tf.contrib.distributions.Chi2.std()

tf.contrib.distributions.Chi2.std(name='std') Standard deviation.

2016-10-14 12:49:32
tf.contrib.distributions.Distribution.mean()

tf.contrib.distributions.Distribution.mean(name='mean') Mean.

2016-10-14 12:51:24
tf.contrib.distributions.Dirichlet.mean()

tf.contrib.distributions.Dirichlet.mean(name='mean') Mean.

2016-10-14 12:50:11
tf.contrib.distributions.MultivariateNormalDiag.is_reparameterized

tf.contrib.distributions.MultivariateNormalDiag.is_reparameterized

2016-10-14 12:58:01
tf.contrib.distributions.Uniform.validate_args

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

2016-10-14 13:03:44
tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.beta

tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.beta Scale parameter.

2016-10-14 12:54:59
tf.contrib.distributions.MultivariateNormalCholesky.log_pmf()

tf.contrib.distributions.MultivariateNormalCholesky.log_pmf(value, name='log_pmf') Log probability mass function.

2016-10-14 12:57:28
tf.contrib.distributions.MultivariateNormalFull.

tf.contrib.distributions.MultivariateNormalFull.__init__(mu, sigma, validate_args=False, allow_nan_stats=True, name='MultivariateNormalFull')

2016-10-14 12:59:38
tf.contrib.distributions.MultivariateNormalCholesky.pdf()

tf.contrib.distributions.MultivariateNormalCholesky.pdf(value, name='pdf') Probability density function.

2016-10-14 12:57:39
tf.contrib.distributions.MultivariateNormalCholesky.mu

tf.contrib.distributions.MultivariateNormalCholesky.mu

2016-10-14 12:57:34