automatic differentiation

The numerics-side name for the machinery that AI calls backpropagation — the split is deliberate (per the entity-page spec's own canonical example), because the same flower is caught whether the source speaks numerical analysis or deep learning. Reverse-mode AD computes a full gradient in a small constant multiple of the cost of the original function (the cheap-gradient principle, Griewank's bound), running a recorded computation — the Wengert list, or "tape" — backward. The vault's autodiff thread carries the Linnainmaa priority story, the forward/reverse (JVP/VJP) transpose duality, and the observation that the ML and AD communities were mutually unaware for years.

References

• claim-linnainmaa-reverse-mode-single-pass · claim-cheap-gradient-bound-two-figures · claim-jvp-vjp-transpose-duality · claim-autograd-three-reifications-of-the-tape · claim-wengert-list-named-for-forward-mode-inventor · claim-ml-and-ad-communities-mutually-unaware
• Related hubs: entity-seppo-linnainmaa · entity-andreas-griewank · entity-backpropagation · Capture: 2026-07-06-did-linnainmaa-originate-reverse-mode-automatic-differentiation-per-griewank-2012