Automating Adjoints with Algorithmic Differentiation

A derivation of how to use implicit differentiation in reverse-mode AD (forward-mode is similar) to compute adjoints for a generic solver. Shows how to use vector Jacobian products for efficient calculation. Ends with a simple example of how you could implement in Julia (or in another language).

[@franciscoparraguez4576]

Very interesting video. It is like the Chain Rule, attempting to find the derivative in a composition of functions. Thank you so much !!!!!!

[@jamjam2973]

Thank you! Waiting to another awsome video :)