Efficiently computes derivatives of NumPy code.
- autograd
- automatic-differentiation
- numpy
- python
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Efficiently computes derivatives of NumPy code.
A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.
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, Matlab/Octave, Julia or Javascript
automatic differentiation made easier for C++
The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control
Owl - OCaml Scientific Computing @ https://ocaml.xyz
The fastest automatic differentiation library for C++, with Python bindings. Forward, adjoint and higher-order derivatives, checkpointing, Eigen support and JIT. Reproducible benchmarks against CppAD, Adept and autodiff.
One open-source modeler for structures, heat and fluids, built from scratch in pure Rust: parametric part in, verified results out. Automatic all-hex and tet meshing, our own nonlinear implicit and explicit FEA, heat transfer and lattice Boltzmann CFD — every result checked against theory. For engineers and AI agents alike. Free, forever.
Solve automatic numerical differentiation problems in one or more variables.
Open source math and physics engine that executes MATLAB-syntax code. Features a modern compiler, automatic GPU acceleration for large calculations, and support for math on geometry / FEA calculations.
Trick Simulation Environment. Trick provides a common set of simulation capabilities and utilities to build simulations automatically.
An automatic code generator for nonlinear model predictive control (NMPC) and the continuation/GMRES method (C/GMRES) based numerical solvers for NMPC
A .NET library that provides fast, accurate and automatic differentiation (computes derivative / gradient) of mathematical functions.