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The Top 178 Automatic Differentiation Open Source Projects on Github

Categories > Machine Learning > Automatic Differentiation
Gorgonia ⭐ 4,249
Gorgonia is a library that helps facilitate machine learning in Go.
Tangent ⭐ 2,066
Source-to-Source Debuggable Derivatives in Pure Python
Zygote.jl ⭐ 1,103
Intimate Affection Auditor
Pennylane ⭐ 1,092
PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.
Spago ⭐ 1,031
Self-contained Machine Learning and Natural Language Processing library in Go
Owl ⭐ 957
Owl - OCaml Scientific and Engineering Computing @ http://ocaml.xyz
Arraymancer ⭐ 880
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
Autodiff ⭐ 810
automatic differentiation made easier for C++
Deeplearning.scala ⭐ 753
A simple library for creating complex neural networks
Control Toolbox ⭐ 649
The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control
Pinocchio ⭐ 614
A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
Forwarddiff.jl ⭐ 600
Forward Mode Automatic Differentiation for Julia
Enzyme ⭐ 570
High-performance automatic differentiation of LLVM.
Math ⭐ 551
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.
Deepdarkfantasy ⭐ 464
A Programming Language for Deep Learning
Kotlingrad ⭐ 438
🧩 Shape-Safe Symbolic Differentiation with Algebraic Data Types
Deep Learning From Scratch 3 ⭐ 426
『ゼロから作る Deep Learning ❸』(O'Reilly Japan, 2020)
Aesara ⭐ 399
Aesara is a Python library that allows one to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.
Tullio.jl ⭐ 348
⅀
Rust Autograd ⭐ 344
Tensors and differentiable operations (like TensorFlow) in Rust
Grassmann.jl ⭐ 338
⟨Leibniz-Grassmann-Clifford⟩ differential geometric algebra / multivector simplicial complex
Theano_lstm ⭐ 309
🔬 Nano size Theano LSTM module
Tensorlang ⭐ 303
Tensorlang, a differentiable programming language based on TensorFlow
Aerosandbox ⭐ 273
Aircraft design optimization made fast through modern automatic differentiation. Plug-and-play analysis tools for aerodynamics, propulsion, structures, trajectory design, and much more.
Qml ⭐ 264
Introductions to key concepts in quantum machine learning, as well as tutorials and implementations from cutting-edge QML research.
Galacticoptim.jl ⭐ 257
Local, global, and beyond optimization for scientific machine learning (SciML)
Chainrules.jl ⭐ 254
forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs
Mitgcm ⭐ 213
M.I.T General Circulation Model master code and documentation repository
Reversediff.jl ⭐ 212
Reverse Mode Automatic Differentiation for Julia
Taylorseries.jl ⭐ 204
A julia package for Taylor polynomial expansions in one and several independent variables.
Adcme.jl ⭐ 158
Automatic Differentiation Library for Computational and Mathematical Engineering
Backprop ⭐ 157
Heterogeneous automatic differentiation ("backpropagation") in Haskell
Autograd.jl ⭐ 153
Julia port of the Python autograd package.
Dcpp ⭐ 142
Automatic differentiation in C++; infinite differentiability of conditionals, loops, recursion and all things C++
Chainrulescore.jl ⭐ 130
AD-backend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for your functions in your packages, without depending on any particular AD system.
Enzyme.jl ⭐ 127
Julia bindings for the Enzyme automatic differentiator
Tensors.jl ⭐ 115
Efficient computations with symmetric and non-symmetric tensors with support for automatic differentiation.
Yota.jl ⭐ 106
Reverse-mode automatic differentiation in Julia
Omeinsum.jl ⭐ 96
One More Einsum for Julia! With runtime order-specification and high-level adjoints for AD
Nbodysimulator.jl ⭐ 94
A differentiable simulator for scientific machine learning (SciML) with N-body problems, including astrophysical and molecular dynamics
Cppadcodegen ⭐ 91
Source Code Generation for Automatic Differentiation using Operator Overloading
Tensorgrad ⭐ 90
Differentiable Programming Tensor Networks
Compfinance ⭐ 86
Companion code for "Modern Computational Finance: AAD and Parallel Simulations" (Antoine Savine, Wiley, 2018)
Birch ⭐ 77
A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.
Quantumflow ⭐ 69
QuantumFlow: A Quantum Algorithms Development Toolkit
Quadrature.jl ⭐ 69
A common interface for quadrature and numerical integration for the SciML scientific machine learning organization
Dl4s ⭐ 64
Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux
Symbolics.jl ⭐ 63
A symbolic math library written in Julia modelled off scmutils
Notebooks ⭐ 60
Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.
Nabla.jl ⭐ 53
A operator overloading, tape-based, reverse-mode AD
Taylorintegration.jl ⭐ 53
ODE integration using Taylor's method, and more, in Julia
Quantumflow Dev ⭐ 47
QuantumFlow: A Quantum Algorithms Development Toolkit
Hamiltoniansolver ⭐ 46
Numerically solves equations of motion for a given Hamiltonian function
Recurrentjava ⭐ 46
Deep Recurrent Neural Nets in Java
Xcfun ⭐ 43
XCFun: A library of exchange-correlation functionals with arbitrary-order derivatives
Qualia2.0 ⭐ 41
Qualia is a deep learning framework deeply integrated with automatic differentiation and dynamic graphing with CUDA acceleration. Qualia was built from scratch.
