tf.contrib.distributions.MultivariateNormalDiag.sample()

tf.contrib.distributions.MultivariateNormalDiag.sample(sample_shape=(), seed=None, name='sample') Generate samples of the specified

2016-10-14 12:58:24
tf.contrib.distributions.Dirichlet.prob()

tf.contrib.distributions.Dirichlet.prob(value, name='prob') Probability density/mass function (depending on is_continuous)

2016-10-14 12:50:19
tf.contrib.distributions.Gamma.prob()

tf.contrib.distributions.Gamma.prob(value, name='prob') Probability density/mass function (depending on is_continuous)

2016-10-14 12:53:39
tf.contrib.distributions.GammaWithSoftplusAlphaBeta.is_reparameterized

tf.contrib.distributions.GammaWithSoftplusAlphaBeta.is_reparameterized

2016-10-14 12:53:56
tf.contrib.distributions.NormalWithSoftplusSigma.is_continuous

tf.contrib.distributions.NormalWithSoftplusSigma.is_continuous

2016-10-14 13:00:25
tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.sigma

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.sigma Dense (batch) covariance matrix, if available.

2016-10-14 12:58:43
tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.sample_n()

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

2016-10-14 12:58:43
tf.contrib.distributions.Normal.variance()

tf.contrib.distributions.Normal.variance(name='variance') Variance.

2016-10-14 13:00:20
tf.contrib.distributions.MultivariateNormalDiag.entropy()

tf.contrib.distributions.MultivariateNormalDiag.entropy(name='entropy') Shanon entropy in nats.

2016-10-14 12:57:56
tf.contrib.distributions.Gamma.variance()

tf.contrib.distributions.Gamma.variance(name='variance') Variance.

2016-10-14 12:53:48