Automatic Differentiation Python Packages

pin

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.

libpinocchio

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

tensorcircuit-nightly

The next-gen AI-native tensor-network-based quantum software framework

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.

ott-jax

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

neurograd

A Pure Python Deep Learning Framework with Automatic Differentiation

aesara

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

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.

pennylane-catalyst

A JIT compiler for hybrid quantum programs in PennyLane

torchopt

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

tad-mctc

PyTorch Automatic Differentiation Utility for "tad" Projects.

tesseract-core

Universal, autodiff-native software components for Simulation Intelligence. 📦

nextstat

High-performance statistical inference engine — MLE, Bayesian, survival, GLM, time series. Rust core with Python bindings.

varipeps

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

tensortrax

Differentiable Tensors based on NumPy Arrays

tad-dftd3

PyTorch Autodiff DFT-D3 Implementation.

hyperjet

Automatic differentiation with dual numbers

tad-multicharge

PyTorch Autodiff Multicharge (Classical Charge Models).

matadi

Material Definition with Automatic Differentiation

quantlib-risks

Fast Risks with QuantLib in Python

neuralengine

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

nanograd-bgriebel

Scalar Automatic Differentiation Engine