Show tools for a specific language:

• Show all
• .NET
• C#
• C/C++
• Delphi
• F#
• Fortran 77/90
• Fortran2003
• Fortran2008
• Fortran2018
• Fortran77
• Fortran95
• FortranCalculus
• Haskell
• Interpreted
• Java
• Julia
• Kotlin
• LLVM
• Language independent
• Lua
• MATLAB
• OpenCL
• Python
• R

Alphabetical List of Tools

• ADiJaC  (Java)
  ADiJaC uses source code transformation to generate derivative codes in both the forward and the reverse modes of automatic differentiation.
  
  
• COJAC  (Java)
  COJAC uses bytecode instrumentation to automatically enrich floats/doubles at runtime; the prototype offers both forward and reverse mode AD. The idea is presented in this short video: https://youtu.be/eAy71M34U_I?list=PLHLKWUtT0B7kNos1e48vKhFlGAXR1AAkF
  
  
• finmath-lib automatic differentiation extensions  (Java)
  Implementation of a stochastic automatic differentiation (AD / AAD for Monte-Carlo Simulations).