automatic-differentiation
There are 535 repositories under automatic-differentiation topic.
ggml-org/ggml
Tensor library for machine learning
gorgonia/gorgonia
Gorgonia is a library that helps facilitate machine learning in Go.
PennyLaneAI/pennylane
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Built by researchers, for research.
stack-of-tasks/pinocchio
A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
google/tangent
Source-to-Source Debuggable Derivatives in Pure Python
autodiff/autodiff
automatic differentiation made easier for C++
nlpodyssey/spago
Self-contained Machine Learning and Natural Language Processing library in Go
ethz-adrl/control-toolbox
The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control
FluxML/Zygote.jl
21st century AD
EnzymeAD/Enzyme
High-performance automatic differentiation of LLVM and MLIR.
mratsim/Arraymancer
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
owlbarn/owl
Owl - OCaml Scientific Computing @ https://ocaml.xyz
aesara-devs/aesara
Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.
eduardoleao052/js-pytorch
A JavaScript library like PyTorch, with GPU acceleration.
peterdsharpe/AeroSandbox
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.
JuliaDiff/ForwardDiff.jl
Forward Mode Automatic Differentiation for Julia
kthohr/optim
OptimLib: a lightweight C++ library of numerical optimization methods for nonlinear functions
oreilly-japan/deep-learning-from-scratch-3
『ゼロから作る Deep Learning ❸』(O'Reilly Japan, 2020)
SciML/Optimization.jl
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.
stan-dev/math
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.
ThoughtWorksInc/DeepLearning.scala
A simple library for creating complex neural networks
ott-jax/ott
Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.
PennyLaneAI/qml
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
metaopt/torchopt
TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
breandan/kotlingrad
🧩 Shape-Safe Symbolic Differentiation with Algebraic Data Types
EnzymeAD/Enzyme.jl
Julia bindings for the Enzyme automatic differentiator
raskr/rust-autograd
Tensors and differentiable operations (like TensorFlow) in Rust
chakravala/Grassmann.jl
⟨Grassmann-Clifford-Hodge⟩ multilinear differential geometric algebra
tumaer/JAXFLUIDS
Differentiable Fluid Dynamics Package
ThoughtWorksInc/DeepDarkFantasy
A Programming Language for Deep Learning
JuliaDiff/ChainRules.jl
forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs
mentat-collective/emmy
The Emmy Computer Algebra System.
patr-schm/TinyAD
Automatic Differentiation in Geometry Processing Made Simple
auto-differentiation/xad
Powerful automatic differentiation in C++ and Python
JuliaDiff/ReverseDiff.jl
Reverse Mode Automatic Differentiation for Julia