FastAD
Summary:
FastAD is a C++ template library of automatic differentiation supporting both forward and reverse mode to compute gradients and Hessians. It utilizes the latest features in C++17 and expression templates for efficient computation.
URL: https://github.com/JamesYang007/FastAD
Developers:
- James Yang
- Kent Hall
| Mode: |
Forward Reverse |
| Method: |
Operator overloading |
| Supported Language: |
C/C++ |
Features:
- Provides both forward and reverse mode.
- Supports gradient and Hessian computation.
- Elementary functions have same name as their STL counterpart.
- Supports similar syntax as STL.
- MIT licensed.
Supported Platforms:
- Unix/Linux
- Mac
- Application Server
Licensing: open source
Entries in our publication database that actually use FastAD in the numerical experiments: 0
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