Autodiff Python Packages

uncertainties

Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.

2.1M 665 85

autograd-gamma

NotImplementedError: VJP of gammainc wrt argnum 0 not defined

2M 15 4

pennylane-catalyst

A JIT compiler for hybrid quantum programs in PennyLane

12K 208 71

hyperjet

Automatic differentiation with dual numbers

5K 17 4

gradgen

Autodiff from Python to Embedded Rust

3K 7 0

trace-opt

End-to-end Generative Optimization for AI Agents

2K 730 58

kineverse

Version 2.0 of Kineverse, a framework for modeling kinematics for robotic manipulation and control.

2K 3 0

mygrad

Drop-in automatic differentiation to NumPy

1K 216 22

dlux

Differentiable Optical Models as Parameterised Neural Networks in Jax using Zodiax.

1K 71 16

hypergraph

Reversed mode second order automatic differentiation for python (WIP)

1K 4 0

nabla-ml

Nabla: High-Performance Scientific Computing

995 335 13

optyx

Intuitive symbolic interface for constrained optimization problems. Write natural Python, get automatic gradients and solvers.

745 25 2

ym-pure-ml

Transparent, NumPy-only deep learning framework for teaching, small-scale projects, prototyping, and reproducible experiments. No CUDA, no giant dependency tree. Batteries included: VJP autograd, layers, activations, losses, optimizers, Zarr checkpoints, and more!

487 10 1