FastAD VS TemporalSetInversion

Compare FastAD vs TemporalSetInversion and see what are their differences.

FastAD

FastAD is a C++ implementation of automatic differentiation both forward and reverse mode. (by JamesYang007)
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FastAD TemporalSetInversion
1 1
91 10
- -
2.5 5.3
7 months ago 8 months ago
C++ C++
MIT License GNU General Public License v3.0 only
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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FastAD

Posts with mentions or reviews of FastAD. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-01-22.
  • WG21 January 2021 Mailing
    3 projects | /r/cpp | 22 Jan 2021
    What stage is the differentiation proposal in? It seems odd they talked about reverse mode AD but made no mention of memory management for it. They also don't mention anything about FastAD or Stan Math which I think do some pretty innovative things in this space.

TemporalSetInversion

Posts with mentions or reviews of TemporalSetInversion. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-07.

What are some alternatives?

When comparing FastAD and TemporalSetInversion you can also consider the following projects:

autodiff - automatic differentiation made easier for C++

papers - ISO/IEC JTC1 SC22 WG21 paper scheduling and management

curv - a language for making art using mathematics

geodesic_raytracing

LearnOpenGL - Code repository of all OpenGL chapters from the book and its accompanying website https://learnopengl.com

giada - Your Hardcore Loop Machine.

control-toolbox - The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control

filesystem - An implementation of C++17 std::filesystem for C++11 /C++14/C++17/C++20 on Windows, macOS, Linux and FreeBSD.

pinocchio - A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives

Mission : Impossible (AutoDiff) - A concise C++17 implementation of automatic differentiation (operator overloading)

papers