Gradients Without Backpropagation

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com
Math automatic-differentiation C++ auto-differentiation numerical-optimization

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  • hn-search

    Hacker News Search

    • Looks like it was submitted a couple of times but withou traction or comments

    https://hn.algolia.com/?dateRange=pastMonth&page=0&prefix=tr...

  • ceres-solver

    A large scale non-linear optimization library

    • http://ceres-solver.org/ works well, in my experience.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • autodiff

    automatic differentiation made easier for C++

    • Forward-mode differentiation is easy to implement in C++ with templates, operator overloading, and dual numbers (https://en.wikipedia.org/wiki/Automatic_differentiation#Auto...). Some libraries such as autodiff (https://github.com/autodiff/autodiff) and CppAD (https://github.com/coin-or/CppAD) use this method.

  • CppAD

    A C++ Algorithmic Differentiation Package: Home Page

    • Forward-mode differentiation is easy to implement in C++ with templates, operator overloading, and dual numbers (https://en.wikipedia.org/wiki/Automatic_differentiation#Auto...). Some libraries such as autodiff (https://github.com/autodiff/autodiff) and CppAD (https://github.com/coin-or/CppAD) use this method.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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