The limits of exactness: On the failure of automatic differentiation in physics-informed machine learning
It is argued that a derivative can be numerically perfect and still be the wrong derivative for the problem at hand, because AD, by construction, has no notion of the physical structure a solution must obey.
Ameya D. Jagtap
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