Jax Fenics Adjoint ⭐ 41
Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint
Autodiff ⭐ 40
A .NET library that provides fast, accurate and automatic differentiation (computes derivative / gradient) of mathematical functions.
Kerax ⭐ 39
Keras-like APIs for JAX framework
Tensornetworkad.jl ⭐ 39
Algorithms that combine tensor network methods with automatic differentiation
Masa ⭐ 35
Method of Manufactured Solutions Repository
Dqc ⭐ 34
Differentiable Quantum Chemistry (only Differentiable Density Functional Theory and Hartree Fock at the moment)
Autodiff ⭐ 34
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
Causing ⭐ 30
Causing: CAUsal INterpretation using Graphs
Cgdms ⭐ 29
Differentiable molecular simulation of proteins with a coarse-grained potential
Chainrulestestutils.jl ⭐ 29
Utilities for testing custom AD primitives.
Pennylane Forest ⭐ 28
This PennyLane plugin allows the Rigetti Forest QPUs, QVM, and wavefunction simulator to optimize quantum circuits.
Ad4sm.jl ⭐ 28
Automatic Differentiation for Solid Mechanics
Adfem.jl ⭐ 28
Innovative, efficient, and computational-graph-based finite element simulator for inverse modeling
Tfga ⭐ 27
Python package for Geometric / Clifford Algebra with TensorFlow
Jax Fenics ⭐ 27
Differentiable interface to FEniCS for JAX
Exprgrad ⭐ 26
An experimental deep learning framework for Nim
Dopt ⭐ 26
A numerical optimisation and deep learning framework for D.
Diffhask ⭐ 26
DSL for forward and reverse mode automatic differentiation in Haskell. Port of DiffSharp.
Abstractoperators.jl ⭐ 26
Abstract operators for large scale optimization in Julia
Yaoblocks.jl ⭐ 24
Standard basic quantum circuit simulator building blocks.
Omd ⭐ 23
JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"
Optimal Control Literature Software ⭐ 23
List of literature and software for optimal control and numerical optimization.
Deepflow ⭐ 20
Pytorch implementation of "DeepFlow: History Matching in the Space of Deep Generative Models"
Fwiflow.jl ⭐ 20
Elastic Full Waveform Inversion for Subsurface Flow Problems Using Intrusive Automatic Differentiation
Tensoralgdiff ⭐ 18
Automatic Differentiation for Tensor Algebras
Workshop Invdesign ⭐ 18
📐 Workshop material for optical inverse design and automatic differentiation
Autodiffr ⭐ 18
Automatic Differentiation for R
Torchquad ⭐ 17
Multidimensional numerical integration on the GPU using PyTorch
Adam ⭐ 17
ADAM implements a collection of algorithms for calculating rigid-body dynamics in Jax, CasADi, PyTorch, and Numpy.
Fastad ⭐ 16
FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
Slicemap.jl ⭐ 16
Same-same but different
Ad Lens ⭐ 15
Automatic Differentiation using Pseudo Lenses. Neat.
Tensorial.jl ⭐ 15
Statically sized tensors and related operations for Julia
Missionimpossible ⭐ 14
A concise C++17 implementation of automatic differentiation (operator overloading)
Machine Learning Summer Schools ⭐ 14
Curated materials for different machine learning related summer schools
Admc ⭐ 13
Infinite order automatic differentiation for Monte Carlo with unnormalized probability distribution
Bayex ⭐ 12
Bayesian Optimization Python Library powered by JAX
Toeffipy ⭐ 11
ToeffiPy is a PyTorch like autograd/deep learning library based only on NumPy.
Nadl ⭐ 11
A small framework that can perform automatic differentiation to calculate first-order gradients of numpy arrays.
Compas_cem ⭐ 10
Constrained form-finding of spatial structures using automatic differentiation.
Mfm Dev ⭐ 10
MFM community development code
Nlreg.jl ⭐ 9
Nonlinear regression in Julia
Dali Cython ⭐ 9
🍭 Dali in Python
Fadbadml ⭐ 9
Automatic Differentiation: FADBAD++ for OCaml
1-100 of 178 projects

Related Projects

Python Automatic Differentiation Projects (58)
Machine Learning Automatic Differentiation Projects (45)
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Julia Automatic Differentiation Projects (39)
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Advertising 📦 9
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Applications 📦 181
Artificial Intelligence 📦 72
Blockchain 📦 70
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Cloud Computing 📦 79
Code Quality 📦 28
Collaboration 📦 30
Command Line Interface 📦 48
Community 📦 81
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Compilers 📦 60
Computer Science 📦 74
Configuration Management 📦 39
Content Management 📦 167
Control Flow 📦 197
Data Formats 📦 77
Data Processing 📦 266
Data Storage 📦 132
Economics 📦 60
Frameworks 📦 198
Games 📦 122
Graphics 📦 103
Hardware 📦 148
Integrated Development Environments 📦 47
Learning Resources 📦 147
Legal 📦 28
Libraries 📦 119
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Machine Learning 📦 336
Mapping 📦 61
Marketing 📦 15
Mathematics 📦 55
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Messaging 📦 97
Networking 📦 304
Operating Systems 📦 84
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Package Managers 📦 52
Programming Languages 📦 229
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Science 📦 42
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