Automatic Differentiation GitHub Repositories

Tensor library for machine learning

Efficiently computes derivatives of NumPy code.

Gorgonia is a library that helps facilitate machine learning in Go.

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.

automatic differentiation made easier for C++

Self-contained Machine Learning and Natural Language Processing library in Go

The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control

High-performance automatic differentiation of LLVM and MLIR.

21st century AD

A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

Owl - OCaml Scientific Computing @ https://ocaml.xyz

Aircraft design optimization made fast through computational graph transformations (e.g., automatic differentiation). Composable analysis tools for aerodynamics, propulsion, structures, trajectory design, and much more.

A JavaScript library like PyTorch, with GPU acceleration.

Forward Mode Automatic Differentiation for Julia

OptimLib: a lightweight C++ library of numerical optimization methods for nonlinear functions

『ゼロから作る Deep Learning ❸』(O'Reilly Japan, 2020)

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.

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.

A simple library for creating complex neural networks

Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.

Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.

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TorchOpt is an efficient library for differentiable optimization built upon PyTorch.

Differentiable Fluid Dynamics Package

Julia bindings for the Enzyme automatic differentiator

🧩 Shape-Safe Symbolic Differentiation with Algebraic Data Types

⟨Grassmann-Clifford-Hodge⟩ differential geometric algebra

Tensors and differentiable operations (like TensorFlow) in Rust

The Emmy Computer Algebra System.