inf-backprop: Automatic differentiation and backpropagation.
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Automatic differentiation and backpropagation.
We do not attract gradient tape.
Instead, the differentiation operator is defined directly as a map between differentiable function objects.
Such functions are to be combined in arrow style using (>>>), (***), first, etc.
The original purpose of the package is an automatic backpropagation differentiation component for a functional type-dependent library for deep machine learning. See tutorial details.
Properties
| Versions | 0.1.0.0, 0.1.0.0, 0.1.0.1, 0.1.0.2 |
|---|---|
| Change log | CHANGELOG.md |
| Dependencies | base (>=4.7 && <5), comonad, isomorphism-class, monad-logger, numhask, simple-expr, text, transformers [details] |
| License | BSD-3-Clause |
| Copyright | 2023 Alexey Tochin |
| Author | Alexey Tochin |
| Maintainer | Alexey.Tochin@gmail.com |
| Category | Math |
| Uploaded | by AlexeyTochin at 2023-05-13T10:35:39Z |
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- inf-backprop-0.1.0.0.tar.gz [browse] (Cabal source package)
- Package description (as included in the package)
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