There are 1 repository under autodiff topic.
Deep learning in Rust, with shape checked tensors and neural networks
Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.
Betty: an automatic differentiation library for generalized meta-learning and multilevel optimization
Comprehensive automatic differentiation in C++
Autodifferentiation package in Rust.
Automatic differentiation of implicit functions
An experimental deep learning framework for Nim based on a differentiable array programming language
Minimal deep learning library written from scratch in Python, using NumPy/CuPy.
A JIT compiler for hybrid quantum programs in PennyLane
FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
Geometry processing utilities compatible with jax for autodifferentiation.
library of C++ functions that support applications of Stan in Pharmacometrics
Utilities for testing custom AD primitives.
Differentiable optical models as parameterised neural networks in Jax using Zodiax
Сustom torch style machine learning framework with automatic differentiation implemented on numpy, allows build GANs, VAEs, etc.
Fazang is a Fortran library for reverse-mode automatic differentiation, inspired by Stan/Math library.
A lightweight deep learning framework made with ❤️