autodiff

Pytorch implementation of convolutional neural network visualization techniques

Source-to-Source Debuggable Derivatives in Pure Python

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

A simple library for creating complex neural networks

DiffSharp: Differentiable Functional Programming

Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.

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

Tensors and differentiable operations (like TensorFlow) in Rust

AutoBound automatically computes upper and lower bounds on functions.

Surrogate modeling and optimization for scientific machine learning (SciML)