Minkowski Engine is an auto-diff neural network library for high-dimensional sparse tensors

automatic differentiation made easier for C++

Computational graphs with reverse automatic differentation in the GPU

Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models

skscope: Sparse-Constrained OPtimization via itErative-solvers

FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.

Enzyme integration into Rust. Experimental, do not use.

AutoDiff DAG constructor, built on numpy and Cython. A Neural Turing Machine and DeepQ agent run on it. Clean code for educational purpose.

Сustom torch style machine learning framework with automatic differentiation implemented on numpy, allows build GANs, VAEs, etc.

Differentiable Reacting Flow Modeling Software

도서 머신러닝·딥러닝에 필요한 기초 수학 with 파이썬의 예제 코드와 그래프 그리는 코드 및 웹앱 저장소

Galactic and Gravitational Dynamics in Python (+ GPU and autodiff)

variational quantum circuit simulator in Julia, under GPLv3

Differentiable Gaussian Process implementation for PyTorch

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

Unitful Quantities in JAX

Auto-differentiation library for C++

JutulDarcyRules: ChainRules extension to Jutul and JutulDarcy

Fortran backward (reverse) mode automatic differentiation.