| PennyLaneAI/pennylane |
2,022 |
|
10 |
54 |
about 2 years ago |
46 |
November 08, 2023 |
263 |
apache-2.0 |
Python |
| PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network. |
| owlbarn/owl |
1,118 |
|
0 |
0 |
over 2 years ago |
0 |
|
77 |
mit |
OCaml |
| Owl - OCaml Scientific Computing @ http://ocaml.xyz |
| ethz-adrl/control-toolbox |
838 |
|
0 |
0 |
about 4 years ago |
0 |
|
53 |
bsd-2-clause |
C++ |
| The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control |
| kthohr/optim |
726 |
|
0 |
0 |
over 2 years ago |
0 |
|
7 |
apache-2.0 |
C++ |
| OptimLib: a lightweight C++ library of numerical optimization methods for nonlinear functions |
| pymanopt/pymanopt |
668 |
|
0 |
0 |
over 2 years ago |
0 |
|
38 |
bsd-3-clause |
Python |
| Python toolbox for optimization on Riemannian manifolds with support for automatic differentiation |
| SciML/Optimization.jl |
625 |
|
0 |
0 |
about 2 years ago |
0 |
|
91 |
mit |
Julia |
| Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface. |
| peterdsharpe/AeroSandbox |
573 |
|
0 |
1 |
over 2 years ago |
161 |
December 08, 2023 |
4 |
mit |
Jupyter Notebook |
| Aircraft design optimization made fast through modern automatic differentiation. Composable analysis tools for aerodynamics, propulsion, structures, trajectory design, and much more. |
| breandan/kotlingrad |
489 |
|
0 |
0 |
about 3 years ago |
2 |
December 25, 2021 |
13 |
apache-2.0 |
Kotlin |
| 🧩 Shape-Safe Symbolic Differentiation with Algebraic Data Types |
| metaopt/torchopt |
460 |
|
0 |
2 |
over 2 years ago |
14 |
November 10, 2023 |
6 |
apache-2.0 |
Python |
| TorchOpt is an efficient library for differentiable optimization built upon PyTorch. |
| patr-schm/TinyAD |
329 |
|
0 |
0 |
over 2 years ago |
0 |
|
2 |
mit |
C++ |
| Automatic Differentiation in Geometry Processing Made Simple |
