dLux

Source-to-Source Debuggable Derivatives in Pure Python

Deep learning in Rust, with shape checked tensors and neural networks

DiffSharp: Differentiable Functional Programming

AutoBound automatically computes upper and lower bounds on functions.

Betty: an automatic differentiation library for generalized meta-learning and multilevel optimization

Drop-in autodiff for NumPy.

Autodifferentiation package in Rust.

Minimal deep learning library written from scratch in Python, using NumPy/CuPy.

An experimental deep learning framework for Nim based on a differentiable array programming language

A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.