A stochastic computation graph is a Directed acyclic graph combining deterministic transformations, random choices and costs. The changing probabilities of random choices contribute score-function gradient estimators, while differentiable deterministic paths contribute pathwise gradients. This accounts for both sources of a parameter's effect on an expected cost.[ref]
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