Topic: "algorithmic-differentation"
casadi/casadi
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.
Language: C++ - Size: 141 MB - Last synced at: 8 days ago - Pushed at: 9 days ago - Stars: 1,916 - Forks: 414
owlbarn/owl
Owl - OCaml Scientific Computing @ https://ocaml.xyz
Language: OCaml - Size: 27.2 MB - Last synced at: 5 days ago - Pushed at: about 1 month ago - Stars: 1,275 - Forks: 126
joaoleal/CppADCodeGen
Source Code Generation for Automatic Differentiation using Operator Overloading
Language: C++ - Size: 14.8 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 180 - Forks: 39
Rookfighter/autodiff-cpp
A single header-only C++ library for automatic / algorithmic differentiation.
Language: C++ - Size: 87.9 KB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 10 - Forks: 2
rcalxrc08/xComplex
Complex Numbers for Algorithmic Differentiation
Language: C++ - Size: 5.3 MB - Last synced at: 3 months ago - Pushed at: over 7 years ago - Stars: 2 - Forks: 0
neilkichler/cutangent
CUDA subgradients using forward-mode AD.
Language: Cuda - Size: 143 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
