Automatic Differentiation Python Packages

autograd

Efficiently computes derivatives of NumPy code.

pin

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

libpinocchio

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

pennylane

PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.

ott-jax

Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.

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.

aesara

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

pennylane-catalyst

A JIT compiler for hybrid quantum programs in PennyLane

neurograd

A Pure Python Deep Learning Framework with Automatic Differentiation and PyTorch-like API

aesara-nightly

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

jaxsim

A differentiable physics engine and multibody dynamics library for control and robot learning.

tesseract-core

Universal components for differentiable scientific computing. :package:

torchopt

TorchOpt is an efficient library for differentiable optimization built upon PyTorch.

llmbroker

PyTorch for Quantitative Finance : Refine Derivatives Hedging and Pricing with Architecture Alightment in Operators

semiflow-pde

Fast no_std Rust library for evolution equations and PDEs via Chernoff approximation of operator semigroups — heat, Schrödinger, diffusion, graph & manifold operators. Bindings for C, Python, and WebAssembly.

varipeps

variPEPS -- Versatile tensor network library for variational ground state simulations in two spatial dimensions

nextstat

Universal differentiable statistical inference engine (Rust + GPU). High-performance Frequentist & Bayesian modeling, RL environments, and end-to-end optimization for Science, Pharma, and Finance

hyperjet

Algorithmic differentiation with hyper-dual numbers in C++ and Python

neuralengine

An open-source framework/library for building and training neural networks in Python with support for GPUs (CUDA).

tad-mctc

PyTorch Automatic Differentiation Utility for "tad" Projects.

nanograd-bgriebel

Scalar automatic differentiation engine.

adam-robotics

adam implements a collection of algorithms for calculating rigid-body dynamics in Jax, CasADi, PyTorch, and Numpy.

asdex

Automatic Sparse Differentiation in JAX.

tad-dftd3

PyTorch Autodiff DFT-D3 Implementation.