tf.contrib.distributions.TransformedDistribution.transform

tf.contrib.distributions.TransformedDistribution.transform Function transforming x => y.

2016-10-14 13:03:05
tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.batch_shape()

tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.batch_shape(name='batch_shape') Shape of a single sample from a single

2016-10-14 12:54:59
tf.contrib.distributions.Exponential

class tf.contrib.distributions.Exponential The Exponential distribution with rate parameter lam. The

2016-10-14 12:51:49
tf.contrib.distributions.Distribution.mode()

tf.contrib.distributions.Distribution.mode(name='mode') Mode.

2016-10-14 12:51:25
tf.contrib.distributions.MultivariateNormalDiagPlusVDVT

class tf.contrib.distributions.MultivariateNormalDiagPlusVDVT The multivariate normal distribution on R^k.

2016-10-14 12:58:32
tf.contrib.distributions.BernoulliWithSigmoidP.log_pdf()

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

2016-10-14 12:45:44
tf.contrib.distributions.Uniform.pmf()

tf.contrib.distributions.Uniform.pmf(value, name='pmf') Probability mass function. Args:

2016-10-14 13:03:37
tf.contrib.distributions.Poisson.cdf()

tf.contrib.distributions.Poisson.cdf(value, name='cdf') Cumulative distribution function. Given

2016-10-14 13:00:39
tf.contrib.distributions.Exponential.sample_n()

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

2016-10-14 12:52:31
tf.contrib.distributions.Categorical.survival_function()

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

2016-10-14 12:48:45