tf.contrib.distributions.ExponentialWithSoftplusLam.is_continuous

tf.contrib.bayesflow.stochastic_tensor.StochasticTensor.value(name='value')

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.param_static_shapes(cls, sample_shape) param_shapes with static (i.e.

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.validate_args Python boolean indicated possibly expensive checks

tf.contrib.distributions.Binomial.validate_args Python boolean indicated possibly expensive checks are enabled.

tf.contrib.bayesflow.stochastic_tensor.StochasticTensor.distribution

tf.contrib.bayesflow.stochastic_tensor.PoissonTensor.entropy(name='entropy')

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

tf.contrib.distributions.InverseGamma.log_pdf(value, name='log_pdf') Log probability density function.

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