value, name='log_survival_function') Log survival function

tf.contrib.bayesflow.stochastic_tensor.CategoricalTensor.value_type

tf.contrib.distributions.DirichletMultinomial.event_shape(name='event_shape') Shape of a single sample from a single batch as

tf.contrib.bayesflow.stochastic_tensor.InverseGammaTensor.mean(name='mean')

tf.contrib.distributions.Poisson.sample_n(n, seed=None, name='sample_n') Generate n samples.

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.sigma Scaling factors of these Student's t distribution(s).