tf.contrib.distributions.Uniform.mean()
  • References/Big Data/TensorFlow/TensorFlow Python/Statistical distributions

tf.contrib.distributions.Uniform.mean(name='mean') Mean.

2025-01-10 15:47:30
tf.contrib.bayesflow.stochastic_tensor.BinomialTensor.value_type
  • References/Big Data/TensorFlow/TensorFlow Python/BayesFlow Stochastic Tensors

tf.contrib.bayesflow.stochastic_tensor.BinomialTensor.value_type

2025-01-10 15:47:30
tf.sparse_to_dense()
  • References/Big Data/TensorFlow/TensorFlow Python/Sparse Tensors

tf.sparse_to_dense(sparse_indices, output_shape, sparse_values, default_value=0, validate_indices=True, name=None) Converts a

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tf.contrib.distributions.Gamma.survival_function()
  • References/Big Data/TensorFlow/TensorFlow Python/Statistical distributions

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

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tf.erf()
  • References/Big Data/TensorFlow/TensorFlow Python/Math

tf.erf(x, name=None) Computes the Gauss error function of x element-wise. Args:

2025-01-10 15:47:30
tf.contrib.bayesflow.stochastic_tensor.StochasticTensor.
  • References/Big Data/TensorFlow/TensorFlow Python/BayesFlow Stochastic Tensors

tf.contrib.bayesflow.stochastic_tensor.StochasticTensor.__init__(dist_cls, name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

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tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagPlusVDVTTensor.
  • References/Big Data/TensorFlow/TensorFlow Python/BayesFlow Stochastic Tensors

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagPlusVDVTTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

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tf.contrib.distributions.StudentT.mean()
  • References/Big Data/TensorFlow/TensorFlow Python/Statistical distributions

tf.contrib.distributions.StudentT.mean(name='mean') Mean. Additional documentation from

2025-01-10 15:47:30
tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.sample_n()
  • References/Big Data/TensorFlow/TensorFlow Python/Statistical distributions

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

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tf.contrib.bayesflow.stochastic_tensor.ExponentialWithSoftplusLamTensor.distribution
  • References/Big Data/TensorFlow/TensorFlow Python/BayesFlow Stochastic Tensors

tf.contrib.bayesflow.stochastic_tensor.ExponentialWithSoftplusLamTensor.distribution

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