tf.contrib.distributions.Distribution.prob()

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

2016-10-14 12:51:37
tf.contrib.distributions.Poisson.

tf.contrib.distributions.Poisson.__init__(lam, validate_args=False, allow_nan_stats=True, name='Poisson') Construct Poisson distributions

2016-10-14 13:01:14
tf.contrib.distributions.Bernoulli.sample_n()

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

2016-10-14 12:45:30
tf.contrib.distributions.WishartFull.name

tf.contrib.distributions.WishartFull.name Name prepended to all ops created by this Distribution.

2016-10-14 13:04:32
tf.contrib.distributions.Gamma.pdf()

tf.contrib.distributions.Gamma.pdf(value, name='pdf') Probability density function. Args:

2016-10-14 12:53:35
tf.contrib.distributions.Multinomial.variance()

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

2016-10-14 12:57:13
tf.contrib.distributions.Gamma.sample_n()

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

2016-10-14 12:53:44
tf.contrib.distributions.Uniform.survival_function()

tf.contrib.distributions.Uniform.survival_function(value, name='survival_function') Survival function. Given

2016-10-14 13:03:43
tf.contrib.distributions.Dirichlet.sample_n()

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

2016-10-14 12:50:22
tf.contrib.distributions.Chi2.beta

tf.contrib.distributions.Chi2.beta Inverse scale parameter.

2016-10-14 12:48:54