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Module: tfp.experimental.distributions

TensorFlow Probability experimental distributions package.


marginal_fns module: Experimental functions to use as marginals for GaussianProcess(es).


class IncrementLogProb: A distribution-like object representing an unnormalized density at a point.

class JointDensityCoroutine: Joint density parameterized by a distribution-making generator.

class JointDistributionPinned: A wrapper class for JointDistribution which pins, e.g., the evidence.

class MultivariateNormalPrecisionFactorLinearOperator: A multivariate normal on R^k, parametrized by a precision factor.


log_prob_ratio(...): Computes p.log_prob(x) - q.log_prob(y), numerically stably.