automatic-differentiation

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

Source-to-Source Debuggable Derivatives in Pure 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.

21st century AD

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

automatic differentiation made easier for C++

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

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

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

A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives

Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.

High-performance automatic differentiation of LLVM and MLIR.

A simple library for creating complex neural networks

Forward Mode Automatic Differentiation for Julia

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.

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)

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🧩 Shape-Safe Symbolic Differentiation with Algebraic Data Types

A Programming Language for Deep Learning