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38:12
YouTube
BYU FLOW Lab
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).
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