Difference between revisions of "Differentiable Programming"
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* [http://en.wikipedia.org/wiki/Category:Programming_paradigms Programming paradigms | Wikipedia] | * [http://en.wikipedia.org/wiki/Category:Programming_paradigms Programming paradigms | Wikipedia] | ||
* [[Automated Machine Learning (AML) - AutoML]] | * [[Automated Machine Learning (AML) - AutoML]] | ||
| + | * [http://medium.com/syncedreview/julia-computing-mit-introduce-differentiable-programming-system-bridging-ai-and-science-738c8a9eb0b9 Julia Computing & MIT Introduce Differentiable Programming System Bridging AI and Science | Yuqing Li - Synced - Medium] | ||
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. [http://pathmind.com/wiki/differentiableprogramming A Beginner's Guide to Differentiable Programming | Chris Nicholson - A.I. Wiki pathmind] | 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. [http://pathmind.com/wiki/differentiableprogramming A Beginner's Guide to Differentiable Programming | Chris Nicholson - A.I. Wiki pathmind] | ||
Revision as of 17:27, 26 April 2020
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- Programming paradigms | Wikipedia
- Automated Machine Learning (AML) - AutoML
- Julia Computing & MIT Introduce Differentiable Programming System Bridging AI and Science | Yuqing Li - Synced - Medium
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
