stack-of-tasks/pinocchio
A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
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A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
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.
The Stan Math Library is a C++ template library for automatic differentiation of any order using forward, reverse, and mixed modes. It includes a range of built-in functions for probabilistic modeling, linear algebra, and equation solving.
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.
Julia bindings for the Enzyme automatic differentiator
A JIT compiler for hybrid quantum programs in PennyLane
High-performance automatic differentiation of LLVM and MLIR.
Universal components for differentiable scientific computing. :package:
Efficiently computes derivatives of NumPy code.
That's all 9 repositories in this period.