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https://github.com/invenia/nabla.jl

A operator overloading, tape-based, reverse-mode AD
https://github.com/invenia/nabla.jl

autodiff automatic-differentiation julia julia-language

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A operator overloading, tape-based, reverse-mode AD

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README

        

# Nabla

[![CI](https://github.com/Invenia/Nabla.jl/workflows/CI/badge.svg)](https://github.com/Invenia/Nabla.jl/actions?query=workflow%3ACI)
[![codecov.io](https://codecov.io/github/invenia/Nabla.jl/coverage.svg?branch=master)](https://codecov.io/github/invenia/Nabla.jl?branch=master)
[![Stable Docs](https://img.shields.io/badge/docs-stable-blue.svg)](https://invenia.github.io/Nabla.jl/stable)
[![Latest Docs](https://img.shields.io/badge/docs-latest-blue.svg)](https://invenia.github.io/Nabla.jl/latest)

# No Longer Maintained

This project is no longer actively maintained, as it has been thoroughly superceeded by other AD projects in the Julia ecosystem.

# README

Nabla.jl is a reverse-mode automatic differentiation package targetting machine learning use cases.
As such, we have (for example) prioritised support for linear algebra optimisations and higher-order functions over the ability to take higher-order derivatives (Nabla currently only supports first-order derivatives).

The [latest docs](https://invenia.github.io/Nabla.jl/latest/), and code in the [examples](examples) folder, best indicate how to use the package.
Given the early stage of development, we anticipate a number of bugs and performance issues.
If you encounter any of these or have any particular feature requests, please raise an issue and let us know.