85 Open Source Automatic Differentiation Software Projects
Free and open source automatic differentiation code projects including engines, APIs, generators, and tools.
Arraymancer 721 ⭐
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
Nlpodyssey Spago 714 ⭐
spaGO is a beautiful and maintainable machine learning library written in Go designed to support relevant neural network architectures in natural language processing tasks
Pennylane 597 ⭐
PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.
Stan Dev Math 456 ⭐
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.
Control Toolbox 448 ⭐
The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control
Pinocchio 332 ⭐
A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
Grassmann.jl 257 ⭐
⟨Leibniz-Grassmann-Clifford⟩ differential geometric algebra / multivector simplicial complex
Dcpp 142 ⭐
Automatic differentiation in C++; infinite differentiability of conditionals, loops, recursion and all things C++
Taylorseries.jl 127 ⭐
A julia package for Taylor polynomial expansions in one and several independent variables.
Chainrules.jl 109 ⭐
forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs
Qml 109 ⭐
Introductions to key concepts in quantum machine learning, as well as tutorials and implementations from cutting-edge QML research.
Tensors.jl 81 ⭐
Efficient computations with symmetric and non-symmetric tensors with support for automatic differentiation.
Omeinsum.jl 65 ⭐
One More Einsum for Julia! With runtime order-specification and high-level adjoints for AD
Nbodysimulator.jl 55 ⭐
A differentiable simulator for scientific machine learning (SciML) with N-body problems, including astrophysical and molecular dynamics
Galacticoptim.jl 68 ⭐
Local, global, and beyond optimization for scientific machine learning (SciML)
Compfinance 58 ⭐
Companion code for "Modern Computational Finance: AAD and Parallel Simulations" (Antoine Savine, Wiley, 2018)
Chainrulescore.jl 58 ⭐
It is like recipes but for AD! (Full functionality is in ChainRules.jl but this a light weight dependency just to define sensitivities for your functions in your packages)
Alexshtf Autodiff 49 ⭐
A .NET library that provides fast, accurate and automatic differentiation (computes derivative / gradient) of mathematical functions.
Tensornetworkad.jl 45 ⭐
Algorithms that combine tensor network methods with automatic differentiation
Qualia2.0 39 ⭐
Qualia is a deep learning framework deeply integrated with automatic differentiation and dynamic graphing with CUDA acceleration. Qualia was built from scratch.
Workshop Invdesign 35 ⭐
📐 Workshop material for optical inverse design and automatic differentiation
Optimal Control Literature Software 30 ⭐
List of literature and software for optimal control and numerical optimization.
Palle K Dl4s 34 ⭐
Deep Learning for Swift - Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation
Diffhask 26 ⭐
DSL for forward and reverse mode automatic differentiation in Haskell. Port of DiffSharp.
Pennylane Forest 26 ⭐
This PennyLane plugin allows the Rigetti Forest QPUs, QVM, and wavefunction simulator to optimize quantum circuits.
Pbenner Autodiff 25 ⭐
Autodiff is a numerical library for the Go programming language that supports automatic differentiation. It implements routines for linear algebra (vector/matrix operations), numerical optimization and statistics
Differential Machine Learning Notebooks 27 ⭐
Implement, demonstrate, reproduce and extend the results of the article 'Differential Machine Learning' (Huge & Savine, 2020), and cover implementation details left out of the working paper
Quadrature.jl 27 ⭐
A common interface for quadrature and numerical integration for the SciML scientific machine learning organization
Deepflow 21 ⭐
Pytorch implementation of "DeepFlow: History Matching in the Space of Deep Generative Models"
Fastad 26 ⭐
FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
Admc 14 ⭐
Infinite order automatic differentiation for Monte Carlo with unnormalized probability distribution
Missionimpossible 12 ⭐
A concise C++17 implementation of automatic differentiation (operator overloading)
Appendices 12 ⭐
Complement the article 'Differential Machine Learning' (Huge & Savine, 2020), including mathematical proofs and important implementation details for production
Machine Learning Summer Schools 11 ⭐
Curated materials for different machine learning related summer schools
Fwiflow.jl 10 ⭐
Elastic Full Waveform Inversion for subsurface flow problems with intrusive automatic differentiation