tf.contrib.distributions.LaplaceWithSoftplusScale.is_continuous

tf.contrib.distributions.LaplaceWithSoftplusScale.is_continuous

2016-10-14 12:56:04
tf.contrib.distributions.BetaWithSoftplusAB.log_prob()

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

2016-10-14 12:46:58
tf.contrib.distributions.Exponential.variance()

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

2016-10-14 12:52:36
tf.contrib.distributions.Poisson.param_static_shapes()

tf.contrib.distributions.Poisson.param_static_shapes(cls, sample_shape) param_shapes with static (i.e. TensorShape) shapes.

2016-10-14 13:01:00
tf.contrib.distributions.InverseGamma.batch_shape()

tf.contrib.distributions.InverseGamma.batch_shape(name='batch_shape') Shape of a single sample from a single event index as a

2016-10-14 12:54:14
tf.contrib.distributions.NormalWithSoftplusSigma.name

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

2016-10-14 13:00:27
tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.log_pmf()

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

2016-10-14 12:55:05
tf.contrib.distributions.BetaWithSoftplusAB.variance()

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

2016-10-14 12:47:07
tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.survival_function()

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

2016-10-14 12:58:56
tf.contrib.distributions.Poisson.param_shapes()

tf.contrib.distributions.Poisson.param_shapes(cls, sample_shape, name='DistributionParamShapes') Shapes of parameters given the

2016-10-14 13:00:58