Automatic differentiation in scientific programming with jax

In scientific programming we use derivatives extensively. Automatic differentiation is a convenient tool for writing programs with derivatives where it is not necessary to approximate them, or derive and implement them. There are many applications where this is useful ranging from mathematics, optimization, property derivations, uncertainty propagation, and sensitivity analysis are just a few of them.

Updated July 17, 2024 for Python 3.11