- The Wikipedia article on Automatic Differentiation, because it's not widely known and is incredibly powerful. https://en.m.wikipedia.org/wiki/automatic_differentiation 78 comments math
- Automatic vs numerical differentiation http://en.wikipedia.org/wiki/Automatic_differentiation 3 comments math
- Automatic differentiation: a fast and accurate alternative to numerical and symbolic differentiation http://en.wikipedia.org/wiki/automatic_differentiation 4 comments math
Linking pages
- swift/WhySwiftForTensorFlow.md at main · tensorflow/swift · GitHub https://github.com/tensorflow/swift/blob/master/docs/whyswiftfortensorflow.md 180 comments
- JAX Quickstart — JAX documentation https://jax.readthedocs.io/en/latest/notebooks/quickstart.html 143 comments
- On the Cleverness of Compilers http://alexey.radul.name/ideas/2013/cleverness-of-compilers/ 125 comments
- GitHub - c0dearm/mushin: Computational graphs with reverse automatic differentation in the GPU https://github.com/c0dearm/mushin 63 comments
- swift/DesignOverview.md at main · tensorflow/swift · GitHub https://github.com/tensorflow/swift/blob/master/docs/DesignOverview.md 45 comments
- Newton, The Ultimate: One Weird Trick To Make You A Mathematical Superhero, part 2: Julia, optimization, and automatic differentiation http://julesjacobs.github.io/2014/10/23/newton-the-ultimate-2.html 36 comments
- Dual Numbers & Automatic Differentiation « The blog at the bottom of the sea http://blog.demofox.org/2014/12/30/dual-numbers-automatic-differentiation/ 35 comments
- Beyond automatic differentiation – Google AI Blog https://ai.googleblog.com/2023/04/beyond-automatic-differentiation.html 34 comments
- Google Announces TensorFlow Graphics Library for Unsupervised Deep Learning of Computer Vision Model https://www.infoq.com/news/2019/05/google-tensorflow-graphics/ 29 comments
- GitHub - c0dearm/mushin: Computational graphs with reverse automatic differentation in the GPU https://github.com/c0dearm/gamma 26 comments
- ad.js - npm https://www.npmjs.com/package/ad.js 25 comments
- A Promenade of PyTorch – Peter Goldsborough http://www.goldsborough.me/ml/ai/python/2018/02/04/20-17-20-a_promenade_of_pytorch/ 24 comments
- Reverse-mode automatic differentiation from scratch, in Python | sidsite https://sidsite.com/posts/autodiff/ 17 comments
- Computing Symbolic Gradient Vectors with Plain Haskell | Dan Aloni http://blog.aloni.org/posts/symbolic-gradients-with-plain-haskell/ 11 comments
- PyTorch internals : ezyang’s blog http://blog.ezyang.com/2019/05/pytorch-internals/ 10 comments
- Introduction to Automatic Differentiation http://alexey.radul.name/ideas/2013/introduction-to-automatic-differentiation/ 10 comments
- Building an autodifferentiation library | by Maciej Kula | Medium https://medium.com/@maciejkula/building-an-autodifferentiation-library-9ccf32c7a658 10 comments
- GitHub - liaopeiyuan/zeta: functional neural networks in ocaml https://github.com/liaopeiyuan/zeta 9 comments
- GitHub - melisgl/mgl: Common Lisp machine learning library. https://github.com/melisgl/mgl 6 comments
- GitHub - Janko-dev/rustydiff: Forward and reverse mode autodiff in Rust https://github.com/Janko-dev/rustydiff 4 comments
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