tf.contrib.distributions.Mixture.std()

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

2016-10-14 12:56:39
tf.contrib.distributions.Uniform.parameters

tf.contrib.distributions.Uniform.parameters Dictionary of parameters used by this Distribution.

2016-10-14 13:03:30
tf.contrib.distributions.TransformedDistribution.std()

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

2016-10-14 13:03:03
tf.contrib.distributions.ExponentialWithSoftplusLam.std()

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

2016-10-14 12:52:55
tf.contrib.distributions.WishartCholesky.prob()

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

2016-10-14 13:04:10
tf.contrib.distributions.Poisson.std()

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

2016-10-14 13:01:10
tf.contrib.distributions.Poisson.lam

tf.contrib.distributions.Poisson.lam Rate parameter.

2016-10-14 13:00:45
tf.contrib.distributions.Gamma.mode()

tf.contrib.distributions.Gamma.mode(name='mode') Mode. Additional documentation from Gamma:

2016-10-14 12:53:27
tf.contrib.distributions.Beta.log_prob()

tf.contrib.distributions.Beta.log_prob(value, name='log_prob') Log probability density/mass function (depending on is_continuous)

2016-10-14 12:46:21
tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.validate_args

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

2016-10-14 13:02:37