Tensor library for machine learning

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.

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

automatic differentiation made easier for C++

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

21st century AD

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

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

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.

Forward Mode Automatic Differentiation for Julia

A JavaScript library like PyTorch, built from scratch.

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

A simple library for creating complex neural networks

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.

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

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.