Difference between revisions of "Differentiable Programming"
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TensorFlow 1 uses the static graph approach, whereas TensorFlow 2 uses the dynamic graph approach by default. [http://en.wikipedia.org/wiki/Differentiable_programming Differentiable programming | Wikipedia] | TensorFlow 1 uses the static graph approach, whereas TensorFlow 2 uses the dynamic graph approach by default. [http://en.wikipedia.org/wiki/Differentiable_programming Differentiable programming | Wikipedia] | ||
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Revision as of 17:20, 26 April 2020
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Differentiable programs are programs that rewrite themselves at least one component by optimizing along a gradient, like neural networks do using optimization algorithms such as gradient descent. Here’s a graphic illustrating the difference between differential and probabilistic programming approaches. A Beginner's Guide to Differentiable Programming | Chris Nicholson - A.I. Wiki pathmind
TensorFlow 1 uses the static graph approach, whereas TensorFlow 2 uses the dynamic graph approach by default. Differentiable programming | Wikipedia
